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Namespaces</h2></td></tr>
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Data Structures</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml">AssetsLibrary</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Factory class to create and fill tensors. <a href="classarm__compute_1_1test_1_1_assets_library.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_activation_layer_fixture.xhtml">ActivationLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_activation_layer_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_alex_net_fixture.xhtml">AlexNetFixture</a></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_batch_normalization_layer_fixture.xhtml">BatchNormalizationLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_batch_normalization_layer_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">ConvolutionLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_depthwise_convolution_fixture.xhtml">DepthwiseConvolutionFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_depthwise_convolution_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_depthwise_separable_convolution_layer_fixture.xhtml">DepthwiseSeparableConvolutionLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_depthwise_separable_convolution_layer_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_floor_fixture.xhtml">FloorFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_floor_fixture.xhtml#details">More...</a><br/></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_fully_connected_layer_fixture.xhtml">FullyConnectedLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_fully_connected_layer_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_g_e_m_m_fixture.xhtml">GEMMFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_g_e_m_m_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_le_net5_fixture.xhtml">LeNet5Fixture</a></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_normalization_layer_fixture.xhtml">NormalizationLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_normalization_layer_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_pooling_layer_fixture.xhtml">PoolingLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_pooling_layer_fixture.xhtml#details">More...</a><br/></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_r_o_i_pooling_layer_fixture.xhtml">ROIPoolingLayerFixture</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fixture that can be used for NEON and CL. <a href="classarm__compute_1_1test_1_1_r_o_i_pooling_layer_fixture.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> objects. <a href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_c_l_array_accessor.xhtml">CLArrayAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_array.xhtml">CLArray</a> objects. <a href="classarm__compute_1_1test_1_1_c_l_array_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_c_l_lut_accessor.xhtml">CLLutAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_c_l_lut.xhtml">CLLut</a> objects. <a href="classarm__compute_1_1test_1_1_c_l_lut_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_i_accessor.xhtml">IAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Common interface to provide information and access to tensor like structures. <a href="classarm__compute_1_1test_1_1_i_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_i_array_accessor.xhtml">IArrayAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Common interface to provide information and access to array like structures. <a href="classarm__compute_1_1test_1_1_i_array_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_i_lut_accessor.xhtml">ILutAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Common interface to provide information and access to <a class="el" href="classarm__compute_1_1_lut.xhtml" title="Basic implementation of the LUT interface. ">Lut</a> like structures. <a href="classarm__compute_1_1test_1_1_i_lut_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> objects. <a href="classarm__compute_1_1test_1_1_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml">ArrayAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml" title="ArrayAccessor implementation for Array objects. ">ArrayAccessor</a> implementation for <a class="el" href="classarm__compute_1_1_array.xhtml">Array</a> objects. <a href="classarm__compute_1_1test_1_1_array_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_lut_accessor.xhtml">LutAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for <a class="el" href="classarm__compute_1_1_lut.xhtml">Lut</a> objects. <a href="classarm__compute_1_1test_1_1_lut_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_padding_calculator.xhtml">PaddingCalculator</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Calculate required padding. <a href="classarm__compute_1_1test_1_1_padding_calculator.xhtml#details">More...</a><br/></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_raw_lut_accessor.xhtml">RawLutAccessor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml" title="Accessor implementation for Tensor objects. ">Accessor</a> implementation for std::map-lut objects. <a href="classarm__compute_1_1test_1_1_raw_lut_accessor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subclass of <a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml" title="Simple tensor object that stores elements in a consecutive chunk of memory. ">SimpleTensor</a> using uint8_t as value type. <a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Simple tensor object that stores elements in a consecutive chunk of memory. <a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_cache.xhtml">TensorCache</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Stores <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> categorised by the image they are created from including name, format and channel. <a href="classarm__compute_1_1test_1_1_tensor_cache.xhtml#details">More...</a><br/></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structarm__compute_1_1test_1_1common__promoted__signed__type.xhtml">common_promoted_signed_type</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Find the signed promoted common type. <a href="structarm__compute_1_1test_1_1common__promoted__signed__type.xhtml#details">More...</a><br/></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="typedef-members"></a>
Typedefs</h2></td></tr>
<tr class="memitem:a74a10374253178ae54e1baab173698a1"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a74a10374253178ae54e1baab173698a1">CLActivationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_activation_layer_fixture.xhtml">ActivationLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml">CLActivationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:af80ea91532f0ebdccb3f1d8e507a98ad"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#af80ea91532f0ebdccb3f1d8e507a98ad">CLBatchNormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_batch_normalization_layer_fixture.xhtml">BatchNormalizationLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml">CLBatchNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:ad275d75e1b63f91fdc59afe026688b12"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">ConvolutionLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:a1e3870d2e47dfd84b259bdbff0a6f5f8"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1e3870d2e47dfd84b259bdbff0a6f5f8">CLDepthwiseConvolutionFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_depthwise_convolution_fixture.xhtml">DepthwiseConvolutionFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution.xhtml">CLDepthwiseConvolution</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:adc07e82b4049d653c965af2606a7d70f"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#adc07e82b4049d653c965af2606a7d70f">CLDepthwiseSeparableConvolutionLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_depthwise_separable_convolution_layer_fixture.xhtml">DepthwiseSeparableConvolutionLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_separable_convolution_layer.xhtml">CLDepthwiseSeparableConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:a4a14e383a632057e99845c74a72a6454"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4a14e383a632057e99845c74a72a6454">CLFloorFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_floor_fixture.xhtml">FloorFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_floor.xhtml">CLFloor</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:a4c33955ce3f6ed3a4d756cdebf6c8b3a"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_fully_connected_layer_fixture.xhtml">FullyConnectedLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml">CLFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:abf07c2bf7d8e9c76e146f9b21bee88fd"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#abf07c2bf7d8e9c76e146f9b21bee88fd">CLGEMMFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_g_e_m_m_fixture.xhtml">GEMMFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml">CLGEMM</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:af4f1c6ad288931f07f614316f57ed63b"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#af4f1c6ad288931f07f614316f57ed63b">CLNormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_normalization_layer_fixture.xhtml">NormalizationLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml">CLNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:a9c81648f3199d0d1c3f34a29a7a2bb8d"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_pooling_layer_fixture.xhtml">PoolingLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml">CLPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt;</td></tr>
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<tr class="memitem:a41884dec2ecae6674396802641b01060"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a41884dec2ecae6674396802641b01060">CLROIPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_r_o_i_pooling_layer_fixture.xhtml">ROIPoolingLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer.xhtml">CLROIPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>, <a class="el" href="classarm__compute_1_1_c_l_array.xhtml">CLArray</a>&lt; <a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a> &gt;, <a class="el" href="classarm__compute_1_1test_1_1_c_l_array_accessor.xhtml">CLArrayAccessor</a>&lt; <a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a> &gt;&gt;</td></tr>
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<tr class="memitem:aa631c5ec3d7cb3dab649f994e9e9217d"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa631c5ec3d7cb3dab649f994e9e9217d">CLAlexNetFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_alex_net_fixture.xhtml">AlexNetFixture</a>&lt; <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_sub_tensor.xhtml">CLSubTensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml">CLActivationLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml">CLDirectConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml">CLFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml">CLNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml">CLPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_softmax_layer.xhtml">CLSoftmaxLayer</a> &gt;</td></tr>
<tr class="separator:aa631c5ec3d7cb3dab649f994e9e9217d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae3b678c8477dd5acc5e264eae37b562c"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ae3b678c8477dd5acc5e264eae37b562c">CLLeNet5Fixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_le_net5_fixture.xhtml">LeNet5Fixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml">CLActivationLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml">CLFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml">CLPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_softmax_layer.xhtml">CLSoftmaxLayer</a> &gt;</td></tr>
<tr class="separator:ae3b678c8477dd5acc5e264eae37b562c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aeded391cb7ec7a44c41eb23544265894"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_activation_layer_fixture.xhtml">ActivationLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
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<tr class="memitem:ac7369c169e6de526fcb6f68e4a959444"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac7369c169e6de526fcb6f68e4a959444">NEBatchNormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_batch_normalization_layer_fixture.xhtml">BatchNormalizationLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer.xhtml">NEBatchNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
<tr class="separator:ac7369c169e6de526fcb6f68e4a959444"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3168ad22b6ac1e9a6996b53e5038a7a2"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">ConvolutionLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml">NEConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
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<tr class="memitem:ac8cf6873b0e9ac7334bcbc042fdc5f02"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac8cf6873b0e9ac7334bcbc042fdc5f02">NEFloorFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_floor_fixture.xhtml">FloorFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_floor.xhtml">NEFloor</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
<tr class="separator:ac8cf6873b0e9ac7334bcbc042fdc5f02"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0b4f7a523ddb2b823750ff5bdc03470c"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_fully_connected_layer_fixture.xhtml">FullyConnectedLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml">NEFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
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<tr class="memitem:a789c444c1307e85eec5f8b0d75fd5f7d"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a789c444c1307e85eec5f8b0d75fd5f7d">NEGEMMFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_g_e_m_m_fixture.xhtml">GEMMFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m.xhtml">NEGEMM</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
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<tr class="memitem:acc2c4764a300b505b50e9ba0642eff2b"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#acc2c4764a300b505b50e9ba0642eff2b">NENormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_normalization_layer_fixture.xhtml">NormalizationLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml">NENormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
<tr class="separator:acc2c4764a300b505b50e9ba0642eff2b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aafcc5ee5a13d9ed18d31591bb1d50fb0"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_pooling_layer_fixture.xhtml">PoolingLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml">NEPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt;</td></tr>
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<tr class="memitem:a7ad74154ac625702bef70b90243ae63f"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a7ad74154ac625702bef70b90243ae63f">NEROIPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_r_o_i_pooling_layer_fixture.xhtml">ROIPoolingLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer.xhtml">NEROIPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>, <a class="el" href="classarm__compute_1_1_array.xhtml">Array</a>&lt; <a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a> &gt;, <a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml">ArrayAccessor</a>&lt; <a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a> &gt;&gt;</td></tr>
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<tr class="memitem:ae0e8bcf3b0ed15e708b4a38febfdb84e"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ae0e8bcf3b0ed15e708b4a38febfdb84e">NEAlexNetFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_alex_net_fixture.xhtml">AlexNetFixture</a>&lt; <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a>, <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_sub_tensor.xhtml">SubTensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>, <a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml">NEConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml">NEConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml">NEFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml">NENormalizationLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml">NEPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_softmax_layer.xhtml">NESoftmaxLayer</a> &gt;</td></tr>
<tr class="separator:ae0e8bcf3b0ed15e708b4a38febfdb84e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6a292ad5fedcc7dea6c6eb1be6d4c0d3"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6a292ad5fedcc7dea6c6eb1be6d4c0d3">NELeNet5Fixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_le_net5_fixture.xhtml">LeNet5Fixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>, <a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml">NEConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml">NEFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml">NEPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_softmax_layer.xhtml">NESoftmaxLayer</a> &gt;</td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
Functions</h2></td></tr>
<tr class="memitem:a2fba44656470195a6245f922a1c264f5"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a2fba44656470195a6245f922a1c264f5">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af80ea91532f0ebdccb3f1d8e507a98ad">CLBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_batch_normalization_layer_dataset.xhtml">datasets::YOLOV2BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a2fba44656470195a6245f922a1c264f5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a365d9325d2bba7fbf9983f80bfe8c796"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a365d9325d2bba7fbf9983f80bfe8c796">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af80ea91532f0ebdccb3f1d8e507a98ad">CLBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_batch_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a365d9325d2bba7fbf9983f80bfe8c796"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2abd12df8c0c36eed83982ee073db2ff"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a2abd12df8c0c36eed83982ee073db2ff">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af80ea91532f0ebdccb3f1d8e507a98ad">CLBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_batch_normalization_layer_dataset.xhtml">datasets::YOLOV2BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a2abd12df8c0c36eed83982ee073db2ff"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8457ac77df7a142e86354ac08fd5ba30"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a8457ac77df7a142e86354ac08fd5ba30">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af80ea91532f0ebdccb3f1d8e507a98ad">CLBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_batch_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a80d1181d85aefe33d6a8720152dba80b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a80d1181d85aefe33d6a8720152dba80b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset.xhtml">datasets::AlexNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a80d1181d85aefe33d6a8720152dba80b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac18e51057a61f7db456d1c8b9b03aa09"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac18e51057a61f7db456d1c8b9b03aa09">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml">datasets::LeNet5ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:ac18e51057a61f7db456d1c8b9b03aa09"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3e452462cb397897f476f6d83b468914"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a3e452462cb397897f476f6d83b468914">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a3e452462cb397897f476f6d83b468914"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aecd85eec5df288174be9b7e0fac6d1fe"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aecd85eec5df288174be9b7e0fac6d1fe">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:aecd85eec5df288174be9b7e0fac6d1fe"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aea25c6951a5d4bcfeb95750105154506"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aea25c6951a5d4bcfeb95750105154506">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:ac62a5389a4a60e89fabb6bb2153adfc5"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac62a5389a4a60e89fabb6bb2153adfc5">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset.xhtml">datasets::AlexNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:ac62a5389a4a60e89fabb6bb2153adfc5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a65a028ab7f8ba81db43d5963ea5343a4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a65a028ab7f8ba81db43d5963ea5343a4">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml">datasets::LeNet5ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a65a028ab7f8ba81db43d5963ea5343a4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6773bc983eece85b34d67c4ba3c09554"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6773bc983eece85b34d67c4ba3c09554">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a6773bc983eece85b34d67c4ba3c09554"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4bdfdac4318cf7e4b09cc13a553363a7"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4bdfdac4318cf7e4b09cc13a553363a7">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a4bdfdac4318cf7e4b09cc13a553363a7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a34df6fb97233366fc9083d79c13a5737"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a34df6fb97233366fc9083d79c13a5737">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a34df6fb97233366fc9083d79c13a5737"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5a371e1a37be130dc9e8c905cd5efc29"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a5a371e1a37be130dc9e8c905cd5efc29">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml">datasets::VGG16ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4})))</td></tr>
<tr class="separator:a5a371e1a37be130dc9e8c905cd5efc29"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7473924d4fdf2b5dec0d8ee9aa11e25d"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a7473924d4fdf2b5dec0d8ee9aa11e25d">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset.xhtml">datasets::YOLOV2ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
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<tr class="memitem:ad7d919409d3d679cfbf28b2dae757fec"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad7d919409d3d679cfbf28b2dae757fec">REGISTER_FIXTURE_DATA_TEST_CASE</a> (MobileNetDepthwiseConvolution, <a class="el" href="namespacearm__compute_1_1test.xhtml#a1e3870d2e47dfd84b259bdbff0a6f5f8">CLDepthwiseConvolutionFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_mobile_net_depthwise_convolution_dataset.xhtml">datasets::MobileNetDepthwiseConvolutionDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1})))</td></tr>
<tr class="separator:ad7d919409d3d679cfbf28b2dae757fec"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1f4b9eae17da2aebc223b0fdeee74cea"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1f4b9eae17da2aebc223b0fdeee74cea">REGISTER_FIXTURE_DATA_TEST_CASE</a> (MobileNetDepthwiseSeparableConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#adc07e82b4049d653c965af2606a7d70f">CLDepthwiseSeparableConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_mobile_net_depthwise_separable_convolution_layer_dataset.xhtml">datasets::MobileNetDepthwiseSeparableConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1})))</td></tr>
<tr class="separator:a1f4b9eae17da2aebc223b0fdeee74cea"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad52c9735c67d5972016f143cd15ea874"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad52c9735c67d5972016f143cd15ea874">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_direct_convolution_layer_dataset.xhtml">datasets::AlexNetDirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:ad52c9735c67d5972016f143cd15ea874"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa971f54dfef950c44d8973db82b91e4e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa971f54dfef950c44d8973db82b91e4e">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:aa971f54dfef950c44d8973db82b91e4e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa0a358cbff96894b77c9b3cfba3c2db4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa0a358cbff96894b77c9b3cfba3c2db4">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:afd1574f92e2d5a179c3c7f0e8e438bba"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#afd1574f92e2d5a179c3c7f0e8e438bba">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a91a53a55f1c814837ea5374d1c2095e8"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a91a53a55f1c814837ea5374d1c2095e8">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_direct_convolution_layer_dataset.xhtml">datasets::AlexNetDirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a91a53a55f1c814837ea5374d1c2095e8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a959373f15eeea41ce740f0bc0ce2244a"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a959373f15eeea41ce740f0bc0ce2244a">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:abb38304d29f99717ecc5c528962972a5"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#abb38304d29f99717ecc5c528962972a5">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:ae88c882e06dad040d2bb6278ef8c4c84"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ae88c882e06dad040d2bb6278ef8c4c84">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:ab0595cda883cec6b1b3a5389fd786e9f"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ab0595cda883cec6b1b3a5389fd786e9f">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml">datasets::VGG16ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
<tr class="separator:ab0595cda883cec6b1b3a5389fd786e9f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aabdb95f3f541376f38e03d63957cd0af"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aabdb95f3f541376f38e03d63957cd0af">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset.xhtml">datasets::YOLOV2ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
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<tr class="memitem:a6e81878e7ca8fecdd9f6e6bcc2a7b794"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6e81878e7ca8fecdd9f6e6bcc2a7b794">REGISTER_FIXTURE_DATA_TEST_CASE</a> (Floor, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4a14e383a632057e99845c74a72a6454">CLFloorFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml">datasets::SmallShapes</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:ae5411ce056673117b799d20c1c9484dd"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ae5411ce056673117b799d20c1c9484dd">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetFullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_fully_connected_layer_dataset.xhtml">datasets::AlexNetFullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:ae63877ff99387d51d4abc340a50f1093"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ae63877ff99387d51d4abc340a50f1093">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_fully_connected_layer_dataset.xhtml">datasets::LeNet5FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a49ab3e510552d29b5698d55ef52674c3"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a49ab3e510552d29b5698d55ef52674c3">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_fully_connected_layer_dataset.xhtml">datasets::VGG16FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a8cf1a9e06ce42b8ff57bf13aa2c2c047"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a8cf1a9e06ce42b8ff57bf13aa2c2c047">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a8388dbd479dceaffb21c8fc564c5c420"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a8388dbd479dceaffb21c8fc564c5c420">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:ab8549a72a0983f5281a5612979669e2d"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ab8549a72a0983f5281a5612979669e2d">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetFullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_fully_connected_layer_dataset.xhtml">datasets::AlexNetFullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:adb9a698039f2f9414f3296a4d9070893"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#adb9a698039f2f9414f3296a4d9070893">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_fully_connected_layer_dataset.xhtml">datasets::LeNet5FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a6fef2cd462f91f3b071ee7d02322dbb6"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6fef2cd462f91f3b071ee7d02322dbb6">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_fully_connected_layer_dataset.xhtml">datasets::VGG16FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a463d7f372ea5c6217b8ee151b47f596e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a463d7f372ea5c6217b8ee151b47f596e">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:ad5d101b25bb35a8d9b1efc70102bb3a4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad5d101b25bb35a8d9b1efc70102bb3a4">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a2b1950a60a98dec32a7ca7531fded8ad"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a2b1950a60a98dec32a7ca7531fded8ad">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1GEMM, <a class="el" href="namespacearm__compute_1_1test.xhtml#abf07c2bf7d8e9c76e146f9b21bee88fd">CLGEMMFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_g_e_m_m_dataset.xhtml">datasets::GoogLeNetInceptionV1GEMMDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:aef76c7b3cf7d1e3c6fc7ff96804a5753"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aef76c7b3cf7d1e3c6fc7ff96804a5753">REGISTER_FIXTURE_DATA_TEST_CASE</a> (MatrixMultiplyGEMM, <a class="el" href="namespacearm__compute_1_1test.xhtml#abf07c2bf7d8e9c76e146f9b21bee88fd">CLGEMMFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_matrix_multiply_g_e_m_m_dataset.xhtml">datasets::MatrixMultiplyGEMMDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:af935c08091163839aead6ac3023c2147"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#af935c08091163839aead6ac3023c2147">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogleNetGEMM, <a class="el" href="namespacearm__compute_1_1test.xhtml#abf07c2bf7d8e9c76e146f9b21bee88fd">CLGEMMFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_google_net_g_e_m_m_dataset.xhtml">datasets::GoogleNetGEMMDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:a70d28ab3b5936a6454451d42f3c170f3"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a70d28ab3b5936a6454451d42f3c170f3">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af4f1c6ad288931f07f614316f57ed63b">CLNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_normalization_layer_dataset.xhtml">datasets::AlexNetNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:afc6ba7f0f4b792e2df1270d8f83f138d"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#afc6ba7f0f4b792e2df1270d8f83f138d">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1NormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af4f1c6ad288931f07f614316f57ed63b">CLNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1NormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:ae4dd72b2a2e5af0c89c5ce7d2443e115"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ae4dd72b2a2e5af0c89c5ce7d2443e115">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af4f1c6ad288931f07f614316f57ed63b">CLNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_normalization_layer_dataset.xhtml">datasets::AlexNetNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a62af6d63be834c648f251c0497e7b59f"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a62af6d63be834c648f251c0497e7b59f">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1NormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#af4f1c6ad288931f07f614316f57ed63b">CLNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1NormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a0e999f1d9f9608da6fb4bbde4afc078e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a0e999f1d9f9608da6fb4bbde4afc078e">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_pooling_layer_dataset.xhtml">datasets::AlexNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a0889351f9ee837c8009925f17dd4688b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a0889351f9ee837c8009925f17dd4688b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_pooling_layer_dataset.xhtml">datasets::LeNet5PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a903e3acaf54969c5d276058e979a753c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a903e3acaf54969c5d276058e979a753c">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a85078031088e419e7f928e5ad5bbafa9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a85078031088e419e7f928e5ad5bbafa9">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a27cf9c407e83adbf0c837240a6bc3534"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a27cf9c407e83adbf0c837240a6bc3534">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_pooling_layer_dataset.xhtml">datasets::SqueezeNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:afd017468a129b6650b73cb65ecc40516"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#afd017468a129b6650b73cb65ecc40516">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_pooling_layer_dataset.xhtml">datasets::VGG16PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a36cad137a713f8be3263a1a6466c6bd7"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a36cad137a713f8be3263a1a6466c6bd7">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_pooling_layer_dataset.xhtml">datasets::YOLOV2PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a4558b577be27af2ceffffd986b1aab7f"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4558b577be27af2ceffffd986b1aab7f">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_pooling_layer_dataset.xhtml">datasets::AlexNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a731977f1de2e0d6dd1512818540ab608"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a731977f1de2e0d6dd1512818540ab608">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_pooling_layer_dataset.xhtml">datasets::LeNet5PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a967825a64c529b573ca62e74179ee921"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a967825a64c529b573ca62e74179ee921">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:ac06bd6612edf1bbb0c0f4b0d4aa86b32"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac06bd6612edf1bbb0c0f4b0d4aa86b32">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a5f97a3f0575116d348f47489487d4214"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a5f97a3f0575116d348f47489487d4214">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_pooling_layer_dataset.xhtml">datasets::SqueezeNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a6a51ef57457c994f04d0b54e76387add"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6a51ef57457c994f04d0b54e76387add">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_pooling_layer_dataset.xhtml">datasets::VGG16PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a7d579c9d463693975486ea2248adc966"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a7d579c9d463693975486ea2248adc966">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_pooling_layer_dataset.xhtml">datasets::YOLOV2PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:ac7d54f1a842ebb07f378846c21ccbe97"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac7d54f1a842ebb07f378846c21ccbe97">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SmallROIPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a41884dec2ecae6674396802641b01060">CLROIPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_r_o_i_pooling_layer_dataset.xhtml">datasets::SmallROIPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;DataType&quot;,{DataType::F16, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>})), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
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<tr class="memitem:a69b2d4f81544c38878bd196d49d41360"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a69b2d4f81544c38878bd196d49d41360">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNet, <a class="el" href="namespacearm__compute_1_1test.xhtml#aa631c5ec3d7cb3dab649f994e9e9217d">CLAlexNetFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;DataType&quot;,{DataType::F16, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>}), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
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<tr class="memitem:a485c6b6af55e2f12c1b7ef40546c08f7"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a485c6b6af55e2f12c1b7ef40546c08f7">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5, <a class="el" href="namespacearm__compute_1_1test.xhtml#ae3b678c8477dd5acc5e264eae37b562c">CLLeNet5Fixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8}))</td></tr>
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<tr class="memitem:abfd4fd028574ac46a9d056e7a1ead6f7"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#abfd4fd028574ac46a9d056e7a1ead6f7">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_activation_layer_dataset.xhtml">datasets::AlexNetActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a70381b263268259b4b6fbff88a0526c4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a70381b263268259b4b6fbff88a0526c4">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_activation_layer_dataset.xhtml">datasets::LeNet5ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a70381b263268259b4b6fbff88a0526c4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:add697a0c19a1638874c37d5d15fc2d83"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#add697a0c19a1638874c37d5d15fc2d83">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_activation_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a117bc733390c845f7493e6dad0b75191"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a117bc733390c845f7493e6dad0b75191">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_activation_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a117bc733390c845f7493e6dad0b75191"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a70f04129817692e0b5727fb542f9153c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a70f04129817692e0b5727fb542f9153c">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_activation_layer_dataset.xhtml">datasets::SqueezeNetActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:ab10eddd065a1bdb9c6b09cb1e1382f5a"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ab10eddd065a1bdb9c6b09cb1e1382f5a">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_activation_layer_dataset.xhtml">datasets::VGG16ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a572b94c09ce496eda95d8d544dc1c4d1"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a572b94c09ce496eda95d8d544dc1c4d1">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_activation_layer_dataset.xhtml">datasets::YOLOV2ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a7677396611ac11166c6f7344f9e0ef12"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a7677396611ac11166c6f7344f9e0ef12">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_activation_layer_dataset.xhtml">datasets::AlexNetActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a1afabd3008ddf541288b01fe746ab284"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1afabd3008ddf541288b01fe746ab284">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_activation_layer_dataset.xhtml">datasets::LeNet5ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a164c7e1e8e2e4de0ce6282d2b0835dd0"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a164c7e1e8e2e4de0ce6282d2b0835dd0">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_activation_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a6ada452bc1053385b8574f38d341ffc9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6ada452bc1053385b8574f38d341ffc9">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_activation_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a6692a58c12e2eff315715e6c971d0230"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6692a58c12e2eff315715e6c971d0230">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_activation_layer_dataset.xhtml">datasets::SqueezeNetActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a6692a58c12e2eff315715e6c971d0230"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a26e3678291b5f879d82808eda0d39bc2"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a26e3678291b5f879d82808eda0d39bc2">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_activation_layer_dataset.xhtml">datasets::VGG16ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a26e3678291b5f879d82808eda0d39bc2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab77581768cf2f7433ba92c2b42c4617e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ab77581768cf2f7433ba92c2b42c4617e">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2ActivationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_activation_layer_dataset.xhtml">datasets::YOLOV2ActivationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:ab77581768cf2f7433ba92c2b42c4617e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9e4dd8377091a877cf271bb34f2ed7da"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9e4dd8377091a877cf271bb34f2ed7da">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ac7369c169e6de526fcb6f68e4a959444">NEBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_batch_normalization_layer_dataset.xhtml">datasets::YOLOV2BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a9e4dd8377091a877cf271bb34f2ed7da"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a09be4cd69df94f0929598f03b32001f0"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a09be4cd69df94f0929598f03b32001f0">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ac7369c169e6de526fcb6f68e4a959444">NEBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_batch_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:aa37f90a45822a6f45002ad5fd1e69560"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa37f90a45822a6f45002ad5fd1e69560">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ac7369c169e6de526fcb6f68e4a959444">NEBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_batch_normalization_layer_dataset.xhtml">datasets::YOLOV2BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:aa93e94a58a377d2493868e24d746531b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa93e94a58a377d2493868e24d746531b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4BatchNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#ac7369c169e6de526fcb6f68e4a959444">NEBatchNormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_batch_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a4fc639ce3410d3609337137d44a68ac9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4fc639ce3410d3609337137d44a68ac9">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset.xhtml">datasets::AlexNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a7da7dbada8d8e076c78d1402743b7de9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a7da7dbada8d8e076c78d1402743b7de9">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml">datasets::LeNet5ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a7da7dbada8d8e076c78d1402743b7de9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9c30ac20d9eae69db3b004f36d8efaca"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9c30ac20d9eae69db3b004f36d8efaca">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:abe4e6a4ff5c68a5403ec4dc38149d097"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#abe4e6a4ff5c68a5403ec4dc38149d097">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a2a91a938df2a246bb92811fe90bf5ee0"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a2a91a938df2a246bb92811fe90bf5ee0">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a2a91a938df2a246bb92811fe90bf5ee0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8c86e43926d24040dbbc73e5ad638dea"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a8c86e43926d24040dbbc73e5ad638dea">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_convolution_layer_dataset.xhtml">datasets::AlexNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a8c86e43926d24040dbbc73e5ad638dea"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11c4e187683f0687472d48d8f279c8fc"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a11c4e187683f0687472d48d8f279c8fc">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_convolution_layer_dataset.xhtml">datasets::LeNet5ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a3df552423cbf598c725b9dc615f06315"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a3df552423cbf598c725b9dc615f06315">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a4470fc8180788f756fccdb77f9a25886"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4470fc8180788f756fccdb77f9a25886">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a029d80ad64be335749e827cc64efd88c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a029d80ad64be335749e827cc64efd88c">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a68166bcb788035f5a6c17fe0c68ae730"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a68166bcb788035f5a6c17fe0c68ae730">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml">datasets::VGG16ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4})))</td></tr>
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<tr class="memitem:a0ca04d4de125be45c16b579b43d53835"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a0ca04d4de125be45c16b579b43d53835">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2ConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset.xhtml">datasets::YOLOV2ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
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<tr class="memitem:abe7167f9af260495f067dd8f36251a3b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#abe7167f9af260495f067dd8f36251a3b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_direct_convolution_layer_dataset.xhtml">datasets::AlexNetDirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:adc3f7b3f1d06144af1980e8705253583"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#adc3f7b3f1d06144af1980e8705253583">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a9cc3e01ede750344f389191184d4682d"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9cc3e01ede750344f389191184d4682d">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a9c7a41c764eb85334c2d75df71d40cc4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9c7a41c764eb85334c2d75df71d40cc4">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:ad8c07298bae2d7cd7ace3ad869371b0b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad8c07298bae2d7cd7ace3ad869371b0b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_direct_convolution_layer_dataset.xhtml">datasets::AlexNetDirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:ad8c07298bae2d7cd7ace3ad869371b0b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a981537b01124fe1025ab51dfe0dde1ee"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a981537b01124fe1025ab51dfe0dde1ee">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a981537b01124fe1025ab51dfe0dde1ee"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a27446bd5b343d26d6028cd2ab34065a6"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a27446bd5b343d26d6028cd2ab34065a6">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_direct_convolution_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a27446bd5b343d26d6028cd2ab34065a6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a13170587db62e123a041d2b8cab82ef8"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a13170587db62e123a041d2b8cab82ef8">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetDirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_convolution_layer_dataset.xhtml">datasets::SqueezeNetConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a1f92978c7363135053baa95b94501676"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1f92978c7363135053baa95b94501676">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_convolution_layer_dataset.xhtml">datasets::VGG16ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
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<tr class="memitem:af3310a6693b1d28b4d474e2a025b8777"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#af3310a6693b1d28b4d474e2a025b8777">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2DirectConvolutionLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_convolution_layer_dataset.xhtml">datasets::YOLOV2ConvolutionLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
<tr class="separator:af3310a6693b1d28b4d474e2a025b8777"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6faf0b684dd2c7e5bb111dd8f8f8c6f1"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a6faf0b684dd2c7e5bb111dd8f8f8c6f1">REGISTER_FIXTURE_DATA_TEST_CASE</a> (Floor, <a class="el" href="namespacearm__compute_1_1test.xhtml#ac8cf6873b0e9ac7334bcbc042fdc5f02">NEFloorFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_shapes.xhtml">datasets::SmallShapes</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:a16176f104b13866fa9c0379d3fd9ef1f"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a16176f104b13866fa9c0379d3fd9ef1f">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetFullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_fully_connected_layer_dataset.xhtml">datasets::AlexNetFullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:ad83dbea09b27679e5c1d7950ae035f3a"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad83dbea09b27679e5c1d7950ae035f3a">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_fully_connected_layer_dataset.xhtml">datasets::LeNet5FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a597d20f8105ae670eccdc44b0486ad4e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a597d20f8105ae670eccdc44b0486ad4e">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_fully_connected_layer_dataset.xhtml">datasets::VGG16FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a033a42b308036c4e46a8bef7536d88f9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a033a42b308036c4e46a8bef7536d88f9">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a4b45a5a8afe0c81a4aafef1ba2ba96e8"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4b45a5a8afe0c81a4aafef1ba2ba96e8">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a4325316dca63988d0c63c8e761143557"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4325316dca63988d0c63c8e761143557">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetFullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_fully_connected_layer_dataset.xhtml">datasets::AlexNetFullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a4ecb06077e2a789221648d0479e61809"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4ecb06077e2a789221648d0479e61809">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_fully_connected_layer_dataset.xhtml">datasets::LeNet5FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:adeee41f0a436718ca296fc99f2e2a151"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#adeee41f0a436718ca296fc99f2e2a151">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_fully_connected_layer_dataset.xhtml">datasets::VGG16FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:af5e14e7ca5ce517a75fb019b02108797"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#af5e14e7ca5ce517a75fb019b02108797">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a1d77d86fcdca1b8578756eae70fcac85"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1d77d86fcdca1b8578756eae70fcac85">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4FullyConnectedLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_fully_connected_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4FullyConnectedLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a1d515029981b77ba7d02f20251013a3b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1d515029981b77ba7d02f20251013a3b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1GEMM, <a class="el" href="namespacearm__compute_1_1test.xhtml#a789c444c1307e85eec5f8b0d75fd5f7d">NEGEMMFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_g_e_m_m_dataset.xhtml">datasets::GoogLeNetInceptionV1GEMMDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:a5dbda869f12c5e1ffa17a2dce7e82609"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a5dbda869f12c5e1ffa17a2dce7e82609">REGISTER_FIXTURE_DATA_TEST_CASE</a> (MatrixMultiplyGEMM, <a class="el" href="namespacearm__compute_1_1test.xhtml#a789c444c1307e85eec5f8b0d75fd5f7d">NEGEMMFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_matrix_multiply_g_e_m_m_dataset.xhtml">datasets::MatrixMultiplyGEMMDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:ac9eaa20c5215f43c16202896b7ea9118"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac9eaa20c5215f43c16202896b7ea9118">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogleNetGEMM, <a class="el" href="namespacearm__compute_1_1test.xhtml#a789c444c1307e85eec5f8b0d75fd5f7d">NEGEMMFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_google_net_g_e_m_m_dataset.xhtml">datasets::GoogleNetGEMMDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>))</td></tr>
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<tr class="memitem:a3d815590d056717dde89027c469fba5a"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a3d815590d056717dde89027c469fba5a">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#acc2c4764a300b505b50e9ba0642eff2b">NENormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_normalization_layer_dataset.xhtml">datasets::AlexNetNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a04a6f03a4f0b85f507735cd409a8b74d"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a04a6f03a4f0b85f507735cd409a8b74d">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1NormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#acc2c4764a300b505b50e9ba0642eff2b">NENormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1NormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a04a6f03a4f0b85f507735cd409a8b74d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a962c45074ad2b94899bc7003b3db0509"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a962c45074ad2b94899bc7003b3db0509">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetNormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#acc2c4764a300b505b50e9ba0642eff2b">NENormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_normalization_layer_dataset.xhtml">datasets::AlexNetNormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:ab17878545b689878d626f8e2298d2b1b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ab17878545b689878d626f8e2298d2b1b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1NormalizationLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#acc2c4764a300b505b50e9ba0642eff2b">NENormalizationLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_normalization_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1NormalizationLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:af33a8fe45c20501be3c2fa7aaa32bf26"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#af33a8fe45c20501be3c2fa7aaa32bf26">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_pooling_layer_dataset.xhtml">datasets::AlexNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a7d7ea7b966b70d0931772f51a2cfcdb0"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a7d7ea7b966b70d0931772f51a2cfcdb0">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_pooling_layer_dataset.xhtml">datasets::LeNet5PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a7d7ea7b966b70d0931772f51a2cfcdb0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac4a14a4ebd0a6067fa657e06d6e6d9ec"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac4a14a4ebd0a6067fa657e06d6e6d9ec">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:ac4a14a4ebd0a6067fa657e06d6e6d9ec"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a97400b4e200d00d86169b2afc584d2e3"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a97400b4e200d00d86169b2afc584d2e3">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:a97400b4e200d00d86169b2afc584d2e3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa7edcfdce59bb3cb0f1ed784a28fb6d2"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa7edcfdce59bb3cb0f1ed784a28fb6d2">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_pooling_layer_dataset.xhtml">datasets::SqueezeNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:aa7edcfdce59bb3cb0f1ed784a28fb6d2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab644feafdb4a10f39c7e4acca32744eb"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ab644feafdb4a10f39c7e4acca32744eb">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_pooling_layer_dataset.xhtml">datasets::VGG16PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
<tr class="separator:ab644feafdb4a10f39c7e4acca32744eb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a49f6de6126e559d77c77ec1252ead9e1"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a49f6de6126e559d77c77ec1252ead9e1">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_pooling_layer_dataset.xhtml">datasets::YOLOV2PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;, 1)))</td></tr>
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<tr class="memitem:a8050efac909e6e8fce5791d2205fe0a8"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a8050efac909e6e8fce5791d2205fe0a8">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_alex_net_pooling_layer_dataset.xhtml">datasets::AlexNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
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<tr class="memitem:a0a1da94fb11977ec74784861c2c56246"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a0a1da94fb11977ec74784861c2c56246">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_le_net5_pooling_layer_dataset.xhtml">datasets::LeNet5PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a0a1da94fb11977ec74784861c2c56246"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad5101e30d9b5306231c7ed2ce71f350b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad5101e30d9b5306231c7ed2ce71f350b">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV1PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV1PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:ad5101e30d9b5306231c7ed2ce71f350b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad0b2b0d1564cc6c5ac951a7b8e59bda8"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad0b2b0d1564cc6c5ac951a7b8e59bda8">REGISTER_FIXTURE_DATA_TEST_CASE</a> (GoogLeNetInceptionV4PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_pooling_layer_dataset.xhtml">datasets::GoogLeNetInceptionV4PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:ad0b2b0d1564cc6c5ac951a7b8e59bda8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa973f66482fdadbd2ab72cdb6face4b5"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa973f66482fdadbd2ab72cdb6face4b5">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SqueezeNetPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_squeeze_net_pooling_layer_dataset.xhtml">datasets::SqueezeNetPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:aa973f66482fdadbd2ab72cdb6face4b5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9adba78f24e5c87b2c95a1c5e23883e9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9adba78f24e5c87b2c95a1c5e23883e9">REGISTER_FIXTURE_DATA_TEST_CASE</a> (VGG16PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_v_g_g16_pooling_layer_dataset.xhtml">datasets::VGG16PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a9adba78f24e5c87b2c95a1c5e23883e9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a03474ce6764bea95de0edb583d281017"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a03474ce6764bea95de0edb583d281017">REGISTER_FIXTURE_DATA_TEST_CASE</a> (YOLOV2PoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfad791cd54143e331164a2b216451a5dd3">framework::DatasetMode::NIGHTLY</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_y_o_l_o_v2_pooling_layer_dataset.xhtml">datasets::YOLOV2PoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a>), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{4, 8})))</td></tr>
<tr class="separator:a03474ce6764bea95de0edb583d281017"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa14390b7bed93ce327f5dedd89fc8928"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa14390b7bed93ce327f5dedd89fc8928">REGISTER_FIXTURE_DATA_TEST_CASE</a> (SmallROIPoolingLayer, <a class="el" href="namespacearm__compute_1_1test.xhtml#a7ad74154ac625702bef70b90243ae63f">NEROIPoolingLayerFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(<a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_small_r_o_i_pooling_layer_dataset.xhtml">datasets::SmallROIPoolingLayerDataset</a>(), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;DataType&quot;,{DataType::F32})), <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
<tr class="separator:aa14390b7bed93ce327f5dedd89fc8928"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4fa3f7aa92292c25a9876a3b1cded7c9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4fa3f7aa92292c25a9876a3b1cded7c9">REGISTER_FIXTURE_DATA_TEST_CASE</a> (AlexNet, <a class="el" href="namespacearm__compute_1_1test.xhtml#ae0e8bcf3b0ed15e708b4a38febfdb84e">NEAlexNetFixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a6f4fa4bb0583f29e77138fb1e7d77411">framework::dataset::combine</a>(alex_net_data_types, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8})))</td></tr>
<tr class="separator:a4fa3f7aa92292c25a9876a3b1cded7c9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9ba464da0fc25dbd0cb96fe5c61494c4"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9ba464da0fc25dbd0cb96fe5c61494c4">REGISTER_FIXTURE_DATA_TEST_CASE</a> (LeNet5, <a class="el" href="namespacearm__compute_1_1test.xhtml#a6a292ad5fedcc7dea6c6eb1be6d4c0d3">NELeNet5Fixture</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;Batches&quot;,{1, 4, 8}))</td></tr>
<tr class="separator:a9ba464da0fc25dbd0cb96fe5c61494c4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a629633220b1b91a871c57b679b9f06e3"><td class="memTemplParams" colspan="2">template&lt;typename O , typename F , typename... As&gt; </td></tr>
<tr class="memitem:a629633220b1b91a871c57b679b9f06e3"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a629633220b1b91a871c57b679b9f06e3">apply</a> (O *obj, F &amp;&amp;func, const std::tuple&lt; As...&gt; &amp;args)</td></tr>
<tr class="separator:a629633220b1b91a871c57b679b9f06e3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa18932675cbb5eb9c9dbf8ff4d7106c7"><td class="memTemplParams" colspan="2">template&lt;typename T , typename std::enable_if&lt; std::is_same&lt; typename T::value_type, std::string &gt;::value, int &gt;::type = 0&gt; </td></tr>
<tr class="memitem:aa18932675cbb5eb9c9dbf8ff4d7106c7"><td class="memTemplItemLeft" align="right" valign="top">std::string&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aa18932675cbb5eb9c9dbf8ff4d7106c7">join</a> (T first, T last, const std::string &amp;separator)</td></tr>
<tr class="memdesc:aa18932675cbb5eb9c9dbf8ff4d7106c7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Helper function to concatenate multiple strings. <a href="#aa18932675cbb5eb9c9dbf8ff4d7106c7">More...</a><br/></td></tr>
<tr class="separator:aa18932675cbb5eb9c9dbf8ff4d7106c7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a898a0423aace06af0f3a18a26a972a1a"><td class="memTemplParams" colspan="2">template&lt;typename T , typename UnaryOp &gt; </td></tr>
<tr class="memitem:a898a0423aace06af0f3a18a26a972a1a"><td class="memTemplItemLeft" align="right" valign="top">std::string&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a898a0423aace06af0f3a18a26a972a1a">join</a> (T &amp;&amp;first, T &amp;&amp;last, const std::string &amp;separator, UnaryOp &amp;&amp;op)</td></tr>
<tr class="memdesc:a898a0423aace06af0f3a18a26a972a1a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Helper function to concatenate multiple values. <a href="#a898a0423aace06af0f3a18a26a972a1a">More...</a><br/></td></tr>
<tr class="separator:a898a0423aace06af0f3a18a26a972a1a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a69835710fc772315f4e65ce156034530"><td class="memTemplParams" colspan="2">template&lt;typename T , typename std::enable_if&lt; std::is_arithmetic&lt; typename T::value_type &gt;::value, int &gt;::type = 0&gt; </td></tr>
<tr class="memitem:a69835710fc772315f4e65ce156034530"><td class="memTemplItemLeft" align="right" valign="top">std::string&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a69835710fc772315f4e65ce156034530">join</a> (T &amp;&amp;first, T &amp;&amp;last, const std::string &amp;separator)</td></tr>
<tr class="memdesc:a69835710fc772315f4e65ce156034530"><td class="mdescLeft">&#160;</td><td class="mdescRight">Helper function to concatenate multiple values. <a href="#a69835710fc772315f4e65ce156034530">More...</a><br/></td></tr>
<tr class="separator:a69835710fc772315f4e65ce156034530"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5b67cbf475b1e1d3bec9b0b937fdafac"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a5b67cbf475b1e1d3bec9b0b937fdafac">tolower</a> (std::string string)</td></tr>
<tr class="memdesc:a5b67cbf475b1e1d3bec9b0b937fdafac"><td class="mdescLeft">&#160;</td><td class="mdescRight">Convert string to lower case. <a href="#a5b67cbf475b1e1d3bec9b0b937fdafac">More...</a><br/></td></tr>
<tr class="separator:a5b67cbf475b1e1d3bec9b0b937fdafac"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8939810976531494e8db1f491bf61a35"><td class="memTemplParams" colspan="2">template&lt;typename D , typename T , typename... Ts&gt; </td></tr>
<tr class="memitem:a8939810976531494e8db1f491bf61a35"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a8939810976531494e8db1f491bf61a35">fill_tensors</a> (D &amp;&amp;dist, std::initializer_list&lt; int &gt; seeds, T &amp;&amp;tensor, Ts &amp;&amp;...other_tensors)</td></tr>
<tr class="separator:a8939810976531494e8db1f491bf61a35"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a28edc8880596d14c099f3c2509efc8b3"><td class="memTemplParams" colspan="2">template&lt;typename U &gt; </td></tr>
<tr class="memitem:a28edc8880596d14c099f3c2509efc8b3"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a> (<a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a>&lt; U &gt; &amp;tensor1, <a class="el" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a>&lt; U &gt; &amp;tensor2)</td></tr>
<tr class="separator:a28edc8880596d14c099f3c2509efc8b3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af4bcf30f8c56f547f66d61c7c5ae01db"><td class="memTemplParams" colspan="2">template&lt;typename T , typename = typename std::enable_if&lt;std::is_floating_point&lt;T&gt;::value&gt;::type&gt; </td></tr>
<tr class="memitem:af4bcf30f8c56f547f66d61c7c5ae01db"><td class="memTemplItemLeft" align="right" valign="top">T&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#af4bcf30f8c56f547f66d61c7c5ae01db">round_half_up</a> (T <a class="el" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>)</td></tr>
<tr class="memdesc:af4bcf30f8c56f547f66d61c7c5ae01db"><td class="mdescLeft">&#160;</td><td class="mdescRight">Round floating-point value with half value rounding to positive infinity. <a href="#af4bcf30f8c56f547f66d61c7c5ae01db">More...</a><br/></td></tr>
<tr class="separator:af4bcf30f8c56f547f66d61c7c5ae01db"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad93bb148a873f19ad7692756e59617f4"><td class="memTemplParams" colspan="2">template&lt;typename T , typename = typename std::enable_if&lt;std::is_floating_point&lt;T&gt;::value&gt;::type&gt; </td></tr>
<tr class="memitem:ad93bb148a873f19ad7692756e59617f4"><td class="memTemplItemLeft" align="right" valign="top">T&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad93bb148a873f19ad7692756e59617f4">round_half_even</a> (T <a class="el" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>, T epsilon=std::numeric_limits&lt; T &gt;::epsilon())</td></tr>
<tr class="memdesc:ad93bb148a873f19ad7692756e59617f4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Round floating-point value with half value rounding to nearest even. <a href="#ad93bb148a873f19ad7692756e59617f4">More...</a><br/></td></tr>
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<tr class="memdesc:aa337ab76176f3c4193642ac6de3a61cf"><td class="mdescLeft">&#160;</td><td class="mdescRight">Look up the format corresponding to a channel. <a href="#aa337ab76176f3c4193642ac6de3a61cf">More...</a><br/></td></tr>
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<tr class="memdesc:ac7dbe33793790fc37a5eda11ed6b0273"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return the format of a channel. <a href="#ac7dbe33793790fc37a5eda11ed6b0273">More...</a><br/></td></tr>
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<tr class="memitem:a1ebbb23b0094d47c51226d58e17e6447"><td class="memTemplParams" colspan="2">template&lt;typename F , typename T &gt; </td></tr>
<tr class="memitem:a1ebbb23b0094d47c51226d58e17e6447"><td class="memTemplItemLeft" align="right" valign="top">T&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1ebbb23b0094d47c51226d58e17e6447">foldl</a> (F &amp;&amp;, const T &amp;<a class="el" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>)</td></tr>
<tr class="memdesc:a1ebbb23b0094d47c51226d58e17e6447"><td class="mdescLeft">&#160;</td><td class="mdescRight">Base case of foldl. <a href="#a1ebbb23b0094d47c51226d58e17e6447">More...</a><br/></td></tr>
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<tr class="memitem:ad933f996ccb22854ae56dd86de8cbbfe"><td class="memTemplParams" colspan="2">template&lt;typename F , typename T , typename U &gt; </td></tr>
<tr class="memitem:ad933f996ccb22854ae56dd86de8cbbfe"><td class="memTemplItemLeft" align="right" valign="top">auto&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ad933f996ccb22854ae56dd86de8cbbfe">foldl</a> (F &amp;&amp;func, T &amp;&amp;value1, U &amp;&amp;value2) -&gt; decltype(func(value1, value2))</td></tr>
<tr class="memdesc:ad933f996ccb22854ae56dd86de8cbbfe"><td class="mdescLeft">&#160;</td><td class="mdescRight">Base case of foldl. <a href="#ad933f996ccb22854ae56dd86de8cbbfe">More...</a><br/></td></tr>
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<tr class="memitem:a89322cccde5e0a27d3a41085d3fd366c"><td class="memTemplParams" colspan="2">template&lt;typename F , typename I , typename T , typename... Vs&gt; </td></tr>
<tr class="memitem:a89322cccde5e0a27d3a41085d3fd366c"><td class="memTemplItemLeft" align="right" valign="top">I&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a89322cccde5e0a27d3a41085d3fd366c">foldl</a> (F &amp;&amp;func, I &amp;&amp;initial, T &amp;&amp;<a class="el" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>, Vs &amp;&amp;...values)</td></tr>
<tr class="memdesc:a89322cccde5e0a27d3a41085d3fd366c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fold left. <a href="#a89322cccde5e0a27d3a41085d3fd366c">More...</a><br/></td></tr>
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<tr class="memitem:a4c9ad143c34306817986409ffb1dbd40"><td class="memItemLeft" align="right" valign="top"><a class="el" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a4c9ad143c34306817986409ffb1dbd40">shape_to_valid_region</a> (<a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> shape, bool border_undefined=false, <a class="el" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a> border_size=<a class="el" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>(0))</td></tr>
<tr class="memdesc:a4c9ad143c34306817986409ffb1dbd40"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create a valid region based on tensor shape, border mode and border size. <a href="#a4c9ad143c34306817986409ffb1dbd40">More...</a><br/></td></tr>
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<tr class="memitem:a1e6934e95738573214c2ce1d6648d116"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a1e6934e95738573214c2ce1d6648d116">store_value_with_data_type</a> (void *ptr, T <a class="el" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type)</td></tr>
<tr class="memdesc:a1e6934e95738573214c2ce1d6648d116"><td class="mdescLeft">&#160;</td><td class="mdescRight">Write the value after casting the pointer according to <code>data_type</code>. <a href="#a1e6934e95738573214c2ce1d6648d116">More...</a><br/></td></tr>
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<tr class="memitem:a24d8c0391cfa38e78969b6ad97c0ff09"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">index2coord</a> (const <a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;shape, int index)</td></tr>
<tr class="memdesc:a24d8c0391cfa38e78969b6ad97c0ff09"><td class="mdescLeft">&#160;</td><td class="mdescRight">Convert a linear index into n-dimensional coordinates. <a href="#a24d8c0391cfa38e78969b6ad97c0ff09">More...</a><br/></td></tr>
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<tr class="memitem:a9be4cb7e6ee20063a4a10bc3abb750b9"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a> (const <a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;shape, const <a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;coord)</td></tr>
<tr class="memdesc:a9be4cb7e6ee20063a4a10bc3abb750b9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Linearise the given coordinate. <a href="#a9be4cb7e6ee20063a4a10bc3abb750b9">More...</a><br/></td></tr>
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<tr class="memitem:a856b55fc20ddcbdbeb84c35ae27bedac"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a856b55fc20ddcbdbeb84c35ae27bedac">is_in_valid_region</a> (const <a class="el" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> &amp;valid_region, <a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> coord)</td></tr>
<tr class="memdesc:a856b55fc20ddcbdbeb84c35ae27bedac"><td class="mdescLeft">&#160;</td><td class="mdescRight">Check if a coordinate is within a valid region. <a href="#a856b55fc20ddcbdbeb84c35ae27bedac">More...</a><br/></td></tr>
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<tr class="memitem:a2ce249581879425cc66db8d364c838f3"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
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<tr class="memdesc:a2ce249581879425cc66db8d364c838f3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and initialize a tensor of the given type. <a href="#a2ce249581879425cc66db8d364c838f3">More...</a><br/></td></tr>
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<tr class="memitem:ac7324cc960068b65c558b7d25dfe2914"><td class="memItemLeft" align="right" valign="top">std::vector&lt; <a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac7324cc960068b65c558b7d25dfe2914">generate_random_rois</a> (const <a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;shape, const <a class="el" href="classarm__compute_1_1_r_o_i_pooling_layer_info.xhtml">ROIPoolingLayerInfo</a> &amp;pool_info, unsigned int num_rois, std::random_device::result_type seed)</td></tr>
<tr class="memdesc:ac7324cc960068b65c558b7d25dfe2914"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create a vector of random ROIs. <a href="#ac7324cc960068b65c558b7d25dfe2914">More...</a><br/></td></tr>
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<tr class="memitem:ac35e7a1ad467f5fe8620cbbc5793d53b"><td class="memTemplParams" colspan="2">template&lt;typename T , typename ArrayAccessor_T &gt; </td></tr>
<tr class="memitem:ac35e7a1ad467f5fe8620cbbc5793d53b"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ac35e7a1ad467f5fe8620cbbc5793d53b">fill_array</a> (ArrayAccessor_T &amp;&amp;array, const std::vector&lt; T &gt; &amp;v)</td></tr>
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<tr class="memitem:ae47155d6186155ec4da9295764b3c05a"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#ae47155d6186155ec4da9295764b3c05a">get_typestring</a> (<a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type)</td></tr>
<tr class="memdesc:ae47155d6186155ec4da9295764b3c05a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Obtain numpy type string from DataType. <a href="#ae47155d6186155ec4da9295764b3c05a">More...</a><br/></td></tr>
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Variables</h2></td></tr>
<tr class="memitem:aab9a2ff74a27ae837d32a79a38952228"><td class="memItemLeft" align="right" valign="top">const auto&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#aab9a2ff74a27ae837d32a79a38952228">data_types</a> = <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;DataType&quot;, { DataType::F32 })</td></tr>
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<tr class="memitem:a71326f0909d77386e29b511e1990a11f"><td class="memItemLeft" align="right" valign="top">std::unique_ptr&lt; <a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml">AssetsLibrary</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a></td></tr>
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<h2 class="groupheader">Typedef Documentation</h2>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a74a10374253178ae54e1baab173698a1">CLActivationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_activation_layer_fixture.xhtml">ActivationLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml">CLActivationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_activation_layer_8cpp_source.xhtml#l00051">51</a> of file <a class="el" href="benchmark_2_c_l_2_activation_layer_8cpp_source.xhtml">ActivationLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#aa631c5ec3d7cb3dab649f994e9e9217d">CLAlexNetFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_alex_net_fixture.xhtml">AlexNetFixture</a>&lt;<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_sub_tensor.xhtml">CLSubTensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml">CLActivationLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml">CLDirectConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml">CLFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml">CLNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml">CLPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_softmax_layer.xhtml">CLSoftmaxLayer</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_s_y_s_t_e_m_2_alex_net_8cpp_source.xhtml#l00056">56</a> of file <a class="el" href="benchmark_2_c_l_2_s_y_s_t_e_m_2_alex_net_8cpp_source.xhtml">AlexNet.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#af80ea91532f0ebdccb3f1d8e507a98ad">CLBatchNormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_batch_normalization_layer_fixture.xhtml">BatchNormalizationLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer.xhtml">CLBatchNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00046">46</a> of file <a class="el" href="benchmark_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml">BatchNormalizationLayer.cpp</a>.</p>
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<td class="memname">typedef <a class="el" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">ConvolutionLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml">CLDirectConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a> &gt; <a class="el" href="namespacearm__compute_1_1test.xhtml#ad275d75e1b63f91fdc59afe026688b12">CLConvolutionLayerFixture</a></td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00051">51</a> of file <a class="el" href="benchmark_2_c_l_2_convolution_layer_8cpp_source.xhtml">ConvolutionLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a1e3870d2e47dfd84b259bdbff0a6f5f8">CLDepthwiseConvolutionFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_depthwise_convolution_fixture.xhtml">DepthwiseConvolutionFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution.xhtml">CLDepthwiseConvolution</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_depthwise_convolution_8cpp_source.xhtml#l00041">41</a> of file <a class="el" href="benchmark_2_c_l_2_depthwise_convolution_8cpp_source.xhtml">DepthwiseConvolution.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#adc07e82b4049d653c965af2606a7d70f">CLDepthwiseSeparableConvolutionLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_depthwise_separable_convolution_layer_fixture.xhtml">DepthwiseSeparableConvolutionLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_separable_convolution_layer.xhtml">CLDepthwiseSeparableConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_depthwise_separable_convolution_layer_8cpp_source.xhtml#l00041">41</a> of file <a class="el" href="benchmark_2_c_l_2_depthwise_separable_convolution_layer_8cpp_source.xhtml">DepthwiseSeparableConvolutionLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a4a14e383a632057e99845c74a72a6454">CLFloorFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_floor_fixture.xhtml">FloorFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_floor.xhtml">CLFloor</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_floor_8cpp_source.xhtml#l00045">45</a> of file <a class="el" href="benchmark_2_c_l_2_floor_8cpp_source.xhtml">Floor.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a4c33955ce3f6ed3a4d756cdebf6c8b3a">CLFullyConnectedLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_fully_connected_layer_fixture.xhtml">FullyConnectedLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml">CLFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_fully_connected_layer_8cpp_source.xhtml#l00049">49</a> of file <a class="el" href="benchmark_2_c_l_2_fully_connected_layer_8cpp_source.xhtml">FullyConnectedLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#abf07c2bf7d8e9c76e146f9b21bee88fd">CLGEMMFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_g_e_m_m_fixture.xhtml">GEMMFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml">CLGEMM</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_g_e_m_m_8cpp_source.xhtml#l00046">46</a> of file <a class="el" href="benchmark_2_c_l_2_g_e_m_m_8cpp_source.xhtml">GEMM.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#ae3b678c8477dd5acc5e264eae37b562c">CLLeNet5Fixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_le_net5_fixture.xhtml">LeNet5Fixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer.xhtml">CLActivationLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_fully_connected_layer.xhtml">CLFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml">CLPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_c_l_softmax_layer.xhtml">CLSoftmaxLayer</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_s_y_s_t_e_m_2_le_net5_8cpp_source.xhtml#l00049">49</a> of file <a class="el" href="benchmark_2_c_l_2_s_y_s_t_e_m_2_le_net5_8cpp_source.xhtml">LeNet5.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#af4f1c6ad288931f07f614316f57ed63b">CLNormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_normalization_layer_fixture.xhtml">NormalizationLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_normalization_layer.xhtml">CLNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_normalization_layer_8cpp_source.xhtml#l00046">46</a> of file <a class="el" href="benchmark_2_c_l_2_normalization_layer_8cpp_source.xhtml">NormalizationLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a9c81648f3199d0d1c3f34a29a7a2bb8d">CLPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_pooling_layer_fixture.xhtml">PoolingLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer.xhtml">CLPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_pooling_layer_8cpp_source.xhtml#l00051">51</a> of file <a class="el" href="benchmark_2_c_l_2_pooling_layer_8cpp_source.xhtml">PoolingLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a41884dec2ecae6674396802641b01060">CLROIPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_r_o_i_pooling_layer_fixture.xhtml">ROIPoolingLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a>, <a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer.xhtml">CLROIPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>, <a class="el" href="classarm__compute_1_1_c_l_array.xhtml">CLArray</a>&lt;<a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a>&gt;, <a class="el" href="classarm__compute_1_1test_1_1_c_l_array_accessor.xhtml">CLArrayAccessor</a>&lt;<a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a>&gt;&gt;</td>
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<p>Definition at line <a class="el" href="_c_l_2_r_o_i_pooling_layer_8cpp_source.xhtml#l00042">42</a> of file <a class="el" href="_c_l_2_r_o_i_pooling_layer_8cpp_source.xhtml">ROIPoolingLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#aeded391cb7ec7a44c41eb23544265894">NEActivationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_activation_layer_fixture.xhtml">ActivationLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_activation_layer_8cpp_source.xhtml#l00055">55</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_activation_layer_8cpp_source.xhtml">ActivationLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#ae0e8bcf3b0ed15e708b4a38febfdb84e">NEAlexNetFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_alex_net_fixture.xhtml">AlexNetFixture</a>&lt;<a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a>, <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_sub_tensor.xhtml">SubTensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>, <a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml">NEConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml">NEConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml">NEFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml">NENormalizationLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml">NEPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_softmax_layer.xhtml">NESoftmaxLayer</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_s_y_s_t_e_m_2_alex_net_8cpp_source.xhtml#l00065">65</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_s_y_s_t_e_m_2_alex_net_8cpp_source.xhtml">AlexNet.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#ac7369c169e6de526fcb6f68e4a959444">NEBatchNormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_batch_normalization_layer_fixture.xhtml">BatchNormalizationLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_batch_normalization_layer.xhtml">NEBatchNormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_batch_normalization_layer_8cpp_source.xhtml#l00051">51</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_batch_normalization_layer_8cpp_source.xhtml">BatchNormalizationLayer.cpp</a>.</p>
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<td class="memname">typedef <a class="el" href="classarm__compute_1_1test_1_1_convolution_layer_fixture.xhtml">ConvolutionLayerFixture</a>&lt; <a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_direct_convolution_layer.xhtml">NEDirectConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a> &gt; <a class="el" href="namespacearm__compute_1_1test.xhtml#a3168ad22b6ac1e9a6996b53e5038a7a2">NEConvolutionLayerFixture</a></td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_convolution_layer_8cpp_source.xhtml#l00055">55</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_convolution_layer_8cpp_source.xhtml">ConvolutionLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#ac8cf6873b0e9ac7334bcbc042fdc5f02">NEFloorFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_floor_fixture.xhtml">FloorFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_floor.xhtml">NEFloor</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_floor_8cpp_source.xhtml#l00045">45</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_floor_8cpp_source.xhtml">Floor.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a0b4f7a523ddb2b823750ff5bdc03470c">NEFullyConnectedLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_fully_connected_layer_fixture.xhtml">FullyConnectedLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml">NEFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_fully_connected_layer_8cpp_source.xhtml#l00053">53</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_fully_connected_layer_8cpp_source.xhtml">FullyConnectedLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a789c444c1307e85eec5f8b0d75fd5f7d">NEGEMMFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_g_e_m_m_fixture.xhtml">GEMMFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_g_e_m_m.xhtml">NEGEMM</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_g_e_m_m_8cpp_source.xhtml#l00054">54</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_g_e_m_m_8cpp_source.xhtml">GEMM.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a6a292ad5fedcc7dea6c6eb1be6d4c0d3">NELeNet5Fixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_le_net5_fixture.xhtml">LeNet5Fixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>, <a class="el" href="classarm__compute_1_1_n_e_activation_layer.xhtml">NEActivationLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml">NEConvolutionLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_fully_connected_layer.xhtml">NEFullyConnectedLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml">NEPoolingLayer</a>, <a class="el" href="classarm__compute_1_1_n_e_softmax_layer.xhtml">NESoftmaxLayer</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_s_y_s_t_e_m_2_le_net5_8cpp_source.xhtml#l00049">49</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_s_y_s_t_e_m_2_le_net5_8cpp_source.xhtml">LeNet5.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#acc2c4764a300b505b50e9ba0642eff2b">NENormalizationLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_normalization_layer_fixture.xhtml">NormalizationLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_normalization_layer.xhtml">NENormalizationLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_normalization_layer_8cpp_source.xhtml#l00049">49</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_normalization_layer_8cpp_source.xhtml">NormalizationLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#aafcc5ee5a13d9ed18d31591bb1d50fb0">NEPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_pooling_layer_fixture.xhtml">PoolingLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_pooling_layer.xhtml">NEPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>&gt;</td>
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<p>Definition at line <a class="el" href="benchmark_2_n_e_o_n_2_pooling_layer_8cpp_source.xhtml#l00055">55</a> of file <a class="el" href="benchmark_2_n_e_o_n_2_pooling_layer_8cpp_source.xhtml">PoolingLayer.cpp</a>.</p>
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<td class="memname">using <a class="el" href="namespacearm__compute_1_1test.xhtml#a7ad74154ac625702bef70b90243ae63f">NEROIPoolingLayerFixture</a> = <a class="el" href="classarm__compute_1_1test_1_1_r_o_i_pooling_layer_fixture.xhtml">ROIPoolingLayerFixture</a>&lt;<a class="el" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>, <a class="el" href="classarm__compute_1_1_n_e_r_o_i_pooling_layer.xhtml">NEROIPoolingLayer</a>, <a class="el" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>, <a class="el" href="classarm__compute_1_1_array.xhtml">Array</a>&lt;<a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a>&gt;, <a class="el" href="classarm__compute_1_1test_1_1_array_accessor.xhtml">ArrayAccessor</a>&lt;<a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a>&gt;&gt;</td>
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<p>Definition at line <a class="el" href="_n_e_o_n_2_r_o_i_pooling_layer_8cpp_source.xhtml#l00042">42</a> of file <a class="el" href="_n_e_o_n_2_r_o_i_pooling_layer_8cpp_source.xhtml">ROIPoolingLayer.cpp</a>.</p>
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<h2 class="groupheader">Function Documentation</h2>
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<td class="memname">void arm_compute::test::apply </td>
<td>(</td>
<td class="paramtype">O *&#160;</td>
<td class="paramname"><em>obj</em>, </td>
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<td class="paramtype">F &amp;&amp;&#160;</td>
<td class="paramname"><em>func</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const std::tuple&lt; As...&gt; &amp;&#160;</td>
<td class="paramname"><em>args</em>&#160;</td>
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<p>Definition at line <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00079">79</a> of file <a class="el" href="tests_2framework_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00072">arm_compute::test::framework::apply_impl()</a>.</p>
<div class="fragment"><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;{</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a8daf3ad5a8666ce417ad176256a592eb">detail::apply_impl</a>(obj, std::forward&lt;F&gt;(func), <a class="code" href="namespacecaffe__data__extractor.xhtml#aad3cdfd6574de97bf37448087aaff11d">args</a>, detail::sequence_t&lt;<span class="keyword">sizeof</span>...(As)&gt;());</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_a8daf3ad5a8666ce417ad176256a592eb"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#a8daf3ad5a8666ce417ad176256a592eb">arm_compute::test::framework::apply_impl</a></div><div class="ttdeci">void apply_impl(O *obj, F &amp;&amp;func, const std::tuple&lt; As...&gt; &amp;args, detail::sequence&lt; S...&gt;)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2framework_2_utils_8h_source.xhtml#l00072">Utils.h:72</a></div></div>
<div class="ttc" id="namespacecaffe__data__extractor_xhtml_aad3cdfd6574de97bf37448087aaff11d"><div class="ttname"><a href="namespacecaffe__data__extractor.xhtml#aad3cdfd6574de97bf37448087aaff11d">caffe_data_extractor.args</a></div><div class="ttdeci">tuple args</div><div class="ttdef"><b>Definition:</b> <a href="caffe__data__extractor_8py_source.xhtml#l00021">caffe_data_extractor.py:21</a></div></div>
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<td class="memname">int arm_compute::test::coord2index </td>
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<td class="paramtype">const TensorShape &amp;&#160;</td>
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<p>Linearise the given coordinate. </p>
<p>Transforms the given coordinate into a linear offset in terms of elements.</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">shape</td><td>Shape of the n-dimensional tensor. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">coord</td><td>The to be converted coordinate.</td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Linear offset to the element. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00337">337</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00115">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00109">Dimensions&lt; T &gt;::num_dimensions()</a>, and <a class="el" href="_tensor_shape_8h_source.xhtml#l00135">TensorShape::total_size()</a>.</p>
<p>Referenced by <a class="el" href="tests_2validation_2_c_p_p_2_utils_8h_source.xhtml#l00081">arm_compute::test::validation::apply_2d_spatial_filter()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00057">RawTensor::operator()()</a>, <a class="el" href="_simple_tensor_8h_source.xhtml#l00323">SimpleTensor&lt; T &gt;::operator()()</a>, <a class="el" href="_c_p_p_2_scale_8cpp_source.xhtml#l00039">arm_compute::test::validation::reference::scale()</a>, <a class="el" href="tests_2validation_2_c_p_p_2_utils_8h_source.xhtml#l00046">arm_compute::test::validation::tensor_elem_at()</a>, <a class="el" href="_c_p_p_2_warp_affine_8cpp_source.xhtml#l00050">arm_compute::test::validation::reference::warp_affine()</a>, and <a class="el" href="_c_p_p_2_warp_perspective_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::warp_perspective()</a>.</p>
<div class="fragment"><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160;{</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.total_size() == 0, <span class="stringliteral">&quot;Cannot get index from empty shape&quot;</span>);</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(coord.num_dimensions() == 0, <span class="stringliteral">&quot;Cannot get index of empty coordinate&quot;</span>);</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160;</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <span class="keywordtype">int</span> index = 0;</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; <span class="keywordtype">int</span> dim_size = 1;</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160;</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; coord.num_dimensions(); ++i)</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; {</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; index += coord[i] * dim_size;</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; dim_size *= <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>[i];</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160; }</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160;</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; <span class="keywordflow">return</span> index;</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00089">MinMaxLocation.cpp:89</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00115">Error.h:115</a></div></div>
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<td class="memname">T arm_compute::test::create_tensor </td>
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<td class="paramtype">const TensorShape &amp;&#160;</td>
<td class="paramname"><em>shape</em>, </td>
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<p>Create and initialize a tensor of the given type. </p>
<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramdir">[in]</td><td class="paramname">shape</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> shape. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">data_type</td><td>Data type. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_channels</td><td>(Optional) Number of channels. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">fixed_point_position</td><td>(Optional) Number of fractional bits.</td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Initialized tensor of given type. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00378">378</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160;{</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; T tensor;</div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160; tensor.allocator()-&gt;init(TensorInfo(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, num_channels, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>, fixed_point_position));</div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160;</div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160; <span class="keywordflow">return</span> tensor;</div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160;}</div>
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<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ac2ad7f431e3446fddcd9b6b9f93c4c14"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00090">MinMaxLocation.cpp:90</a></div></div>
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<td class="memname">void arm_compute::test::fill_array </td>
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<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00433">433</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>Referenced by <a class="el" href="_r_o_i_pooling_layer_fixture_8h_source.xhtml#l00045">ROIPoolingLayerFixture&lt; TensorType, Function, Accessor, Array_T, ArrayAccessor &gt;::setup()</a>.</p>
<div class="fragment"><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>&#160;{</div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>&#160; array.resize(v.size());</div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>&#160; std::memcpy(array.buffer(), v.data(), v.size() * <span class="keyword">sizeof</span>(T));</div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>&#160;}</div>
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<td class="memname">void arm_compute::test::fill_tensors </td>
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<p>Definition at line <a class="el" href="_helper_8h_source.xhtml#l00039">39</a> of file <a class="el" href="_helper_8h_source.xhtml">Helper.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00124">ARM_COMPUTE_ERROR_ON</a>, and <a class="el" href="main_8cpp_source.xhtml#l00055">library</a>.</p>
<div class="fragment"><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;{</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="keyword">const</span> std::array &lt; T, 1 + <span class="keyword">sizeof</span>...(Ts) &gt; tensors{ { std::forward&lt;T&gt;(tensor), std::forward&lt;Ts&gt;(other_tensors)... } };</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; std::vector&lt;int&gt; vs(seeds);</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(vs.size() != tensors.size());</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keywordtype">int</span> k = 0;</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keywordflow">for</span>(<span class="keyword">auto</span> tp : tensors)</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; {</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <a class="code" href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">library</a>-&gt;fill(Accessor(*tp), std::forward&lt;D&gt;(dist), vs[k++]);</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; }</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;}</div>
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<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a71326f0909d77386e29b511e1990a11f"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a71326f0909d77386e29b511e1990a11f">arm_compute::test::library</a></div><div class="ttdeci">std::unique_ptr&lt; AssetsLibrary &gt; library</div><div class="ttdef"><b>Definition:</b> <a href="main_8cpp_source.xhtml#l00055">main.cpp:55</a></div></div>
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<td class="memname">T arm_compute::test::foldl </td>
<td>(</td>
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<p>Base case of foldl. </p>
<dl class="section return"><dt>Returns</dt><dd>value. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00156">156</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="hwc_8hpp_source.xhtml#l00269">value</a>.</p>
<p>Referenced by <a class="el" href="tests_2_utils_8h_source.xhtml#l00179">foldl()</a>.</p>
<div class="fragment"><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160;{</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="keywordflow">return</span> <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;}</div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
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<td class="memname">auto arm_compute::test::foldl </td>
<td>(</td>
<td class="paramtype">F &amp;&amp;&#160;</td>
<td class="paramname"><em>func</em>, </td>
</tr>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">T &amp;&amp;&#160;</td>
<td class="paramname"><em>value1</em>, </td>
</tr>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">U &amp;&amp;&#160;</td>
<td class="paramname"><em>value2</em>&#160;</td>
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<td></td>
<td>)</td>
<td></td><td> -&gt; decltype(func(value1, value2))
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<p>Base case of foldl. </p>
<dl class="section return"><dt>Returns</dt><dd>func(value1, value2). </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00166">166</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;{</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <span class="keywordflow">return</span> func(value1, value2);</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;}</div>
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<td class="memname">I arm_compute::test::foldl </td>
<td>(</td>
<td class="paramtype">F &amp;&amp;&#160;</td>
<td class="paramname"><em>func</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">I &amp;&amp;&#160;</td>
<td class="paramname"><em>initial</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">T &amp;&amp;&#160;</td>
<td class="paramname"><em>value</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">Vs &amp;&amp;...&#160;</td>
<td class="paramname"><em>values</em>&#160;</td>
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<td>)</td>
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<p>Fold left. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">func</td><td>Binary function to be called. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">initial</td><td>Initial value. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">value</td><td>Argument passed to the function. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">values</td><td>Remaining arguments. </td></tr>
</table>
</dd>
</dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00179">179</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="tests_2_utils_8h_source.xhtml#l00156">foldl()</a>.</p>
<div class="fragment"><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160;{</div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a89322cccde5e0a27d3a41085d3fd366c">foldl</a>(std::forward&lt;F&gt;(func), func(std::forward&lt;I&gt;(initial), std::forward&lt;T&gt;(<a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>)), std::forward&lt;Vs&gt;(values)...);</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a89322cccde5e0a27d3a41085d3fd366c"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a89322cccde5e0a27d3a41085d3fd366c">arm_compute::test::foldl</a></div><div class="ttdeci">I foldl(F &amp;&amp;func, I &amp;&amp;initial, T &amp;&amp;value, Vs &amp;&amp;...values)</div><div class="ttdoc">Fold left. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00179">Utils.h:179</a></div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
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<td class="memname">std::vector&lt;<a class="el" href="structarm__compute_1_1_r_o_i.xhtml">ROI</a>&gt; arm_compute::test::generate_random_rois </td>
<td>(</td>
<td class="paramtype">const TensorShape &amp;&#160;</td>
<td class="paramname"><em>shape</em>, </td>
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<td class="paramtype">const ROIPoolingLayerInfo &amp;&#160;</td>
<td class="paramname"><em>pool_info</em>, </td>
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<td class="paramtype">unsigned int&#160;</td>
<td class="paramname"><em>num_rois</em>, </td>
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<td class="paramtype">std::random_device::result_type&#160;</td>
<td class="paramname"><em>seed</em>&#160;</td>
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<p>Create a vector of random ROIs. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">shape</td><td>The shape of the input tensor. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">pool_info</td><td>The <a class="el" href="structarm__compute_1_1_r_o_i.xhtml" title="Region of interest. ">ROI</a> pooling information. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_rois</td><td>The number of ROIs to be created. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">seed</td><td>The random seed to be used.</td></tr>
</table>
</dd>
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<dl class="section return"><dt>Returns</dt><dd>A vector that contains the requested number of random ROIs </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00395">395</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00124">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00312">ROI::batch_idx</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00290">Rectangle::height</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00889">arm_compute::test::fixed_point_arithmetic::detail::max()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00495">ROIPoolingLayerInfo::pooled_height()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00491">ROIPoolingLayerInfo::pooled_width()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00311">ROI::rect</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00499">ROIPoolingLayerInfo::spatial_scale()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00289">Rectangle::width</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00081">Dimensions&lt; T &gt;::x()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00287">Rectangle::x</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00086">Dimensions&lt; T &gt;::y()</a>, and <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00288">Rectangle::y</a>.</p>
<p>Referenced by <a class="el" href="_r_o_i_pooling_layer_fixture_8h_source.xhtml#l00045">ROIPoolingLayerFixture&lt; TensorType, Function, Accessor, Array_T, ArrayAccessor &gt;::setup()</a>.</p>
<div class="fragment"><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>&#160;{</div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((pool_info.pooled_width() &lt; 4) || (pool_info.pooled_height() &lt; 4));</div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>&#160;</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; std::vector&lt;ROI&gt; rois;</div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160; std::mt19937 gen(seed);</div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pool_width = pool_info.pooled_width();</div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> pool_height = pool_info.pooled_height();</div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> roi_scale = pool_info.spatial_scale();</div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>&#160;</div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>&#160; <span class="comment">// Calculate distribution bounds</span></div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>&#160; <span class="keyword">const</span> <span class="keyword">auto</span> scaled_width = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.x() / roi_scale) / pool_width);</div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>&#160; <span class="keyword">const</span> <span class="keyword">auto</span> scaled_height = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.y() / roi_scale) / pool_height);</div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>&#160; <span class="keyword">const</span> <span class="keyword">auto</span> min_width = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(pool_width / roi_scale);</div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>&#160; <span class="keyword">const</span> <span class="keyword">auto</span> min_height = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(pool_height / roi_scale);</div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>&#160;</div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>&#160; <span class="comment">// Create distributions</span></div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>&#160; std::uniform_int_distribution&lt;int&gt; dist_batch(0, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>[3] - 1);</div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>&#160; std::uniform_int_distribution&lt;int&gt; dist_x(0, scaled_width);</div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>&#160; std::uniform_int_distribution&lt;int&gt; dist_y(0, scaled_height);</div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>&#160; std::uniform_int_distribution&lt;int&gt; dist_w(min_width, <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(min_width, (pool_width - 2) * scaled_width));</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160; std::uniform_int_distribution&lt;int&gt; dist_h(min_height, <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(min_height, (pool_height - 2) * scaled_height));</div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160;</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> r = 0; r &lt; num_rois; ++r)</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>&#160; {</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>&#160; ROI roi;</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>&#160; roi.batch_idx = dist_batch(gen);</div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>&#160; roi.rect.x = dist_x(gen);</div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>&#160; roi.rect.y = dist_y(gen);</div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>&#160; roi.rect.width = dist_w(gen);</div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>&#160; roi.rect.height = dist_h(gen);</div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>&#160; rois.push_back(roi);</div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>&#160; }</div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>&#160;</div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>&#160; <span class="keywordflow">return</span> rois;</div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00089">MinMaxLocation.cpp:89</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00124">Error.h:124</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ad91bb73431b4de1f4946ed949d444849"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">arm_compute::test::fixed_point_arithmetic::detail::max</a></div><div class="ttdeci">fixed_point&lt; T &gt; max(fixed_point&lt; T &gt; x, fixed_point&lt; T &gt; y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00889">FixedPoint.h:889</a></div></div>
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<td class="memname"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> arm_compute::test::get_channel_format </td>
<td>(</td>
<td class="paramtype">Channel&#160;</td>
<td class="paramname"><em>channel</em></td><td>)</td>
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<p>Return the format of a channel. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel type.</td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Format of the given channel. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00138">138</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa9d5ed678fe57bcca610140957afab571">arm_compute::B</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aadfcf28d0734569a6a693bc8194de62bf">arm_compute::G</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aae1e1d3d40573127e9ee0480caf1283d6">arm_compute::R</a>, and <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>.</p>
<div class="fragment"><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160;{</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="keywordflow">switch</span>(channel)</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; {</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; <span class="keywordflow">case</span> Channel::R:</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keywordflow">case</span> Channel::G:</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordflow">case</span> Channel::B:</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keywordflow">return</span> Format::U8;</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Unsupported channel&quot;</span>);</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; }</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;}</div>
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<td class="memname"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> arm_compute::test::get_format_for_channel </td>
<td>(</td>
<td class="paramtype">Channel&#160;</td>
<td class="paramname"><em>channel</em></td><td>)</td>
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<p>Look up the format corresponding to a channel. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel type.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>Format that contains the given channel. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00119">119</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa9d5ed678fe57bcca610140957afab571">arm_compute::B</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aadfcf28d0734569a6a693bc8194de62bf">arm_compute::G</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aae1e1d3d40573127e9ee0480caf1283d6">arm_compute::R</a>, and <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::RGB888</a>.</p>
<p>Referenced by <a class="el" href="_assets_library_8cpp_source.xhtml#l00210">AssetsLibrary::fill()</a>, and <a class="el" href="_assets_library_8cpp_source.xhtml#l00427">AssetsLibrary::get()</a>.</p>
<div class="fragment"><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;{</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keywordflow">switch</span>(channel)</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; {</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="keywordflow">case</span> Channel::R:</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="keywordflow">case</span> Channel::G:</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keywordflow">case</span> Channel::B:</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keywordflow">return</span> Format::RGB888;</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">&quot;Unsupported channel&quot;</span>);</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; }</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160;}</div>
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<td class="memname">std::string arm_compute::test::get_typestring </td>
<td>(</td>
<td class="paramtype">DataType&#160;</td>
<td class="paramname"><em>data_type</em></td><td>)</td>
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<p>Obtain numpy type string from DataType. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">data_type</td><td>Data type.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>numpy type string. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00445">445</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::F64</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::S64</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::S8</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">arm_compute::SIZET</a>, <a class="el" href="_toolchain_support_8h_source.xhtml#l00168">arm_compute::support::cpp11::to_string()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::U16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::U32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::U64</a>, and <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>.</p>
<p>Referenced by <a class="el" href="_assets_library_8h_source.xhtml#l00656">AssetsLibrary::fill_layer_data()</a>.</p>
<div class="fragment"><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>&#160;{</div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>&#160; <span class="comment">// Check endianness</span></div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 1;</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>&#160; <span class="keyword">const</span> <span class="keywordtype">char</span> *c = <span class="keyword">reinterpret_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">char</span> *<span class="keyword">&gt;</span>(&amp;i);</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>&#160; std::string endianness;</div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>&#160; <span class="keywordflow">if</span>(*c == 1)</div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>&#160; {</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>&#160; endianness = std::string(<span class="stringliteral">&quot;&lt;&quot;</span>);</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>&#160; }</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>&#160; {</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>&#160; endianness = std::string(<span class="stringliteral">&quot;&gt;&quot;</span>);</div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>&#160; }</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>&#160; <span class="keyword">const</span> std::string no_endianness(<span class="stringliteral">&quot;|&quot;</span>);</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>&#160;</div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>&#160; <span class="keywordflow">switch</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>)</div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>&#160; {</div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>&#160; <span class="keywordflow">case</span> DataType::U8:</div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>&#160; <span class="keywordflow">return</span> no_endianness + <span class="stringliteral">&quot;u&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(uint8_t));</div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>&#160; <span class="keywordflow">case</span> DataType::S8:</div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>&#160; <span class="keywordflow">return</span> no_endianness + <span class="stringliteral">&quot;i&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(int8_t));</div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>&#160; <span class="keywordflow">case</span> DataType::U16:</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;u&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(uint16_t));</div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>&#160; <span class="keywordflow">case</span> DataType::S16:</div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;i&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(int16_t));</div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>&#160; <span class="keywordflow">case</span> DataType::U32:</div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;u&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(uint32_t));</div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>&#160; <span class="keywordflow">case</span> DataType::S32:</div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;i&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(int32_t));</div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>&#160; <span class="keywordflow">case</span> DataType::U64:</div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;u&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(uint64_t));</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>&#160; <span class="keywordflow">case</span> DataType::S64:</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;i&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(int64_t));</div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>&#160; <span class="keywordflow">case</span> DataType::F32:</div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;f&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(<span class="keywordtype">float</span>));</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>&#160; <span class="keywordflow">case</span> DataType::F64:</div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;f&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(<span class="keywordtype">double</span>));</div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>&#160; <span class="keywordflow">case</span> DataType::SIZET:</div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>&#160; <span class="keywordflow">return</span> endianness + <span class="stringliteral">&quot;u&quot;</span> + <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>(<span class="keyword">sizeof</span>(<span class="keywordtype">size_t</span>));</div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>&#160; <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;NOT SUPPORTED!&quot;</span>);</div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>&#160; }</div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>&#160;}</div>
<div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_ace86dc6f3dfa4f3c256b3999ab250c0a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">arm_compute::test::framework::to_string</a></div><div class="ttdeci">std::string to_string(DatasetMode mode)</div><div class="ttdef"><b>Definition:</b> <a href="_dataset_modes_8h_source.xhtml#l00097">DatasetModes.h:97</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ac2ad7f431e3446fddcd9b6b9f93c4c14"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00090">MinMaxLocation.cpp:90</a></div></div>
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<td class="memname"><a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> arm_compute::test::index2coord </td>
<td>(</td>
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<p>Convert a linear index into n-dimensional coordinates. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">shape</td><td>Shape of the n-dimensional tensor. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">index</td><td>Linear index specifying the i-th element.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>n-dimensional coordinates. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00308">308</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00115">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00109">Dimensions&lt; T &gt;::num_dimensions()</a>, <a class="el" href="_tensor_shape_8h_source.xhtml#l00074">TensorShape::set()</a>, and <a class="el" href="_tensor_shape_8h_source.xhtml#l00135">TensorShape::total_size()</a>.</p>
<p>Referenced by <a class="el" href="_c_p_p_2_box3x3_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::box3x3()</a>, <a class="el" href="_assets_library_8h_source.xhtml#l00438">AssetsLibrary::fill()</a>, <a class="el" href="_c_p_p_2_gaussian3x3_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::gaussian3x3()</a>, <a class="el" href="_c_p_p_2_gaussian5x5_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::gaussian5x5()</a>, <a class="el" href="_c_p_p_2_non_linear_filter_8cpp_source.xhtml#l00036">arm_compute::test::validation::reference::non_linear_filter()</a>, <a class="el" href="_non_maxima_suppression_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::non_maxima_suppression()</a>, <a class="el" href="_c_p_p_2_scale_8cpp_source.xhtml#l00039">arm_compute::test::validation::reference::scale()</a>, <a class="el" href="_c_p_p_2_sobel_8cpp_source.xhtml#l00106">arm_compute::test::validation::reference::sobel()</a>, <a class="el" href="tests_2validation_2_c_p_p_2_utils_8cpp_source.xhtml#l00069">arm_compute::test::validation::transpose()</a>, <a class="el" href="_validation_8cpp_source.xhtml#l00173">arm_compute::test::validation::validate()</a>, <a class="el" href="_c_p_p_2_warp_affine_8cpp_source.xhtml#l00050">arm_compute::test::validation::reference::warp_affine()</a>, and <a class="el" href="_c_p_p_2_warp_perspective_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::warp_perspective()</a>.</p>
<div class="fragment"><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160;{</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; <span class="keywordtype">int</span> num_elements = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.total_size();</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160;</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(index &lt; 0 || index &gt;= num_elements, <span class="stringliteral">&quot;Index has to be in [0, num_elements]&quot;</span>);</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(num_elements == 0, <span class="stringliteral">&quot;Cannot create coordinate from empty shape&quot;</span>);</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160;</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; Coordinates coord{ 0 };</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160;</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> d = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.num_dimensions() - 1; d &gt;= 0; --d)</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; {</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; num_elements /= <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>[d];</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; coord.set(d, index / num_elements);</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; index %= num_elements;</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; }</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160;</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; <span class="keywordflow">return</span> coord;</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00089">MinMaxLocation.cpp:89</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00115">Error.h:115</a></div></div>
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<td class="memname">bool arm_compute::test::is_in_valid_region </td>
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<td class="paramtype">const ValidRegion &amp;&#160;</td>
<td class="paramname"><em>valid_region</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">Coordinates&#160;</td>
<td class="paramname"><em>coord</em>&#160;</td>
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<p>Check if a coordinate is within a valid region. </p>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00355">355</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00118">ValidRegion::end()</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00045">Dimensions&lt; int &gt;::num_max_dimensions</a>, and <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00112">ValidRegion::start()</a>.</p>
<p>Referenced by <a class="el" href="_c_p_p_2_non_linear_filter_8cpp_source.xhtml#l00036">arm_compute::test::validation::reference::non_linear_filter()</a>, <a class="el" href="_non_maxima_suppression_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::non_maxima_suppression()</a>, <a class="el" href="_c_p_p_2_sobel_8cpp_source.xhtml#l00106">arm_compute::test::validation::reference::sobel()</a>, and <a class="el" href="_validation_8h_source.xhtml#l00319">arm_compute::test::validation::validate()</a>.</p>
<div class="fragment"><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>&#160;{</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> d = 0; d &lt; Coordinates::num_max_dimensions; ++d)</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; {</div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160; <span class="keywordflow">if</span>(coord[d] &lt; valid_region.start(d) || coord[d] &gt;= valid_region.end(d))</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; {</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160; }</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160; }</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160;</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160; <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160;}</div>
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<td class="memname">std::string arm_compute::test::join </td>
<td>(</td>
<td class="paramtype">T&#160;</td>
<td class="paramname"><em>first</em>, </td>
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<td class="paramname"><em>last</em>, </td>
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<p>Helper function to concatenate multiple strings. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">first</td><td><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> pointing to the first element to be concatenated. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">last</td><td><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> pointing behind the last element to be concatenated. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">separator</td><td>String used to join the elements.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>String containing all elements joined by <code>separator</code>. </dd></dl>
<p>Definition at line <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00093">93</a> of file <a class="el" href="tests_2framework_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="accumulate_8cl_source.xhtml#l00041">accumulate()</a>.</p>
<p>Referenced by <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00136">join()</a>, and <a class="el" href="_j_s_o_n_printer_8cpp_source.xhtml#l00157">JSONPrinter::print_measurements()</a>.</p>
<div class="fragment"><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;{</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keywordflow">return</span> <a class="code" href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">std::accumulate</a>(std::next(first), last, *first, [&amp;separator](<span class="keyword">const</span> std::string &amp; base, <span class="keyword">const</span> std::string &amp; suffix)</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; {</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keywordflow">return</span> base + separator + suffix;</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; });</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;}</div>
<div class="ttc" id="accumulate_8cl_xhtml_a00e540076dd545ad59ac7482f8cdf514"><div class="ttname"><a href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">accumulate</a></div><div class="ttdeci">__kernel void accumulate(__global uchar *input_ptr, uint input_stride_x, uint input_step_x, uint input_stride_y, uint input_step_y, uint input_offset_first_element_in_bytes, __global uchar *accu_ptr, uint accu_stride_x, uint accu_step_x, uint accu_stride_y, uint accu_step_y, uint accu_offset_first_element_in_bytes)</div><div class="ttdoc">This function accumulates an input image into output image. </div><div class="ttdef"><b>Definition:</b> <a href="accumulate_8cl_source.xhtml#l00041">accumulate.cl:41</a></div></div>
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<td class="memname">std::string arm_compute::test::join </td>
<td>(</td>
<td class="paramtype">T &amp;&amp;&#160;</td>
<td class="paramname"><em>first</em>, </td>
</tr>
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<td class="paramkey"></td>
<td></td>
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<td class="paramname"><em>separator</em>, </td>
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<p>Helper function to concatenate multiple values. </p>
<p>All values are converted to std::string using the provided operation before being joined.</p>
<p>The signature of op has to be equivalent to std::string op(const T::value_type &amp;val).</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">first</td><td><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> pointing to the first element to be concatenated. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">last</td><td><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> pointing behind the last element to be concatenated. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">separator</td><td>String used to join the elements. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">op</td><td>Conversion function.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>String containing all elements joined by <code>separator</code>. </dd></dl>
<p>Definition at line <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00117">117</a> of file <a class="el" href="tests_2framework_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="accumulate_8cl_source.xhtml#l00041">accumulate()</a>.</p>
<div class="fragment"><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;{</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keywordflow">return</span> <a class="code" href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">std::accumulate</a>(std::next(first), last, op(*first), [&amp;separator, &amp;op](<span class="keyword">const</span> std::string &amp; base, <span class="keyword">const</span> <span class="keyword">typename</span> T::value_type &amp; suffix)</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; {</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keywordflow">return</span> base + separator + op(suffix);</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; });</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;}</div>
<div class="ttc" id="accumulate_8cl_xhtml_a00e540076dd545ad59ac7482f8cdf514"><div class="ttname"><a href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">accumulate</a></div><div class="ttdeci">__kernel void accumulate(__global uchar *input_ptr, uint input_stride_x, uint input_step_x, uint input_stride_y, uint input_step_y, uint input_offset_first_element_in_bytes, __global uchar *accu_ptr, uint accu_stride_x, uint accu_step_x, uint accu_stride_y, uint accu_step_y, uint accu_offset_first_element_in_bytes)</div><div class="ttdoc">This function accumulates an input image into output image. </div><div class="ttdef"><b>Definition:</b> <a href="accumulate_8cl_source.xhtml#l00041">accumulate.cl:41</a></div></div>
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<td>(</td>
<td class="paramtype">T &amp;&amp;&#160;</td>
<td class="paramname"><em>first</em>, </td>
</tr>
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<td class="paramkey"></td>
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<td class="paramname"><em>last</em>, </td>
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<td class="paramkey"></td>
<td></td>
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<td></td>
<td>)</td>
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<p>Helper function to concatenate multiple values. </p>
<p>All values are converted to std::string using std::to_string before being joined.</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">first</td><td><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> pointing to the first element to be concatenated. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">last</td><td><a class="el" href="classarm__compute_1_1_iterator.xhtml" title="Iterator updated by execute_window_loop for each window element. ">Iterator</a> pointing behind the last element to be concatenated. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">separator</td><td>String used to join the elements.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>String containing all elements joined by <code>separator</code>. </dd></dl>
<p>Definition at line <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00136">136</a> of file <a class="el" href="tests_2framework_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00093">join()</a>, and <a class="el" href="_toolchain_support_8h_source.xhtml#l00168">arm_compute::support::cpp11::to_string()</a>.</p>
<div class="fragment"><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;{</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a69835710fc772315f4e65ce156034530">join</a>(std::forward&lt;T&gt;(first), std::forward&lt;T&gt;(last), separator, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">support::cpp11::to_string</a>);</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_ace86dc6f3dfa4f3c256b3999ab250c0a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#ace86dc6f3dfa4f3c256b3999ab250c0a">arm_compute::test::framework::to_string</a></div><div class="ttdeci">std::string to_string(DatasetMode mode)</div><div class="ttdef"><b>Definition:</b> <a href="_dataset_modes_8h_source.xhtml#l00097">DatasetModes.h:97</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a69835710fc772315f4e65ce156034530"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a69835710fc772315f4e65ce156034530">arm_compute::test::join</a></div><div class="ttdeci">std::string join(T &amp;&amp;first, T &amp;&amp;last, const std::string &amp;separator)</div><div class="ttdoc">Helper function to concatenate multiple values. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2framework_2_utils_8h_source.xhtml#l00136">Utils.h:136</a></div></div>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">CLBatchNormalizationLayerFixture&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">NEFullyConnectedLayerFixture&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NENormalizationLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::GoogLeNetInceptionV1NormalizationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLFullyConnectedLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::LeNet5FullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEActivationLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::AlexNetActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEBatchNormalizationLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
<td class="paramname">, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">NEGEMMFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>datasets::MatrixMultiplyGEMMDataset(), data_types&#160;</td>
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<td class="paramtype">NEPoolingLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLPoolingLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEGEMMFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLNormalizationLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLBatchNormalizationLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::YOLOV2BatchNormalizationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="memname">arm_compute::test::REGISTER_FIXTURE_DATA_TEST_CASE </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">CLAlexNetFixture&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">NEFullyConnectedLayerFixture&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
<td class="paramname">, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::LeNet5FullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
<td class="paramname">, </td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::LeNet5PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLFullyConnectedLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::VGG16FullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEActivationLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">CLFullyConnectedLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEBatchNormalizationLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">NEPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">NENormalizationLayerFixture&#160;</td>
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<td class="paramtype">NEFullyConnectedLayerFixture&#160;</td>
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<td class="paramtype">CLFullyConnectedLayerFixture&#160;</td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">NEActivationLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::VGG16ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="memname">arm_compute::test::REGISTER_FIXTURE_DATA_TEST_CASE </td>
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<td class="paramkey"></td>
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<td class="paramtype">CLFullyConnectedLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::AlexNetFullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::VGG16PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::AlexNetPoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEActivationLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::YOLOV2ActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;, 1)&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEFullyConnectedLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::AlexNetFullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::LeNet5PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLFullyConnectedLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::LeNet5FullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::ALL&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">NEPoolingLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::VGG16PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLPoolingLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::LeNet5PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramtype">NEFullyConnectedLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::GoogLeNetInceptionV1FullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLFullyConnectedLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
<td class="paramname">, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::GoogLeNetInceptionV4FullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::YOLOV2PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">NEActivationLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
<td class="paramname">, </td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{1, 4})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEFullyConnectedLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
<td class="paramname">, </td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::GoogLeNetInceptionV4FullyConnectedLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEActivationLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::SqueezeNetActivationLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">NEConvolutionLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLPoolingLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::DatasetMode::NIGHTLY&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">CLConvolutionLayerFixture&#160;</td>
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<td class="paramkey"></td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramtype">framework::dataset::&#160;</td>
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<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{1, 4, 8})&#160;</td>
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<td class="paramtype">CLPoolingLayerFixture&#160;</td>
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<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::VGG16PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="memname">arm_compute::test::REGISTER_FIXTURE_DATA_TEST_CASE </td>
<td>(</td>
<td class="paramtype">YOLOV2PoolingLayer&#160;</td>
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<td class="paramname"><em>combine</em>framework::dataset::combine(datasets::YOLOV2PoolingLayerDataset(), data_types), framework::dataset::make(&quot;Batches&quot;,{4, 8})&#160;</td>
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<td class="memname">T arm_compute::test::round_half_even </td>
<td>(</td>
<td class="paramtype">T&#160;</td>
<td class="paramname"><em>value</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">T&#160;</td>
<td class="paramname"><em>epsilon</em> = <code>std::numeric_limits&lt;T&gt;::epsilon()</code>&#160;</td>
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<p>Round floating-point value with half value rounding to nearest even. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">value</td><td>floating-point value to be rounded. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">epsilon</td><td>precision.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>Floating-point value of rounded <code>value</code>. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00069">69</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00914">arm_compute::test::fixed_point_arithmetic::detail::abs()</a>, <a class="el" href="_toolchain_support_8h_source.xhtml#l00259">arm_compute::support::cpp11::copysign()</a>, and <a class="el" href="_toolchain_support_8h_source.xhtml#l00228">arm_compute::support::cpp11::round()</a>.</p>
<div class="fragment"><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;{</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; T positive_value = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ae115fc750a92fb6a5e094998b56fcc56">std::abs</a>(<a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>);</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; T ipart = 0;</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; std::modf(positive_value, &amp;ipart);</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="comment">// If &#39;value&#39; is exactly halfway between two integers</span></div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ae115fc750a92fb6a5e094998b56fcc56">std::abs</a>(positive_value - (ipart + 0.5f)) &lt; epsilon)</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; {</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="comment">// If &#39;ipart&#39; is even then return &#39;ipart&#39;</span></div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">if</span>(std::fmod(ipart, 2.f) &lt; epsilon)</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; {</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#a28096f8372c0ad762864c790917375e2">support::cpp11::copysign</a>(ipart, <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>);</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; }</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="comment">// Else return the nearest even integer</span></div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#a28096f8372c0ad762864c790917375e2">support::cpp11::copysign</a>(std::ceil(ipart + 0.5f), <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>);</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; }</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="comment">// Otherwise use the usual round to closest</span></div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#a28096f8372c0ad762864c790917375e2">support::cpp11::copysign</a>(<a class="code" href="namespacearm__compute_1_1support_1_1cpp11.xhtml#ab71c35ca207b916a9f8b0336ab88484e">support::cpp11::round</a>(positive_value), <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>);</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1support_1_1cpp11_xhtml_a28096f8372c0ad762864c790917375e2"><div class="ttname"><a href="namespacearm__compute_1_1support_1_1cpp11.xhtml#a28096f8372c0ad762864c790917375e2">arm_compute::support::cpp11::copysign</a></div><div class="ttdeci">T copysign(T x, T y)</div><div class="ttdoc">Composes a floating point value with the magnitude of x and the sign of y. </div><div class="ttdef"><b>Definition:</b> <a href="_toolchain_support_8h_source.xhtml#l00259">ToolchainSupport.h:259</a></div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1support_1_1cpp11_xhtml_ab71c35ca207b916a9f8b0336ab88484e"><div class="ttname"><a href="namespacearm__compute_1_1support_1_1cpp11.xhtml#ab71c35ca207b916a9f8b0336ab88484e">arm_compute::support::cpp11::round</a></div><div class="ttdeci">T round(T value)</div><div class="ttdoc">Round floating-point value with half value rounding away from zero. </div><div class="ttdef"><b>Definition:</b> <a href="_toolchain_support_8h_source.xhtml#l00228">ToolchainSupport.h:228</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ae115fc750a92fb6a5e094998b56fcc56"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ae115fc750a92fb6a5e094998b56fcc56">arm_compute::test::fixed_point_arithmetic::detail::abs</a></div><div class="ttdeci">fixed_point&lt; T &gt; abs(fixed_point&lt; T &gt; x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00914">FixedPoint.h:914</a></div></div>
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<td class="memname">T arm_compute::test::round_half_up </td>
<td>(</td>
<td class="paramtype">T&#160;</td>
<td class="paramname"><em>value</em></td><td>)</td>
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<p>Round floating-point value with half value rounding to positive infinity. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">value</td><td>floating-point value to be rounded.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>Floating-point value of rounded <code>value</code>. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00056">56</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;{</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keywordflow">return</span> std::floor(<a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a> + 0.5f);</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160;}</div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
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<td class="memname">T arm_compute::test::saturate_cast </td>
<td>(</td>
<td class="paramtype">T&#160;</td>
<td class="paramname"><em>val</em></td><td>)</td>
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<p>Saturate a value of type T against the numeric limits of type U. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">val</td><td>Value to be saturated.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>saturated value. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00278">278</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00889">arm_compute::test::fixed_point_arithmetic::detail::max()</a>.</p>
<p>Referenced by <a class="el" href="validation_2_c_p_p_2_depthwise_convolution_8cpp_source.xhtml#l00048">arm_compute::test::validation::reference::depthwise_convolution()</a>, and <a class="el" href="_c_p_p_2_non_linear_filter_8cpp_source.xhtml#l00036">arm_compute::test::validation::reference::non_linear_filter()</a>.</p>
<div class="fragment"><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160;{</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; <span class="keywordflow">if</span>(val &gt; static_cast&lt;T&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits&lt;U&gt;::max</a>()))</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; {</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; val = <span class="keyword">static_cast&lt;</span>T<span class="keyword">&gt;</span>(<a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits&lt;U&gt;::max</a>());</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; }</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; <span class="keywordflow">if</span>(val &lt; static_cast&lt;T&gt;(std::numeric_limits&lt;U&gt;::lowest()))</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; {</div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; val = <span class="keyword">static_cast&lt;</span>T<span class="keyword">&gt;</span>(std::numeric_limits&lt;U&gt;::lowest());</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; }</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; <span class="keywordflow">return</span> val;</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ad91bb73431b4de1f4946ed949d444849"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">arm_compute::test::fixed_point_arithmetic::detail::max</a></div><div class="ttdeci">fixed_point&lt; T &gt; max(fixed_point&lt; T &gt; x, fixed_point&lt; T &gt; y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00889">FixedPoint.h:889</a></div></div>
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<td class="memname"><a class="el" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> arm_compute::test::shape_to_valid_region </td>
<td>(</td>
<td class="paramtype">TensorShape&#160;</td>
<td class="paramname"><em>shape</em>, </td>
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<td></td>
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<td class="paramname"><em>border_size</em> = <code>BorderSize(0)</code>&#160;</td>
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<p>Create a valid region based on tensor shape, border mode and border size. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">shape</td><td>Shape used as size of the valid region. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">border_undefined</td><td>(Optional) Boolean indicating if the border mode is undefined. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">border_size</td><td>(Optional) Border size used to specify the region to exclude.</td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>A valid region starting at (0, 0, ...) with size of <code>shape</code> if <code>border_undefined</code> is false; otherwise return A valid region starting at (<code>border_size.left</code>, <code>border_size.top</code>, ...) with reduced size of <code>shape</code>. </dd></dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00193">193</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00124">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00889">arm_compute::test::fixed_point_arithmetic::detail::max()</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00109">Dimensions&lt; T &gt;::num_dimensions()</a>, <a class="el" href="_tensor_shape_8h_source.xhtml#l00074">TensorShape::set()</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00074">Dimensions&lt; T &gt;::set()</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00115">Dimensions&lt; T &gt;::set_num_dimensions()</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00081">Dimensions&lt; T &gt;::x()</a>, and <a class="el" href="_dimensions_8h_source.xhtml#l00086">Dimensions&lt; T &gt;::y()</a>.</p>
<p>Referenced by <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00064">arm_compute::test::validation::DATA_TEST_CASE()</a>, <a class="el" href="_c_l_2_box3x3_8cpp_source.xhtml#l00091">arm_compute::test::validation::FIXTURE_DATA_TEST_CASE()</a>, <a class="el" href="_c_p_p_2_non_linear_filter_8cpp_source.xhtml#l00036">arm_compute::test::validation::reference::non_linear_filter()</a>, <a class="el" href="_non_maxima_suppression_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::non_maxima_suppression()</a>, <a class="el" href="_c_p_p_2_sobel_8cpp_source.xhtml#l00106">arm_compute::test::validation::reference::sobel()</a>, and <a class="el" href="_validation_8h_source.xhtml#l00312">arm_compute::test::validation::validate()</a>.</p>
<div class="fragment"><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160;{</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; Coordinates anchor;</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; anchor.set_num_dimensions(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.num_dimensions());</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160;</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; <span class="keywordflow">if</span>(border_undefined)</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; {</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.num_dimensions() &lt; 2);</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160;</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; anchor.set(0, border_size.left);</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; anchor.set(1, border_size.top);</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160;</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> valid_shape_x = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(0, static_cast&lt;int&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.x()) - static_cast&lt;int&gt;(border_size.left) - <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(border_size.right));</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> valid_shape_y = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(0, static_cast&lt;int&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.y()) - static_cast&lt;int&gt;(border_size.top) - <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(border_size.bottom));</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160;</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.set(0, valid_shape_x);</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.set(1, valid_shape_y);</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; }</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160;</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <span class="keywordflow">return</span> ValidRegion(std::move(anchor), std::move(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>));</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00089">MinMaxLocation.cpp:89</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00124">Error.h:124</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ad91bb73431b4de1f4946ed949d444849"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">arm_compute::test::fixed_point_arithmetic::detail::max</a></div><div class="ttdeci">fixed_point&lt; T &gt; max(fixed_point&lt; T &gt; x, fixed_point&lt; T &gt; y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00889">FixedPoint.h:889</a></div></div>
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<td class="memname">void arm_compute::test::store_value_with_data_type </td>
<td>(</td>
<td class="paramtype">void *&#160;</td>
<td class="paramname"><em>ptr</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">T&#160;</td>
<td class="paramname"><em>value</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">DataType&#160;</td>
<td class="paramname"><em>data_type</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Write the value after casting the pointer according to <code>data_type</code>. </p>
<dl class="section warning"><dt>Warning</dt><dd>The type of the value must match the specified data type.</dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[out]</td><td class="paramname">ptr</td><td>Pointer to memory where the <code>value</code> will be written. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">value</td><td>Value that will be written. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">data_type</td><td>Data type that will be written. </td></tr>
</table>
</dd>
</dl>
<p>Definition at line <a class="el" href="tests_2_utils_8h_source.xhtml#l00224">224</a> of file <a class="el" href="tests_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::F16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::F64</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9">arm_compute::QS16</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::QS8</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::S64</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::S8</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">arm_compute::SIZET</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::U16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::U32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::U64</a>, and <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>.</p>
<p>Referenced by <a class="el" href="_assets_library_8h_source.xhtml#l00403">AssetsLibrary::fill()</a>, and <a class="el" href="_assets_library_8h_source.xhtml#l00377">AssetsLibrary::fill_borders_with_garbage()</a>.</p>
<div class="fragment"><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160;{</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; <span class="keywordflow">switch</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>)</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; {</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="keywordflow">case</span> DataType::U8:</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>uint8_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; <span class="keywordflow">case</span> DataType::S8:</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; <span class="keywordflow">case</span> DataType::QS8:</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>int8_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; <span class="keywordflow">case</span> DataType::U16:</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>uint16_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; <span class="keywordflow">case</span> DataType::S16:</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; <span class="keywordflow">case</span> DataType::QS16:</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>int16_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; <span class="keywordflow">case</span> DataType::U32:</div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>uint32_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; <span class="keywordflow">case</span> DataType::S32:</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>int32_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; <span class="keywordflow">case</span> DataType::U64:</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>uint64_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; <span class="keywordflow">case</span> DataType::S64:</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>int64_t *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; <span class="keywordflow">case</span> DataType::F16:</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span><a class="code" href="namespacearm__compute.xhtml#a73e2825fd61d349c5ca2f5313e3c8ea1">half</a> *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; <span class="keywordflow">case</span> DataType::F32:</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; <span class="keywordflow">case</span> DataType::F64:</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">double</span> *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; <span class="keywordflow">case</span> DataType::SIZET:</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">size_t</span> *<span class="keyword">&gt;</span>(ptr) = <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>;</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;NOT SUPPORTED!&quot;</span>);</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; }</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160;}</div>
<div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a73e2825fd61d349c5ca2f5313e3c8ea1"><div class="ttname"><a href="namespacearm__compute.xhtml#a73e2825fd61d349c5ca2f5313e3c8ea1">arm_compute::half</a></div><div class="ttdeci">half_float::half half</div><div class="ttdoc">16-bit floating point type </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00039">Types.h:39</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ac2ad7f431e3446fddcd9b6b9f93c4c14"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00090">MinMaxLocation.cpp:90</a></div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
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<td class="memname">void arm_compute::test::swap </td>
<td>(</td>
<td class="paramtype">SimpleTensor&lt; U &gt; &amp;&#160;</td>
<td class="paramname"><em>tensor1</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">SimpleTensor&lt; U &gt; &amp;&#160;</td>
<td class="paramname"><em>tensor2</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">tensor1</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to be swapped. </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">tensor2</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to be swapped. </td></tr>
</table>
</dd>
</dl>
<p>Definition at line <a class="el" href="_simple_tensor_8h_source.xhtml#l00335">335</a> of file <a class="el" href="_simple_tensor_8h_source.xhtml">SimpleTensor.h</a>.</p>
<p>Referenced by <a class="el" href="_simple_tensor_8h_source.xhtml#l00214">SimpleTensor&lt; T &gt;::operator=()</a>.</p>
<div class="fragment"><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160;{</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; <span class="comment">// Use unqualified call to swap to enable ADL. But make std::swap available</span></div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; <span class="comment">// as backup.</span></div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; <span class="keyword">using</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">std::swap</a>;</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._shape, tensor2._shape);</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._format, tensor2._format);</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._data_type, tensor2._data_type);</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._num_channels, tensor2._num_channels);</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._buffer, tensor2._buffer);</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a28edc8880596d14c099f3c2509efc8b3"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">arm_compute::test::swap</a></div><div class="ttdeci">void swap(SimpleTensor&lt; U &gt; &amp;tensor1, SimpleTensor&lt; U &gt; &amp;tensor2)</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00335">SimpleTensor.h:335</a></div></div>
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<td class="memname">std::string arm_compute::test::tolower </td>
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<p>Convert string to lower case. </p>
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<tr><td class="paramdir">[in]</td><td class="paramname">string</td><td>To be converted string.</td></tr>
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<dl class="section return"><dt>Returns</dt><dd>Lower case string. </dd></dl>
<p>Definition at line <a class="el" href="tests_2framework_2_utils_8h_source.xhtml#l00147">147</a> of file <a class="el" href="tests_2framework_2_utils_8h_source.xhtml">Utils.h</a>.</p>
<p>Referenced by <a class="el" href="_u_n_i_t_2_fixed_point_8cpp_source.xhtml#l00067">arm_compute::test::validation::DATA_TEST_CASE()</a>, <a class="el" href="_dataset_modes_8cpp_source.xhtml#l00036">arm_compute::test::framework::dataset_mode_from_name()</a>, <a class="el" href="_instruments_8cpp_source.xhtml#l00037">arm_compute::test::framework::instrument_type_from_name()</a>, <a class="el" href="_printers_8cpp_source.xhtml#l00037">arm_compute::test::framework::log_format_from_name()</a>, and <a class="el" href="_exceptions_8cpp_source.xhtml#l00037">arm_compute::test::framework::log_level_from_name()</a>.</p>
<div class="fragment"><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160;{</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; std::transform(<span class="keywordtype">string</span>.begin(), <span class="keywordtype">string</span>.end(), <span class="keywordtype">string</span>.begin(), [](<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> c)</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; {</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a5b67cbf475b1e1d3bec9b0b937fdafac">std::tolower</a>(c);</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; });</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <span class="keywordflow">return</span> string;</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160;}</div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a5b67cbf475b1e1d3bec9b0b937fdafac"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a5b67cbf475b1e1d3bec9b0b937fdafac">arm_compute::test::tolower</a></div><div class="ttdeci">std::string tolower(std::string string)</div><div class="ttdoc">Convert string to lower case. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2framework_2_utils_8h_source.xhtml#l00147">Utils.h:147</a></div></div>
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<h2 class="groupheader">Variable Documentation</h2>
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<td class="memname">const auto data_types = <a class="el" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(&quot;DataType&quot;, { DataType::F32 })</td>
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<p>Definition at line <a class="el" href="benchmark_2_c_l_2_depthwise_convolution_8cpp_source.xhtml#l00040">40</a> of file <a class="el" href="benchmark_2_c_l_2_depthwise_convolution_8cpp_source.xhtml">DepthwiseConvolution.cpp</a>.</p>
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<td class="memname">std::unique_ptr&lt; <a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml">AssetsLibrary</a> &gt; library</td>
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<p>Definition at line <a class="el" href="main_8cpp_source.xhtml#l00055">55</a> of file <a class="el" href="main_8cpp_source.xhtml">main.cpp</a>.</p>
<p>Referenced by <a class="el" href="_c_l_2_fill_border_8cpp_source.xhtml#l00052">arm_compute::test::validation::DATA_TEST_CASE()</a>, <a class="el" href="_le_net5_network_8h_source.xhtml#l00152">LeNet5Network&lt; TensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;::feed()</a>, <a class="el" href="_alex_net_network_8h_source.xhtml#l00413">AlexNetNetwork&lt; ITensorType, TensorType, SubTensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;::feed()</a>, <a class="el" href="_le_net5_network_8h_source.xhtml#l00136">LeNet5Network&lt; TensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;::fill()</a>, <a class="el" href="_alex_net_network_8h_source.xhtml#l00396">AlexNetNetwork&lt; ITensorType, TensorType, SubTensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;::fill()</a>, <a class="el" href="tests_2validation_2_helpers_8h_source.xhtml#l00169">arm_compute::test::validation::fill_lookuptable()</a>, <a class="el" href="_helpers_8cpp_source.xhtml#l00032">arm_compute::test::validation::fill_mask_from_pattern()</a>, <a class="el" href="_le_net5_network_8h_source.xhtml#l00120">LeNet5Network&lt; TensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, FullyConnectedLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;::fill_random()</a>, <a class="el" href="_alex_net_network_8h_source.xhtml#l00346">AlexNetNetwork&lt; ITensorType, TensorType, SubTensorType, arm_compute::test::Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, FullyConnectedLayerFunction, NormalizationLayerFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;::fill_random()</a>, <a class="el" href="_helper_8h_source.xhtml#l00039">fill_tensors()</a>, <a class="el" href="tests_2validation_2_c_p_p_2_utils_8h_source.xhtml#l00109">arm_compute::test::validation::fill_warp_matrix()</a>, <a class="el" href="_helpers_8cpp_source.xhtml#l00098">arm_compute::test::validation::harris_corners_parameters()</a>, <a class="el" href="main_8cpp_source.xhtml#l00059">main()</a>, <a class="el" href="benchmark_2fixtures_2_convolution_layer_fixture_8h_source.xhtml#l00043">ConvolutionLayerFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_batch_normalization_layer_fixture_8h_source.xhtml#l00043">BatchNormalizationLayerFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_fully_connected_layer_fixture_8h_source.xhtml#l00043">FullyConnectedLayerFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_floor_fixture_8h_source.xhtml#l00043">FloorFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_g_e_m_m_fixture_8h_source.xhtml#l00043">GEMMFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_normalization_layer_fixture_8h_source.xhtml#l00043">NormalizationLayerFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_activation_layer_fixture_8h_source.xhtml#l00043">ActivationLayerFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_depthwise_convolution_fixture_8h_source.xhtml#l00043">DepthwiseConvolutionFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_pooling_layer_fixture_8h_source.xhtml#l00043">PoolingLayerFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="benchmark_2fixtures_2_depthwise_separable_convolution_layer_fixture_8h_source.xhtml#l00043">DepthwiseSeparableConvolutionLayerFixture&lt; TensorType, Function, Accessor &gt;::setup()</a>, <a class="el" href="_r_o_i_pooling_layer_fixture_8h_source.xhtml#l00045">ROIPoolingLayerFixture&lt; TensorType, Function, Accessor, Array_T, ArrayAccessor &gt;::setup()</a>, <a class="el" href="_scale_fixture_8h_source.xhtml#l00047">ScaleValidationFixture&lt; TensorType, AccessorType, FunctionType, T &gt;::setup()</a>, <a class="el" href="_non_linear_filter_fixture_8h_source.xhtml#l00048">NonLinearFilterValidationFixture&lt; TensorType, AccessorType, FunctionType, T &gt;::setup()</a>, <a class="el" href="_box3x3_fixture_8h_source.xhtml#l00049">Box3x3ValidationFixture&lt; TensorType, AccessorType, FunctionType, T &gt;::setup()</a>, <a class="el" href="_gaussian5x5_fixture_8h_source.xhtml#l00049">Gaussian5x5ValidationFixture&lt; TensorType, AccessorType, FunctionType, T &gt;::setup()</a>, <a class="el" href="_gaussian3x3_fixture_8h_source.xhtml#l00049">Gaussian3x3ValidationFixture&lt; TensorType, AccessorType, FunctionType, T &gt;::setup()</a>, <a class="el" href="_depth_concatenate_layer_fixture_8h_source.xhtml#l00050">DepthConcatenateValidationFixture&lt; TensorType, ITensorType, AccessorType, FunctionType, T &gt;::setup()</a>, <a class="el" href="_warp_affine_fixture_8h_source.xhtml#l00050">WarpAffineValidationFixture&lt; TensorType, AccessorType, FunctionType, T &gt;::setup()</a>, <a class="el" href="_warp_perspective_fixture_8h_source.xhtml#l00050">WarpPerspectiveValidationFixture&lt; TensorType, AccessorType, FunctionType, T &gt;::setup()</a>, and <a class="el" href="_sobel_fixture_8h_source.xhtml#l00105">SobelValidationFixture&lt; TensorType, AccessorType, FunctionType, T, U &gt;::setup()</a>.</p>
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