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| <a href="#pub-methods">Public Member Functions</a> | |
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| <div class="title">CLConvolutionLayer Class Reference</div> </div> |
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| |
| <p>Basic function to compute the convolution layer. |
| <a href="classarm__compute_1_1_c_l_convolution_layer.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_c_l_convolution_layer_8h_source.xhtml">CLConvolutionLayer.h</a>></code></p> |
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| Collaboration diagram for CLConvolutionLayer:</div> |
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| <table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a> |
| Public Member Functions</h2></td></tr> |
| <tr class="memitem:a3c3a42aeb64bcce1705ac4159fcf938e"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a3c3a42aeb64bcce1705ac4159fcf938e">CLConvolutionLayer</a> (std::shared_ptr< <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> > memory_manager=nullptr)</td></tr> |
| <tr class="memdesc:a3c3a42aeb64bcce1705ac4159fcf938e"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <a href="#a3c3a42aeb64bcce1705ac4159fcf938e">More...</a><br /></td></tr> |
| <tr class="separator:a3c3a42aeb64bcce1705ac4159fcf938e"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ae0c61dabbcfeda5c7f01a7ae66e58b2c"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#ae0c61dabbcfeda5c7f01a7ae66e58b2c">configure</a> (<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *weights, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *biases, <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &conv_info, const <a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a> &weights_info=<a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a>(), const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &dilation=<a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U), const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false, unsigned int num_groups=1)</td></tr> |
| <tr class="memdesc:ae0c61dabbcfeda5c7f01a7ae66e58b2c"><td class="mdescLeft"> </td><td class="mdescRight">Set the input and output tensors. <a href="#ae0c61dabbcfeda5c7f01a7ae66e58b2c">More...</a><br /></td></tr> |
| <tr class="separator:ae0c61dabbcfeda5c7f01a7ae66e58b2c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr> |
| <tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft"> </td><td class="mdescRight">Run the kernels contained in the function. <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br /></td></tr> |
| <tr class="separator:ad1717410afd0be936c6213a63c8005fb"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aa9b93ef660fc3c5b4b19d3fc7b891b77"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a> () override</td></tr> |
| <tr class="memdesc:aa9b93ef660fc3c5b4b19d3fc7b891b77"><td class="mdescLeft"> </td><td class="mdescRight">Prepare the function for executing. <a href="#aa9b93ef660fc3c5b4b19d3fc7b891b77">More...</a><br /></td></tr> |
| <tr class="separator:aa9b93ef660fc3c5b4b19d3fc7b891b77"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="inherit_header pub_methods_classarm__compute_1_1_i_function"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_function')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></td></tr> |
| <tr class="memitem:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">~IFunction</a> ()=default</td></tr> |
| <tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft"> </td><td class="mdescRight">Destructor. <a href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br /></td></tr> |
| <tr class="separator:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2"> </td></tr> |
| </table><table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a> |
| Static Public Member Functions</h2></td></tr> |
| <tr class="memitem:a1a37ad594537835b39165a1369dd254c"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a1a37ad594537835b39165a1369dd254c">validate</a> (const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *weights, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *biases, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &conv_info, const <a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a> &weights_info=<a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a>(), const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &dilation=<a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U), const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false, unsigned int num_groups=1)</td></tr> |
| <tr class="memdesc:a1a37ad594537835b39165a1369dd254c"><td class="mdescLeft"> </td><td class="mdescRight">Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>. <a href="#a1a37ad594537835b39165a1369dd254c">More...</a><br /></td></tr> |
| <tr class="separator:a1a37ad594537835b39165a1369dd254c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a52d5a4b1c55ce0198a793d5ebe5eb714"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517d">ConvolutionMethod</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a52d5a4b1c55ce0198a793d5ebe5eb714">get_convolution_method</a> (const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *weights, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &conv_info, const <a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a> &weights_info, const <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &act_info, const <a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target, const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &dilation=<a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U), bool enable_fast_math=false)</td></tr> |
| <tr class="memdesc:a52d5a4b1c55ce0198a793d5ebe5eb714"><td class="mdescLeft"> </td><td class="mdescRight">Static function to check if given info will return the convolution called by <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>. <a href="#a52d5a4b1c55ce0198a793d5ebe5eb714">More...</a><br /></td></tr> |
| <tr class="separator:a52d5a4b1c55ce0198a793d5ebe5eb714"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>Basic function to compute the convolution layer. </p> |
| <p>This function calls the following OpenCL kernels/functions:</p> |
| <ol type="1"> |
| <li><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_convolution_layer.xhtml">CLGEMMConvolutionLayer</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml">CLWinogradConvolutionLayer</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml">CLDirectConvolutionLayer</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_f_f_t_convolution_layer.xhtml">CLFFTConvolutionLayer</a></li> |
| </ol> |
| <p>The function selects one of the algorithms mentioned above based on:</p><ul> |
| <li>The size of the kernel</li> |
| <li>Number of input/output feature maps</li> |
| <li>Amount of memory needed</li> |
| </ul> |
| <p>Generally GEMM-based convolution is executed when neither Winograd nor FFT nor Direct convolution can be performed.</p> |
| <table class="markdownTable"> |
| <tr class="markdownTableHead"> |
| <th class="markdownTableHeadNone">FP32 Algorithm </th><th class="markdownTableHeadNone">Filter Size </th><th class="markdownTableHeadNone">Input/Output feature maps </th></tr> |
| <tr class="markdownTableRowOdd"> |
| <td class="markdownTableBodyNone">Winograd </td><td class="markdownTableBodyNone">3x3 1x3 3x1 5x1 1x5 5x5(fast maths) 7x1 1x7 </td><td class="markdownTableBodyNone">Input channels is greater than 3 </td></tr> |
| <tr class="markdownTableRowEven"> |
| <td class="markdownTableBodyNone">FFT </td><td class="markdownTableBodyNone">Squared kernels and greater than 9x9 </td><td class="markdownTableBodyNone">Input feature maps > Output feature maps </td></tr> |
| <tr class="markdownTableRowOdd"> |
| <td class="markdownTableBodyNone">DirectConv </td><td class="markdownTableBodyNone">9x9 </td><td class="markdownTableBodyNone"></td></tr> |
| <tr class="markdownTableRowEven"> |
| <td class="markdownTableBodyNone">GEMM </td><td class="markdownTableBodyNone">Any size </td><td class="markdownTableBodyNone"></td></tr> |
| </table> |
| <p>Winograd 5x5 requires fast maths enabled.</p> |
| <table class="markdownTable"> |
| <tr class="markdownTableHead"> |
| <th class="markdownTableHeadNone">FP16 Algorithm </th><th class="markdownTableHeadNone">Filter Size </th><th class="markdownTableHeadNone">Input/Output feature maps </th></tr> |
| <tr class="markdownTableRowOdd"> |
| <td class="markdownTableBodyNone">Winograd </td><td class="markdownTableBodyNone">3x3 1x3 3x1 5x1 1x5 5x5 </td><td class="markdownTableBodyNone">Input channels is greater than 3 </td></tr> |
| <tr class="markdownTableRowEven"> |
| <td class="markdownTableBodyNone">FFT </td><td class="markdownTableBodyNone">Not supported </td><td class="markdownTableBodyNone"></td></tr> |
| <tr class="markdownTableRowOdd"> |
| <td class="markdownTableBodyNone">DirectConv </td><td class="markdownTableBodyNone">9x9 </td><td class="markdownTableBodyNone"></td></tr> |
| <tr class="markdownTableRowEven"> |
| <td class="markdownTableBodyNone">GEMM </td><td class="markdownTableBodyNone">Any size </td><td class="markdownTableBodyNone"></td></tr> |
| </table> |
| <p>Winograd FP16 requires fast maths enabled. </p> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_convolution_layer_8h_source.xhtml#l00071">71</a> of file <a class="el" href="_c_l_convolution_layer_8h_source.xhtml">CLConvolutionLayer.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a id="a3c3a42aeb64bcce1705ac4159fcf938e"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a3c3a42aeb64bcce1705ac4159fcf938e">◆ </a></span>CLConvolutionLayer()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a> </td> |
| <td>(</td> |
| <td class="paramtype">std::shared_ptr< <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> > </td> |
| <td class="paramname"><em>memory_manager</em> = <code>nullptr</code></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Default constructor. </p> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00040">40</a> of file <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml">CLConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  : _memory_manager(std::move(memory_manager)), _function()</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <h2 class="groupheader">Member Function Documentation</h2> |
| <a id="ae0c61dabbcfeda5c7f01a7ae66e58b2c"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ae0c61dabbcfeda5c7f01a7ae66e58b2c">◆ </a></span>configure()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void configure </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td> |
| <td class="paramname"><em>input</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td> |
| <td class="paramname"><em>weights</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td> |
| <td class="paramname"><em>biases</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td> |
| <td class="paramname"><em>output</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> & </td> |
| <td class="paramname"><em>conv_info</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a> & </td> |
| <td class="paramname"><em>weights_info</em> = <code><a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a>()</code>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> & </td> |
| <td class="paramname"><em>dilation</em> = <code><a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U)</code>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> & </td> |
| <td class="paramname"><em>act_info</em> = <code><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>()</code>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">bool </td> |
| <td class="paramname"><em>enable_fast_math</em> = <code>false</code>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">unsigned int </td> |
| <td class="paramname"><em>num_groups</em> = <code>1</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Set the input and output tensors. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor. 3 lower dimensions represent a single input [width, height, IFM], while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/F16/F32. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">biases</td><td>Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Should match <code>input</code> data type, except for input of QASYMM8 type where biases should be of S32 type. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. Data types supported: Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Contains padding and stride information described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights_info</td><td>Specifies if the weights tensor has been reshaped with <a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml" title="OpenCL kernel to perform reshaping on the weights used by convolution and locally connected layer.">CLWeightsReshapeKernel</a>. Data type supported: Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">dilation</td><td>(Optional) Dilation, in elements, across x and y. Defaults to (1, 1). </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">enable_fast_math</td><td>(Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation available which may introduce a drop of accuracy as well. Default is false </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">num_groups</td><td>(Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00045">45</a> of file <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml">CLConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, output);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(<a class="code" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a1a37ad594537835b39165a1369dd254c">CLConvolutionLayer::validate</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), ((biases != <span class="keyword">nullptr</span>) ? biases-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>() : <span class="keyword">nullptr</span>), output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">weights_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  enable_fast_math, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>));</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">switch</span>(<a class="code" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a52d5a4b1c55ce0198a793d5ebe5eb714">CLConvolutionLayer::get_convolution_method</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">weights_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a27561688e2fc60176608ef725a4ecb30">target</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>, enable_fast_math))</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">ConvolutionMethod::WINOGRAD</a>:</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  {</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a> != 1);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">auto</span> f = arm_compute::support::cpp14::make_unique<CLWinogradConvolutionLayer>(_memory_manager);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  f->configure(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, enable_fast_math);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  _function = std::move(f);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  }</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">ConvolutionMethod::DIRECT</a>:</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a> != 1);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">auto</span> f = arm_compute::support::cpp14::make_unique<CLDirectConvolutionLayer>();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  f->configure(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  _function = std::move(f);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  }</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>:</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">auto</span> f = arm_compute::support::cpp14::make_unique<CLGEMMConvolutionLayer>(_memory_manager);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  f->configure(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">weights_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  _function = std::move(f);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  }</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">ConvolutionMethod::FFT</a>:</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">auto</span> f = arm_compute::support::cpp14::make_unique<CLFFTConvolutionLayer>(_memory_manager);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  f->configure(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  _function = std::move(f);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  }</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Not supported."</span>);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  }</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> }</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#l00261">Error.h:261</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_ad45f0c01a0713dfb6bd7232c7f396fc4"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">arm_compute::CLTensor::info</a></div><div class="ttdeci">TensorInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00035">CLTensor.cpp:35</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ad3fd4136244e42ad89b01c02b904336d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">arm_compute::test::validation::dilation</a></div><div class="ttdeci">dilation</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">ConvolutionLayer.cpp:175</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler & get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler.cpp:41</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7cb842ebfe255726066039853a4322f0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">arm_compute::test::validation::weights_info</a></div><div class="ttdeci">weights_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00196">BatchNormalizationLayer.cpp:196</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a27561688e2fc60176608ef725a4ecb30"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a27561688e2fc60176608ef725a4ecb30">arm_compute::CLScheduler::target</a></div><div class="ttdeci">GPUTarget target() const</div><div class="ttdoc">Get the target GPU.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8h_source.xhtml#l00112">CLScheduler.h:112</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00599">Winograd.cpp:599</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#l00337">Error.h:337</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00327">Error.h:327</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_convolution_layer_xhtml_a1a37ad594537835b39165a1369dd254c"><div class="ttname"><a href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a1a37ad594537835b39165a1369dd254c">arm_compute::CLConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info=WeightsInfo(), const Size2D &dilation=Size2D(1U, 1U), const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false, unsigned int num_groups=1)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLConvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_convolution_layer_8cpp_source.xhtml#l00091">CLConvolutionLayer.cpp:91</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">arm_compute::ConvolutionMethod::DIRECT</a></div><div class="ttdoc">Direct convolution.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a2270b3e1d20651d2d8341c858c890830"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">arm_compute::test::validation::num_groups</a></div><div class="ttdeci">const unsigned int num_groups</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00148">Im2Col.cpp:148</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">arm_compute::ConvolutionMethod::WINOGRAD</a></div><div class="ttdoc">Convolution using Winograd.</div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_convolution_layer_xhtml_a52d5a4b1c55ce0198a793d5ebe5eb714"><div class="ttname"><a href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a52d5a4b1c55ce0198a793d5ebe5eb714">arm_compute::CLConvolutionLayer::get_convolution_method</a></div><div class="ttdeci">static ConvolutionMethod get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, const ActivationLayerInfo &act_info, const GPUTarget gpu_target, const Size2D &dilation=Size2D(1U, 1U), bool enable_fast_math=false)</div><div class="ttdoc">Static function to check if given info will return the convolution called by CLConvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_convolution_layer_8cpp_source.xhtml#l00135">CLConvolutionLayer.cpp:135</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">arm_compute::ConvolutionMethod::FFT</a></div><div class="ttdoc">Convolution using FFT.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">arm_compute::ConvolutionMethod::GEMM</a></div><div class="ttdoc">Convolution using GEMM.</div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">arm_compute::test::validation::act_info</a>, <a class="el" href="_error_8h_source.xhtml#l00261">ARM_COMPUTE_ERROR</a>, <a class="el" href="_error_8h_source.xhtml#l00337">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00327">ARM_COMPUTE_ERROR_THROW_ON</a>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00599">arm_compute::test::validation::conv_info</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::dilation</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">arm_compute::DIRECT</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">arm_compute::FFT</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">arm_compute::GEMM</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</a>, <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00135">CLConvolutionLayer::get_convolution_method()</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00035">CLTensor::info()</a>, <a class="el" href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00148">arm_compute::test::validation::num_groups</a>, <a class="el" href="_c_l_scheduler_8h_source.xhtml#l00112">CLScheduler::target()</a>, <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00091">CLConvolutionLayer::validate()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">arm_compute::test::validation::weights</a>, <a class="el" href="validation_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00196">arm_compute::test::validation::weights_info</a>, and <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">arm_compute::WINOGRAD</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_c_l_direct_deconvolution_layer_8cpp_source.xhtml#l00107">CLDirectDeconvolutionLayer::configure()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="a52d5a4b1c55ce0198a793d5ebe5eb714"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a52d5a4b1c55ce0198a793d5ebe5eb714">◆ </a></span>get_convolution_method()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517d">ConvolutionMethod</a> get_convolution_method </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>input</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>weights</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>output</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> & </td> |
| <td class="paramname"><em>conv_info</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a> & </td> |
| <td class="paramname"><em>weights_info</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> & </td> |
| <td class="paramname"><em>act_info</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> </td> |
| <td class="paramname"><em>gpu_target</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> & </td> |
| <td class="paramname"><em>dilation</em> = <code><a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U)</code>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">bool </td> |
| <td class="paramname"><em>enable_fast_math</em> = <code>false</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">static</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Static function to check if given info will return the convolution called by <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor. 3 lower dimensions represent a single input [width, height, IFM], while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/F16/F32. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. Data types supported: Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Contains padding and stride information described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights_info</td><td>Specifies if the weights tensor has been reshaped with <a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml" title="OpenCL kernel to perform reshaping on the weights used by convolution and locally connected layer.">CLWeightsReshapeKernel</a>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">gpu_target</td><td>Specifies the <code>GPUTarget</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">dilation</td><td>(Optional) Dilation, in elements, across x and y. Defaults to (1, 1). </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">enable_fast_math</td><td>(Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation available which may introduce a drop of accuracy as well. Default is false</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00135">135</a> of file <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml">CLConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> {</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(output);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>);</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">weights_info</a>);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(gpu_target);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_w = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_h = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_c = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="comment">/* Input spatial dims, kernel size, IFM/OFM, conv info*/</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keyword">using</span> ConvolutionConfiguration = std::tuple<Size2D, Size2D, Size2D, PadStrideInfo, DataLayout>;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keyword">using</span> ConfigurationMethod = std::pair<ConvolutionConfiguration, ConvolutionMethod>;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">const</span> std::vector<ConfigurationMethod> known_configs =</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// Alexnet</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  ConfigurationMethod(ConvolutionConfiguration(<a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 27<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(5<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 5<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(48<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 128<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>), <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">ConvolutionMethod::DIRECT</a>),</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="comment">// VGG16 / VGG19</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  ConfigurationMethod(ConvolutionConfiguration(<a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 64<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>), <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">ConvolutionMethod::DIRECT</a>),</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// Mobilenet 224</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  ConfigurationMethod(ConvolutionConfiguration(<a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</a>), <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>), <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>),</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="comment">// Mobilenet 160</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  ConfigurationMethod(ConvolutionConfiguration(<a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(160<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 160<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 24<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</a>), <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>), <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>),</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="comment">// Mobilenet 224</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  ConfigurationMethod(ConvolutionConfiguration(<a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 224<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 32<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</a>), <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>), <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>),</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="comment">// Mobilenet 160</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  ConfigurationMethod(ConvolutionConfiguration(<a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(160<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 160<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(3<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 24<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>(2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, <a class="code" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">DimensionRoundingType::FLOOR</a>), <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>), <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>),</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  };</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keyword">const</span> <span class="keyword">auto</span> find_config = [&](ConfigurationMethod c)</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  {</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keyword">const</span> ConvolutionConfiguration config = c.first;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = std::get<3>(config);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> = std::get<4>(config);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">return</span> std::get<0>(config) == <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(idx_w), input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(idx_h)) && std::get<1>(config) == <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_w), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_h))</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  && std::get<2>(config) == <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_c), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(3)) && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.pad_top() == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top() && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.pad_right() == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right()</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.pad_bottom() == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_bottom() && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.pad_left() == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left() && <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.stride() == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride() && (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>());</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  };</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  std::vector<ConfigurationMethod>::const_iterator found;</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">if</span>((found = std::find_if(known_configs.begin(), known_configs.end(), find_config)) != known_configs.end())</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">return</span> (*found).second;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  }</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a> != <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>))</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  }</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  {</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="comment">// SRGAN</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordflow">if</span>((input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(idx_h) > 720<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>) && (output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(idx_h) > 720<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>) && (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_h) == 9) && (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top() < 3)</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  && (<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">CLDirectConvolutionLayer::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">nullptr</span>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>)))</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  {</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">ConvolutionMethod::DIRECT</a>;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  }</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keywordflow">if</span>((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_h) > 7) && (input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(idx_c) > output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(idx_c)) && (<a class="code" href="classarm__compute_1_1_c_l_f_f_t_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">CLFFTConvolutionLayer::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">nullptr</span>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>)))</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  {</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">ConvolutionMethod::FFT</a>;</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  }</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordflow">if</span>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(idx_c) < 16)</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  {</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  }</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">return</span> bool(<a class="code" href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml#a1c5a3dc6ea10d1f68d76064b82b8b5c2">CLWinogradConvolutionLayer::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">nullptr</span>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, enable_fast_math)) ? <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">ConvolutionMethod::WINOGRAD</a> : <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>;</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  }</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_acf5f12bbab64dd614bd8220c97fe484f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">arm_compute::test::validation::data_layout</a></div><div class="ttdeci">const DataLayout data_layout</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00146">Im2Col.cpp:146</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ad3fd4136244e42ad89b01c02b904336d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">arm_compute::test::validation::dilation</a></div><div class="ttdeci">dilation</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">ConvolutionLayer.cpp:175</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7cb842ebfe255726066039853a4322f0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">arm_compute::test::validation::weights_info</a></div><div class="ttdeci">weights_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00196">BatchNormalizationLayer.cpp:196</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00599">Winograd.cpp:599</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe"><div class="ttname"><a href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">arm_compute::DimensionRoundingType::FLOOR</a></div><div class="ttdoc">Floor rounding.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">arm_compute::DataLayoutDimension::HEIGHT</a></div><div class="ttdoc">height</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_xhtml_ac89fb11a78baf66222f50cd5ee725ebd"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">arm_compute::CLDirectConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDirectConvolutionLayer...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_8cpp_source.xhtml#l00068">CLDirectConvolutionLayer.cpp:68</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">arm_compute::ConvolutionMethod::DIRECT</a></div><div class="ttdoc">Direct convolution.</div></div> |
| <div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml">arm_compute::PadStrideInfo</a></div><div class="ttdoc">Padding and stride information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00676">Types.h:676</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">arm_compute::DataLayoutDimension::CHANNEL</a></div><div class="ttdoc">channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_winograd_convolution_layer_xhtml_a1c5a3dc6ea10d1f68d76064b82b8b5c2"><div class="ttname"><a href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml#a1c5a3dc6ea10d1f68d76064b82b8b5c2">arm_compute::CLWinogradConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLWinogradConvolutionLay...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_winograd_convolution_layer_8cpp_source.xhtml#l00149">CLWinogradConvolutionLayer.cpp:149</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">arm_compute::ConvolutionMethod::WINOGRAD</a></div><div class="ttdoc">Convolution using Winograd.</div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_size2_d_xhtml"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml">arm_compute::Size2D</a></div><div class="ttdoc">Class for specifying the size of an image or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00034">Size2D.h:34</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_f_f_t_convolution_layer_xhtml_ac89fb11a78baf66222f50cd5ee725ebd"><div class="ttname"><a href="classarm__compute_1_1_c_l_f_f_t_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">arm_compute::CLFFTConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLFFTConvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_f_f_t_convolution_layer_8cpp_source.xhtml#l00253">CLFFTConvolutionLayer.cpp:253</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">arm_compute::ConvolutionMethod::FFT</a></div><div class="ttdoc">Convolution using FFT.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::DataLayoutDimension::WIDTH</a></div><div class="ttdoc">width</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a46e938020a3ac8c926d0590b7fe957db"><div class="ttname"><a href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">arm_compute::get_data_layout_dimension_index</a></div><div class="ttdeci">size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)</div><div class="ttdoc">Get the index of the given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00326">Helpers.inl:326</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdoc">[DataLayout enum definition]</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00114">Types.h:114</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">arm_compute::ConvolutionMethod::GEMM</a></div><div class="ttdoc">Convolution using GEMM.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a367b5090ab432bc7de2c32369e087ab1"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">arm_compute::ITensorInfo::data_layout</a></div><div class="ttdeci">virtual DataLayout data_layout() const =0</div><div class="ttdoc">Get the data layout of the tensor.</div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">arm_compute::test::validation::act_info</a>, <a class="el" href="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00160">ARM_COMPUTE_UNUSED</a>, <a class="el" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">arm_compute::CHANNEL</a>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00599">arm_compute::test::validation::conv_info</a>, <a class="el" href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00146">arm_compute::test::validation::data_layout</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">ITensorInfo::data_layout()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::dilation</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">arm_compute::DIRECT</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">arm_compute::FFT</a>, <a class="el" href="namespacearm__compute.xhtml#a1fece1bd804e64f39f602d1c3969849aa56c1e354d36beb85b0d881c5b2e24cbe">arm_compute::FLOOR</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">arm_compute::GEMM</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00326">arm_compute::get_data_layout_dimension_index()</a>, <a class="el" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">arm_compute::HEIGHT</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::info</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::NCHW</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::NHWC</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::U</a>, <a class="el" href="_c_l_direct_convolution_layer_8cpp_source.xhtml#l00068">CLDirectConvolutionLayer::validate()</a>, <a class="el" href="_c_l_winograd_convolution_layer_8cpp_source.xhtml#l00149">CLWinogradConvolutionLayer::validate()</a>, <a class="el" href="_c_l_f_f_t_convolution_layer_8cpp_source.xhtml#l00253">CLFFTConvolutionLayer::validate()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">arm_compute::test::validation::weights</a>, <a class="el" href="validation_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00196">arm_compute::test::validation::weights_info</a>, <a class="el" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::WIDTH</a>, and <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">arm_compute::WINOGRAD</a>.</p> |
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| <p class="reference">Referenced by <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00045">CLConvolutionLayer::configure()</a>, and <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00091">CLConvolutionLayer::validate()</a>.</p> |
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| <a id="aa9b93ef660fc3c5b4b19d3fc7b891b77"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#aa9b93ef660fc3c5b4b19d3fc7b891b77">◆ </a></span>prepare()</h2> |
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| <td class="memname">void prepare </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
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| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td> |
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| <p>Prepare the function for executing. </p> |
| <p>Any one off pre-processing step required by the function is handled here</p> |
| <dl class="section note"><dt>Note</dt><dd>Prepare stage might not need all the function's buffers' backing memory to be available in order to execute </dd></dl> |
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| <p>Reimplemented from <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">IFunction</a>.</p> |
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| <p class="definition">Definition at line <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00215">215</a> of file <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml">CLConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  _function->prepare();</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> }</div></div><!-- fragment --> |
| <p class="reference">Referenced by <a class="el" href="_c_l_direct_deconvolution_layer_8cpp_source.xhtml#l00185">CLDirectDeconvolutionLayer::prepare()</a>, and <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00209">CLConvolutionLayer::run()</a>.</p> |
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| <a id="ad1717410afd0be936c6213a63c8005fb"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">◆ </a></span>run()</h2> |
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| <td class="memname">void run </td> |
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| <td class="paramname"></td><td>)</td> |
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| <p>Run the kernels contained in the function. </p> |
| <p>For NEON kernels:</p><ul> |
| <li>Multi-threading is used for the kernels which are parallelisable.</li> |
| <li>By default std::thread::hardware_concurrency() threads are used.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl> |
| <p>For OpenCL kernels:</p><ul> |
| <li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li> |
| <li>The queue is then flushed.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd> |
| <dd> |
| Will call <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl> |
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| <p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p> |
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| <p class="definition">Definition at line <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00209">209</a> of file <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml">CLConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>();</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  _function->run();</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> }</div><div class="ttc" id="classarm__compute_1_1_c_l_convolution_layer_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_c_l_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::CLConvolutionLayer::prepare</a></div><div class="ttdeci">void prepare() override</div><div class="ttdoc">Prepare the function for executing.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_convolution_layer_8cpp_source.xhtml#l00215">CLConvolutionLayer.cpp:215</a></div></div> |
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| <p class="reference">References <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00215">CLConvolutionLayer::prepare()</a>.</p> |
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| <p class="reference">Referenced by <a class="el" href="_c_l_direct_deconvolution_layer_8cpp_source.xhtml#l00175">CLDirectDeconvolutionLayer::run()</a>.</p> |
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| <a id="a1a37ad594537835b39165a1369dd254c"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a1a37ad594537835b39165a1369dd254c">◆ </a></span>validate()</h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>input</em>, </td> |
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| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>weights</em>, </td> |
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| <td class="paramkey"></td> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>biases</em>, </td> |
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| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>output</em>, </td> |
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| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> & </td> |
| <td class="paramname"><em>conv_info</em>, </td> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a> & </td> |
| <td class="paramname"><em>weights_info</em> = <code><a class="el" href="classarm__compute_1_1_weights_info.xhtml">WeightsInfo</a>()</code>, </td> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> & </td> |
| <td class="paramname"><em>dilation</em> = <code><a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(1U, 1U)</code>, </td> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> & </td> |
| <td class="paramname"><em>act_info</em> = <code><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>()</code>, </td> |
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| <td class="paramtype">bool </td> |
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| <td class="paramtype">unsigned int </td> |
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| <td>)</td> |
| <td></td><td></td> |
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| <span class="mlabels"><span class="mlabel">static</span></span> </td> |
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| <p>Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml">CLConvolutionLayer</a>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor. 3 lower dimensions represent a single input [width, height, IFM], while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/F16/F32. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">biases</td><td>Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported:Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. Data types supported: Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Contains padding and stride information described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights_info</td><td>Specifies if the weights tensor has been reshaped with <a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml" title="OpenCL kernel to perform reshaping on the weights used by convolution and locally connected layer.">CLWeightsReshapeKernel</a>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">dilation</td><td>(Optional) Dilation, in elements, across x and y. Defaults to (1, 1). </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">enable_fast_math</td><td>(Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation available which may introduce a drop of accuracy as well. Default is false </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">num_groups</td><td>(Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout</td></tr> |
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| <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl> |
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| <p class="definition">Definition at line <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00091">91</a> of file <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml">CLConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> {</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, output);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>((<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a> != 1) && (input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>() != <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>), <span class="stringliteral">"Grouping (num_groups != 1) with NHWC data layout is not supported"</span>);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> gpu_target = <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a27561688e2fc60176608ef725a4ecb30">target</a>();</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">switch</span>(<a class="code" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a52d5a4b1c55ce0198a793d5ebe5eb714">CLConvolutionLayer::get_convolution_method</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">weights_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, gpu_target, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>, enable_fast_math))</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">ConvolutionMethod::WINOGRAD</a>:</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">//Validate Winograd</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a> != 1, <span class="stringliteral">"Grouping (num_groups != 1) with CLWinogradConvolutionLayer is not supported"</span>);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml#a1c5a3dc6ea10d1f68d76064b82b8b5c2">CLWinogradConvolutionLayer::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, enable_fast_math));</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">ConvolutionMethod::DIRECT</a>:</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// Validate direct convolution layer</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a> != 1, <span class="stringliteral">"Grouping (num_groups != 1) with CLDirectConvolutionLayer is not supported"</span>);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">CLDirectConvolutionLayer::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>));</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">ConvolutionMethod::GEMM</a>:</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="comment">// Validate gemm-based convolution layer</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_convolution_layer.xhtml#a3113fd3147c1bbc06b3f9890063c87c7">CLGEMMConvolutionLayer::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">weights_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">dilation</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">num_groups</a>));</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  }</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">ConvolutionMethod::FFT</a>:</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="comment">// Validate FFT-based convolution layer</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_f_f_t_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">CLFFTConvolutionLayer::validate</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">nullptr</span>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>));</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Not supported."</span>);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> }</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#l00261">Error.h:261</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ad3fd4136244e42ad89b01c02b904336d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ad3fd4136244e42ad89b01c02b904336d">arm_compute::test::validation::dilation</a></div><div class="ttdeci">dilation</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">ConvolutionLayer.cpp:175</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler & get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler.cpp:41</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7cb842ebfe255726066039853a4322f0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">arm_compute::test::validation::weights_info</a></div><div class="ttdeci">weights_info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00196">BatchNormalizationLayer.cpp:196</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a27561688e2fc60176608ef725a4ecb30"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a27561688e2fc60176608ef725a4ecb30">arm_compute::CLScheduler::target</a></div><div class="ttdeci">GPUTarget target() const</div><div class="ttdoc">Get the target GPU.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8h_source.xhtml#l00112">CLScheduler.h:112</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00599">Winograd.cpp:599</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00193">Error.h:193</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_convolution_layer_xhtml_a3113fd3147c1bbc06b3f9890063c87c7"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_convolution_layer.xhtml#a3113fd3147c1bbc06b3f9890063c87c7">arm_compute::CLGEMMConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info=WeightsInfo(), const Size2D &dilation=Size2D(1U, 1U), const ActivationLayerInfo &act_info=ActivationLayerInfo(), unsigned int num_groups=1)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLGEMMConvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_convolution_layer_8cpp_source.xhtml#l00373">CLGEMMConvolutionLayer.cpp:373</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_direct_convolution_layer_xhtml_ac89fb11a78baf66222f50cd5ee725ebd"><div class="ttname"><a href="classarm__compute_1_1_c_l_direct_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">arm_compute::CLDirectConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDirectConvolutionLayer...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_direct_convolution_layer_8cpp_source.xhtml#l00068">CLDirectConvolutionLayer.cpp:68</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">arm_compute::ConvolutionMethod::DIRECT</a></div><div class="ttdoc">Direct convolution.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a2270b3e1d20651d2d8341c858c890830"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a2270b3e1d20651d2d8341c858c890830">arm_compute::test::validation::num_groups</a></div><div class="ttdeci">const unsigned int num_groups</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00148">Im2Col.cpp:148</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a86084036bd3851575ef871ad5bf079a7"><div class="ttname"><a href="_error_8h.xhtml#a86084036bd3851575ef871ad5bf079a7">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MSG(cond,...)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00214">Error.h:214</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_winograd_convolution_layer_xhtml_a1c5a3dc6ea10d1f68d76064b82b8b5c2"><div class="ttname"><a href="classarm__compute_1_1_c_l_winograd_convolution_layer.xhtml#a1c5a3dc6ea10d1f68d76064b82b8b5c2">arm_compute::CLWinogradConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo(), bool enable_fast_math=false)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLWinogradConvolutionLay...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_winograd_convolution_layer_8cpp_source.xhtml#l00149">CLWinogradConvolutionLayer.cpp:149</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">arm_compute::ConvolutionMethod::WINOGRAD</a></div><div class="ttdoc">Convolution using Winograd.</div></div> |
| <div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">arm_compute::GPUTarget</a></div><div class="ttdeci">GPUTarget</div><div class="ttdoc">Available GPU Targets.</div><div class="ttdef"><b>Definition:</b> <a href="_g_p_u_target_8h_source.xhtml#l00034">GPUTarget.h:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_f_f_t_convolution_layer_xhtml_ac89fb11a78baf66222f50cd5ee725ebd"><div class="ttname"><a href="classarm__compute_1_1_c_l_f_f_t_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">arm_compute::CLFFTConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLFFTConvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_f_f_t_convolution_layer_8cpp_source.xhtml#l00253">CLFFTConvolutionLayer.cpp:253</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_convolution_layer_xhtml_a52d5a4b1c55ce0198a793d5ebe5eb714"><div class="ttname"><a href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a52d5a4b1c55ce0198a793d5ebe5eb714">arm_compute::CLConvolutionLayer::get_convolution_method</a></div><div class="ttdeci">static ConvolutionMethod get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, const ActivationLayerInfo &act_info, const GPUTarget gpu_target, const Size2D &dilation=Size2D(1U, 1U), bool enable_fast_math=false)</div><div class="ttdoc">Static function to check if given info will return the convolution called by CLConvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_convolution_layer_8cpp_source.xhtml#l00135">CLConvolutionLayer.cpp:135</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">arm_compute::ConvolutionMethod::FFT</a></div><div class="ttdoc">Convolution using FFT.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">ConvolutionLayer.cpp:180</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3"><div class="ttname"><a href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">arm_compute::ConvolutionMethod::GEMM</a></div><div class="ttdoc">Convolution using GEMM.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a367b5090ab432bc7de2c32369e087ab1"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">arm_compute::ITensorInfo::data_layout</a></div><div class="ttdeci">virtual DataLayout data_layout() const =0</div><div class="ttdoc">Get the data layout of the tensor.</div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00175">arm_compute::test::validation::act_info</a>, <a class="el" href="_error_8h_source.xhtml#l00261">ARM_COMPUTE_ERROR</a>, <a class="el" href="_error_8h_source.xhtml#l00214">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>, <a class="el" href="_validate_8h_source.xhtml#l00163">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00193">ARM_COMPUTE_RETURN_ON_ERROR</a>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00599">arm_compute::test::validation::conv_info</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">ITensorInfo::data_layout()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::dilation</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da4c5d06b02c97731aaa976179c62dcf76">arm_compute::DIRECT</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da86de502ad3fe05ceedaba87164d54d28">arm_compute::FFT</a>, <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da5174aac3927faa9ee34befb7fc87a9e3">arm_compute::GEMM</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</a>, <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00135">CLConvolutionLayer::get_convolution_method()</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::NCHW</a>, <a class="el" href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00148">arm_compute::test::validation::num_groups</a>, <a class="el" href="_c_l_scheduler_8h_source.xhtml#l00112">CLScheduler::target()</a>, <a class="el" href="_c_l_direct_convolution_layer_8cpp_source.xhtml#l00068">CLDirectConvolutionLayer::validate()</a>, <a class="el" href="_c_l_winograd_convolution_layer_8cpp_source.xhtml#l00149">CLWinogradConvolutionLayer::validate()</a>, <a class="el" href="_c_l_f_f_t_convolution_layer_8cpp_source.xhtml#l00253">CLFFTConvolutionLayer::validate()</a>, <a class="el" href="_c_l_g_e_m_m_convolution_layer_8cpp_source.xhtml#l00373">CLGEMMConvolutionLayer::validate()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">arm_compute::test::validation::weights</a>, <a class="el" href="validation_2_c_l_2_batch_normalization_layer_8cpp_source.xhtml#l00196">arm_compute::test::validation::weights_info</a>, and <a class="el" href="namespacearm__compute.xhtml#a683661ae75dcb7aef16b9c9bde31517da9d024a5762b3a992dec7eb3c49d17ae8">arm_compute::WINOGRAD</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml#l00045">CLConvolutionLayer::configure()</a>, and <a class="el" href="_c_l_direct_deconvolution_layer_8cpp_source.xhtml#l00052">CLDirectDeconvolutionLayer::validate()</a>.</p> |
| |
| </div> |
| </div> |
| <hr/>The documentation for this class was generated from the following files:<ul> |
| <li>arm_compute/runtime/CL/functions/<a class="el" href="_c_l_convolution_layer_8h_source.xhtml">CLConvolutionLayer.h</a></li> |
| <li>src/runtime/CL/functions/<a class="el" href="_c_l_convolution_layer_8cpp_source.xhtml">CLConvolutionLayer.cpp</a></li> |
| </ul> |
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