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| <a href="#pub-methods">Public Member Functions</a> | |
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| <div class="title">CLGEMMDeconvolutionLayer Class Reference</div> </div> |
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| |
| <p>Function to run the deconvolution layer through a call to GEMM. |
| <a href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8h_source.xhtml">CLGEMMDeconvolutionLayer.h</a>></code></p> |
| <div class="dynheader"> |
| Collaboration diagram for CLGEMMDeconvolutionLayer:</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:ad861c83138c823ed91ed39c47a2be0e4"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#ad861c83138c823ed91ed39c47a2be0e4">CLGEMMDeconvolutionLayer</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:ad861c83138c823ed91ed39c47a2be0e4"><td class="mdescLeft"> </td><td class="mdescRight">Constructor. <a href="#ad861c83138c823ed91ed39c47a2be0e4">More...</a><br /></td></tr> |
| <tr class="separator:ad861c83138c823ed91ed39c47a2be0e4"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a803107fcf0dbe12b4838adf40f15fe6a"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#a803107fcf0dbe12b4838adf40f15fe6a">CLGEMMDeconvolutionLayer</a> (const <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> &)=delete</td></tr> |
| <tr class="memdesc:a803107fcf0dbe12b4838adf40f15fe6a"><td class="mdescLeft"> </td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#a803107fcf0dbe12b4838adf40f15fe6a">More...</a><br /></td></tr> |
| <tr class="separator:a803107fcf0dbe12b4838adf40f15fe6a"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad1250350075f372833fb754c6ff400b0"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#ad1250350075f372833fb754c6ff400b0">CLGEMMDeconvolutionLayer</a> (<a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> &&)=default</td></tr> |
| <tr class="memdesc:ad1250350075f372833fb754c6ff400b0"><td class="mdescLeft"> </td><td class="mdescRight">Default move constructor. <a href="#ad1250350075f372833fb754c6ff400b0">More...</a><br /></td></tr> |
| <tr class="separator:ad1250350075f372833fb754c6ff400b0"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad2d2e5e6f3b554c8a1375dd76d954d5c"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#ad2d2e5e6f3b554c8a1375dd76d954d5c">operator=</a> (const <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> &)=delete</td></tr> |
| <tr class="memdesc:ad2d2e5e6f3b554c8a1375dd76d954d5c"><td class="mdescLeft"> </td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#ad2d2e5e6f3b554c8a1375dd76d954d5c">More...</a><br /></td></tr> |
| <tr class="separator:ad2d2e5e6f3b554c8a1375dd76d954d5c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a0e6734cb19a2b0fe4ac6b180b296c9ca"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#a0e6734cb19a2b0fe4ac6b180b296c9ca">operator=</a> (<a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> &&)=default</td></tr> |
| <tr class="memdesc:a0e6734cb19a2b0fe4ac6b180b296c9ca"><td class="mdescLeft"> </td><td class="mdescRight">Default move assignment operator. <a href="#a0e6734cb19a2b0fe4ac6b180b296c9ca">More...</a><br /></td></tr> |
| <tr class="separator:a0e6734cb19a2b0fe4ac6b180b296c9ca"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:abe32f29395208b635dd4d063cbb8e832"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#abe32f29395208b635dd4d063cbb8e832">configure</a> (const <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> *bias, <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> &deconv_info)</td></tr> |
| <tr class="memdesc:abe32f29395208b635dd4d063cbb8e832"><td class="mdescLeft"> </td><td class="mdescRight">Set the input, weights, biases and output tensors. <a href="#abe32f29395208b635dd4d063cbb8e832">More...</a><br /></td></tr> |
| <tr class="separator:abe32f29395208b635dd4d063cbb8e832"><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_g_e_m_m_deconvolution_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_g_e_m_m_deconvolution_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:a97f50b89cbcb5b3a3d1c45a1a71cb4ed"><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_g_e_m_m_deconvolution_layer.xhtml#a97f50b89cbcb5b3a3d1c45a1a71cb4ed">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> *bias, 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> &deconv_info)</td></tr> |
| <tr class="memdesc:a97f50b89cbcb5b3a3d1c45a1a71cb4ed"><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_deconvolution_layer.xhtml">CLDeconvolutionLayer</a>. <a href="#a97f50b89cbcb5b3a3d1c45a1a71cb4ed">More...</a><br /></td></tr> |
| <tr class="separator:a97f50b89cbcb5b3a3d1c45a1a71cb4ed"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>Function to run the deconvolution layer through a call to GEMM. </p> |
| <p>Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perform a 1x1 convolution pass. Input stride defines how many zeroes we should put between each element of the input, pad is the amount of padding and finally a is a user specified value where a < stride - 1, that increases the padding top and right of the input image.</p> |
| <p>The relation between input to output is as follows: </p><p class="formulaDsp"> |
| \[ width\_output = (width\_input - 1) \cdot stride\_x - 2 \cdot padding\_x + kernel\_x \] |
| </p> |
| <p class="formulaDsp"> |
| \[ height\_output = (height\_input - 1) \cdot stride\_y - 2 \cdot padding\_y + kernel\_y \] |
| </p> |
| <p>where: width_input is the size of the first input dimension. height_input is the size of the second input dimension. width_output is the size of the first output dimension. height_output is the size of the second output dimension. kernel_x and kernel_y are the convolution sizes in x and y. stride_x and stride_y is the input stride of the first and second dimension.</p> |
| <p>The weights used by Deconvolution are supposed to be the same as the ones used for Convolution.</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_lowp_matrix_multiply_core.xhtml">CLGEMMLowpMatrixMultiplyCore</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_permute.xhtml">CLPermute</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_permute.xhtml">CLPermute</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_reshape_layer.xhtml">CLReshapeLayer</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_transpose.xhtml">CLTranspose</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_deconvolution_reshape_output_kernel.xhtml">CLDeconvolutionReshapeOutputKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_slice.xhtml">CLSlice</a> </li> |
| </ol> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8h_source.xhtml#l00078">78</a> of file <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8h_source.xhtml">CLGEMMDeconvolutionLayer.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a id="ad861c83138c823ed91ed39c47a2be0e4"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad861c83138c823ed91ed39c47a2be0e4">◆ </a></span>CLGEMMDeconvolutionLayer() <span class="overload">[1/3]</span></h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</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>Constructor. </p> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00067">67</a> of file <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml">CLGEMMDeconvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  : _memory_group(std::move(memory_manager)),</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  _mm_gemm(),</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  _mm_gemmlowp(),</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  _gemmlowp_output_stage(),</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  _permute_input_to_nhwc(),</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  _permute_weights_to_nhwc(),</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  _reshape_weights(),</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  _transpose_weights(),</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  _deconv_reshape(),</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  _slice_gemm(),</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  _gemmlowp_final(),</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  _reshaped_weights(),</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  _reshaped_weights_t(),</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  _permuted_input(),</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  _permuted_weights(),</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  _gemm_output(),</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  _slice_gemm_input(),</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  _original_weights(),</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  _is_prepared(<span class="keyword">false</span>),</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  _padded_input(<span class="keyword">false</span>),</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  _is_nchw(<span class="keyword">false</span>),</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  _is_quantized(<span class="keyword">false</span>)</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> {</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> }</div></div><!-- fragment --> |
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| <h2 class="memtitle"><span class="permalink"><a href="#a803107fcf0dbe12b4838adf40f15fe6a">◆ </a></span>CLGEMMDeconvolutionLayer() <span class="overload">[2/3]</span></h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> & </td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
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| <span class="mlabels"><span class="mlabel">delete</span></span> </td> |
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| <p>Prevent instances of this class from being copied (As this class contains pointers) </p> |
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| <a id="ad1250350075f372833fb754c6ff400b0"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad1250350075f372833fb754c6ff400b0">◆ </a></span>CLGEMMDeconvolutionLayer() <span class="overload">[3/3]</span></h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> && </td> |
| <td class="paramname"></td><td>)</td> |
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| <span class="mlabels"><span class="mlabel">default</span></span> </td> |
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| <p>Default move constructor. </p> |
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| <h2 class="groupheader">Member Function Documentation</h2> |
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| <h2 class="memtitle"><span class="permalink"><a href="#abe32f29395208b635dd4d063cbb8e832">◆ </a></span>configure()</h2> |
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| <td class="memname">void configure </td> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td> |
| <td class="paramname"><em>input</em>, </td> |
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| <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> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td> |
| <td class="paramname"><em>bias</em>, </td> |
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| <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> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> & </td> |
| <td class="paramname"><em>deconv_info</em> </td> |
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| <p>Set the input, weights, biases and output tensors. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">input</td><td>Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layout supported: NHWC </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as <code>input</code>. Data layout supported: same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>(Optional) The biases have one dimension. Data type supported: Same as <code>input</code>. Data layout supported: same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Output tensor. The output has the same number of dimensions as the <code>input</code>. Data layout supported: same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">deconv_info</td><td>Contains padding and policies to be used in the deconvolution, this is described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>. This function supports only stride_x = weights.width && stride_y = weights.height. Moreover, padding is not supported. </td></tr> |
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| <p class="definition">Definition at line <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00186">186</a> of file <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml">CLGEMMDeconvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> {</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</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="l00189"></a><span class="lineno"> 189</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_g_e_m_m_deconvolution_layer.xhtml#a97f50b89cbcb5b3a3d1c45a1a71cb4ed">CLGEMMDeconvolutionLayer::validate</a>(input->info(),</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <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>(),</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a> != <span class="keyword">nullptr</span> ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>() : <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  output->info(),</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  deconv_info));</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>  _original_weights = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  _padded_input = deconv_info.pad_bottom() > 0 || deconv_info.pad_left() > 0 || deconv_info.pad_right() > 0 || deconv_info.pad_top() > 0;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  _is_nchw = input->info()->data_layout() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  _is_quantized = <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input->info()->data_type());</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keyword">const</span> ICLTensor *input_to_use = input;</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keyword">const</span> ICLTensor *weights_to_use = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</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="comment">// If the data layout is NCHW, transform everything in NHWC. Another alternative could be to</span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="comment">// do an outer product in NCHW and then an accumulation through a reduction. This would have two</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="comment">// drawbacks: first, the outer product is less efficient than a full GEMM. Second, the reduction</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="comment">// might be slower than GEMM.</span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keywordflow">if</span>(_is_nchw)</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  {</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_permuted_input);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  _permute_input_to_nhwc.<a class="code" href="classarm__compute_1_1_c_l_permute.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">configure</a>(input, &_permuted_input, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</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>));</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  _permute_weights_to_nhwc.<a class="code" href="classarm__compute_1_1_c_l_permute.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">configure</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, &_permuted_weights, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</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>));</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> </div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  input_to_use = &_permuted_input;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  weights_to_use = &_permuted_weights;</div><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> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="comment">// Reshape the input weights. The weights will be reshaped only once during the call to prepare()</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  _reshaped_weights.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(TensorInfo(TensorShape(weights_to_use->info()->dimension(0),</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  weights_to_use->info()->dimension(1) * weights_to_use->info()->dimension(2) * weights_to_use->info()->dimension(3)),</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  1,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  input->info()->data_type(), <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>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>()));</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  _reshape_weights.<a class="code" href="classarm__compute_1_1_c_l_reshape_layer.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(weights_to_use, &_reshaped_weights);</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  _transpose_weights.<a class="code" href="classarm__compute_1_1_c_l_transpose.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(&_reshaped_weights, &_reshaped_weights_t);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</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->info()->data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  GEMMInfo gemm_info(<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>, input->info()->dimension(idx_h), <span class="keyword">true</span>);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="comment">// Configure output stage for asymmetric quantized types</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="keywordflow">if</span>(_is_quantized)</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  {</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  _mm_gemmlowp.<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml#a0ae54876c8c3394f2e207f6b884f2b58">configure</a>(input_to_use, &_reshaped_weights_t, <span class="keyword">nullptr</span>, &_gemm_output, gemm_info);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  }</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  {</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  _mm_gemm.<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml#a34e7b882208ff6720bad2e4f2c7565c5">configure</a>(input_to_use, &_reshaped_weights_t, <span class="keyword">nullptr</span>, &_gemm_output, 1.f, 0.0f, gemm_info);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  }</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <span class="keywordflow">if</span>(_is_nchw)</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  {</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  _permuted_input.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  }</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  ICLTensor *deconv_reshape_output = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  ICLTensor *slice_output = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  ICLTensor *output_stage_output = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">if</span>(_padded_input && _is_quantized)</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  {</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_slice_gemm_input);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_gemmlowp_final);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  deconv_reshape_output = &_gemmlowp_final;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  output_stage_output = &_slice_gemm_input;</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  slice_output = output;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  }</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(_padded_input)</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  {</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_slice_gemm_input);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  deconv_reshape_output = &_slice_gemm_input;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  slice_output = output;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  }</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(_is_quantized)</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  {</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_gemmlowp_final);</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  deconv_reshape_output = &_gemmlowp_final;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  output_stage_output = output;</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  }</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  {</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  deconv_reshape_output = output;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  }</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="comment">// Configure a Col2Im call to reshape the output of GEMM</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  _deconv_reshape.<a class="code" href="classarm__compute_1_1_c_l_deconvolution_reshape_output_kernel.xhtml#aac0cf3ea7a56fc937afe4af852994d26">configure</a>(&_gemm_output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>, deconv_reshape_output, input-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">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>(), deconv_info);</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  _gemm_output.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> </div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keywordflow">if</span>(_is_quantized)</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  {</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keyword">const</span> UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform();</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keyword">const</span> UniformQuantizationInfo wq_info = <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>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">uniform</a>();</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keyword">const</span> UniformQuantizationInfo oq_info = _gemmlowp_final.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>().<a class="code" href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">uniform</a>();</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keywordtype">float</span> multiplier = iq_info.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a> * wq_info.scale / oq_info.scale;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordtype">int</span> output_multiplier(0);</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordtype">int</span> output_shift(0);</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <a class="code" href="namespacearm__compute_1_1quantization.xhtml#a22032f9cf47deae265eafb65ff55b594">quantization::calculate_quantized_multiplier_less_than_one</a>(multiplier, &output_multiplier, &output_shift);</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  _gemmlowp_output_stage.<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml#a15da37f661fdcd81c1f25c5d6bdc6abd">configure</a>(&_gemmlowp_final, <span class="keyword">nullptr</span>, output_stage_output, output_multiplier, output_shift, oq_info.offset);</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  _gemmlowp_final.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  }</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="comment">// If the input was padded, the output needs to be sliced.</span></div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordflow">if</span>(_padded_input)</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  {</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keyword">const</span> <span class="keyword">auto</span> start_end = compute_start_end_slice_coordinates(*deconv_reshape_output->info(), deconv_info, _is_nchw);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  _slice_gemm.<a class="code" href="classarm__compute_1_1_c_l_slice.xhtml#ae883a7cb96f6111b0e8bf3a64842c438">configure</a>(&_slice_gemm_input, slice_output, start_end.first, start_end.second);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  _slice_gemm_input.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  }</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> }</div><div class="ttc" id="namespacearm__compute_1_1quantization_xhtml_a22032f9cf47deae265eafb65ff55b594"><div class="ttname"><a href="namespacearm__compute_1_1quantization.xhtml#a22032f9cf47deae265eafb65ff55b594">arm_compute::quantization::calculate_quantized_multiplier_less_than_one</a></div><div class="ttdeci">arm_compute::Status calculate_quantized_multiplier_less_than_one(float multiplier, int *quant_multiplier, int *right_shift)</div><div class="ttdoc">Calculate quantized representation of multiplier with value less than one.</div><div class="ttdef"><b>Definition:</b> <a href="_asymm_helpers_8cpp_source.xhtml#l00035">AsymmHelpers.cpp:35</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="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer_xhtml_a97f50b89cbcb5b3a3d1c45a1a71cb4ed"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#a97f50b89cbcb5b3a3d1c45a1a71cb4ed">arm_compute::CLGEMMDeconvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &deconv_info)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDeconvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00093">CLGEMMDeconvolutionLayer.cpp:93</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_ac74736e3863207232a23b7181c1d0f44"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ac74736e3863207232a23b7181c1d0f44">arm_compute::TensorInfo::quantization_info</a></div><div class="ttdeci">QuantizationInfo quantization_info() const override</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00293">TensorInfo.h:293</a></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="namespacearm__compute_xhtml_a33e65be485104e2e9e69fca551d6f492"><div class="ttname"><a href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">arm_compute::PermutationVector</a></div><div class="ttdeci">Strides PermutationVector</div><div class="ttdoc">Permutation vector.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00047">Types.h:47</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_xhtml_a15da37f661fdcd81c1f25c5d6bdc6abd"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml#a15da37f661fdcd81c1f25c5d6bdc6abd">arm_compute::CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, int min=0, int max=0)</div><div class="ttdoc">Initialise the kernel's inputs, output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_output_stage_8cpp_source.xhtml#l00047">CLGEMMLowpOutputStage.cpp:47</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a4083de30daebd6bdee6b35d9c8262108"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">arm_compute::CLTensor::allocator</a></div><div class="ttdeci">CLTensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor.cpp:55</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_g_e_m_m_lowp_matrix_multiply_core_xhtml_a0ae54876c8c3394f2e207f6b884f2b58"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml#a0ae54876c8c3394f2e207f6b884f2b58">arm_compute::CLGEMMLowpMatrixMultiplyCore::configure</a></div><div class="ttdeci">void configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, const GEMMInfo &gemm_info=GEMMInfo())</div><div class="ttdoc">Initialise the kernel's inputs, output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00075">CLGEMMLowpMatrixMultiplyCore.cpp:75</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml_a1d28dec57cce925ad92342891bd71e7c"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">arm_compute::UniformQuantizationInfo::scale</a></div><div class="ttdeci">float scale</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00061">QuantizationInfo.h:61</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_deconvolution_reshape_output_kernel_xhtml_aac0cf3ea7a56fc937afe4af852994d26"><div class="ttname"><a href="classarm__compute_1_1_c_l_deconvolution_reshape_output_kernel.xhtml#aac0cf3ea7a56fc937afe4af852994d26">arm_compute::CLDeconvolutionReshapeOutputKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const ITensorInfo *input_info, const ITensorInfo *weights_info, const PadStrideInfo &deconv_info)</div><div class="ttdoc">Initialise the kernel's source and destination.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_deconvolution_reshape_output_kernel_8cpp_source.xhtml#l00120">CLDeconvolutionReshapeOutputKernel.cpp:120</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_allocator_xhtml_af36143939a43fa124312e395975091ed"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">arm_compute::ITensorAllocator::init</a></div><div class="ttdeci">void init(const TensorInfo &input, size_t alignment=0)</div><div class="ttdoc">Initialize a tensor based on the passed TensorInfo.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator.cpp:38</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_memory_group_base_xhtml_ac1f67376afb7822f262a0174ef4a3104"><div class="ttname"><a href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">arm_compute::MemoryGroupBase::manage</a></div><div class="ttdeci">void manage(TensorType *obj)</div><div class="ttdoc">Sets a object to be managed by the given memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase.h:102</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_quantization_info_xhtml_a706fc156bcd4c45441bcaad05884b57d"><div class="ttname"><a href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">arm_compute::QuantizationInfo::uniform</a></div><div class="ttdeci">UniformQuantizationInfo uniform() const</div><div class="ttdoc">Return per layer quantization info.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00134">QuantizationInfo.h:134</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a3a77be8aebd8e00522b32061d46ccdbd"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">arm_compute::test::validation::bias</a></div><div class="ttdeci">CLTensor bias</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00181">ConvolutionLayer.cpp:181</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="classarm__compute_1_1_c_l_slice_xhtml_ae883a7cb96f6111b0e8bf3a64842c438"><div class="ttname"><a href="classarm__compute_1_1_c_l_slice.xhtml#ae883a7cb96f6111b0e8bf3a64842c438">arm_compute::CLSlice::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, const Coordinates &starts, const Coordinates &ends)</div><div class="ttdoc">Configure kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_slice_8cpp_source.xhtml#l00034">CLSlice.cpp:34</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">Utils.h:1030</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::CLTensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of OpenCL memory.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator.cpp:119</a></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_g_e_m_m_xhtml_a34e7b882208ff6720bad2e4f2c7565c5"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m.xhtml#a34e7b882208ff6720bad2e4f2c7565c5">arm_compute::CLGEMM::configure</a></div><div class="ttdeci">void configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *c, ICLTensor *output, float alpha, float beta, const GEMMInfo &gemm_info=GEMMInfo())</div><div class="ttdoc">Initialise the kernel's inputs and output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_8cpp_source.xhtml#l00470">CLGEMM.cpp:470</a></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="classarm__compute_1_1_c_l_permute_xhtml_af1f5e1b7e8bbf0768c406be880387a0d"><div class="ttname"><a href="classarm__compute_1_1_c_l_permute.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">arm_compute::CLPermute::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, const PermutationVector &perm)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_permute_8cpp_source.xhtml#l00033">CLPermute.cpp:33</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_reshape_layer_xhtml_a074e10cfb217e657b9e81adeca2abc68"><div class="ttname"><a href="classarm__compute_1_1_c_l_reshape_layer.xhtml#a074e10cfb217e657b9e81adeca2abc68">arm_compute::CLReshapeLayer::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output)</div><div class="ttdoc">Initialise the kernel's inputs and outputs.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_reshape_layer_8cpp_source.xhtml#l00033">CLReshapeLayer.cpp:33</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_transpose_xhtml_a074e10cfb217e657b9e81adeca2abc68"><div class="ttname"><a href="classarm__compute_1_1_c_l_transpose.xhtml#a074e10cfb217e657b9e81adeca2abc68">arm_compute::CLTranspose::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output)</div><div class="ttdoc">Initialise the kernel's inputs and output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_transpose_8cpp_source.xhtml#l00033">CLTranspose.cpp:33</a></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><!-- fragment --> |
| <p class="reference">References <a class="el" href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator::allocate()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor::allocator()</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="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00181">arm_compute::test::validation::bias</a>, <a class="el" href="_asymm_helpers_8cpp_source.xhtml#l00035">arm_compute::quantization::calculate_quantized_multiplier_less_than_one()</a>, <a class="el" href="_c_l_reshape_layer_8cpp_source.xhtml#l00033">CLReshapeLayer::configure()</a>, <a class="el" href="_c_l_permute_8cpp_source.xhtml#l00033">CLPermute::configure()</a>, <a class="el" href="_c_l_transpose_8cpp_source.xhtml#l00033">CLTranspose::configure()</a>, <a class="el" href="_c_l_slice_8cpp_source.xhtml#l00034">CLSlice::configure()</a>, <a class="el" href="_c_l_deconvolution_reshape_output_kernel_8cpp_source.xhtml#l00120">CLDeconvolutionReshapeOutputKernel::configure()</a>, <a class="el" href="_c_l_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00075">CLGEMMLowpMatrixMultiplyCore::configure()</a>, <a class="el" href="_c_l_g_e_m_m_8cpp_source.xhtml#l00470">CLGEMM::configure()</a>, <a class="el" href="_c_l_g_e_m_m_lowp_output_stage_8cpp_source.xhtml#l00047">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">ITensorInfo::data_layout()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">ITensorInfo::data_type()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</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="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="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator::init()</a>, <a class="el" href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">arm_compute::is_data_type_quantized_asymmetric()</a>, <a class="el" href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase< TensorType >::manage()</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::NCHW</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00062">UniformQuantizationInfo::offset</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00765">PadStrideInfo::pad_bottom()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00750">PadStrideInfo::pad_left()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00755">PadStrideInfo::pad_right()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00760">PadStrideInfo::pad_top()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">ITensorInfo::quantization_info()</a>, <a class="el" href="_tensor_info_8h_source.xhtml#l00293">TensorInfo::quantization_info()</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00061">UniformQuantizationInfo::scale</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::U</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00134">QuantizationInfo::uniform()</a>, <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00093">CLGEMMDeconvolutionLayer::validate()</a>, and <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">arm_compute::test::validation::weights</a>.</p> |
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| <a id="ad2d2e5e6f3b554c8a1375dd76d954d5c"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad2d2e5e6f3b554c8a1375dd76d954d5c">◆ </a></span>operator=() <span class="overload">[1/2]</span></h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a>& operator= </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> & </td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
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| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">delete</span></span> </td> |
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| <p>Prevent instances of this class from being copied (As this class contains pointers) </p> |
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| <a id="a0e6734cb19a2b0fe4ac6b180b296c9ca"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a0e6734cb19a2b0fe4ac6b180b296c9ca">◆ </a></span>operator=() <span class="overload">[2/2]</span></h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a>& operator= </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml">CLGEMMDeconvolutionLayer</a> && </td> |
| <td class="paramname"></td><td>)</td> |
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| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">default</span></span> </td> |
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| <p>Default move assignment operator. </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> |
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| <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_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00334">334</a> of file <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml">CLGEMMDeconvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">if</span>(!_is_prepared)</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  {</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!_original_weights-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a209ea2ddfdfa80703799c92da8beb643">is_used</a>());</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">if</span>(_is_nchw)</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  {</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  _permuted_weights.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  _permute_weights_to_nhwc.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  }</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  _reshaped_weights.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  _reshape_weights.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span> </div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordflow">if</span>(_is_nchw)</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  {</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  _permuted_weights.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a1468b0adb6ec3f9d38aa7d60b8a91974">free</a>();</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  }</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> </div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  _reshaped_weights_t.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  _transpose_weights.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="comment">// Prepare gemm</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">if</span>(!_is_quantized)</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  {</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  _mm_gemm.<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>();</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  }</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  {</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  _mm_gemmlowp.<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>();</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  }</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="comment">// Free resources</span></div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keywordflow">if</span>(!_reshaped_weights_t.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a209ea2ddfdfa80703799c92da8beb643">is_used</a>())</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  {</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  _reshaped_weights_t.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a1468b0adb6ec3f9d38aa7d60b8a91974">free</a>();</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  }</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> </div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  _original_weights-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  _is_prepared = <span class="keyword">true</span>;</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  }</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> }</div><div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::CLGEMM::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_g_e_m_m_8cpp_source.xhtml#l00632">CLGEMM.cpp:632</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::CLGEMMLowpMatrixMultiplyCore::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_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00437">CLGEMMLowpMatrixMultiplyCore.cpp:437</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a209ea2ddfdfa80703799c92da8beb643"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a209ea2ddfdfa80703799c92da8beb643">arm_compute::ITensor::is_used</a></div><div class="ttdeci">bool is_used() const</div><div class="ttdoc">Flags if the tensor is used or not.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8cpp_source.xhtml#l00162">ITensor.cpp:162</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="classarm__compute_1_1_c_l_tensor_xhtml_a4083de30daebd6bdee6b35d9c8262108"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">arm_compute::CLTensor::allocator</a></div><div class="ttdeci">CLTensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor.cpp:55</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a9bc00234de9adf8c99a21eb1d7d494c2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">arm_compute::ITensor::mark_as_unused</a></div><div class="ttdeci">void mark_as_unused() const</div><div class="ttdoc">Marks a tensor as unused.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8cpp_source.xhtml#l00167">ITensor.cpp:167</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::ICLSimpleFunction::run</a></div><div class="ttdeci">void run() override final</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction.cpp:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::CLTensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of OpenCL memory.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator.cpp:119</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a1468b0adb6ec3f9d38aa7d60b8a91974"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a1468b0adb6ec3f9d38aa7d60b8a91974">arm_compute::CLTensorAllocator::free</a></div><div class="ttdeci">void free() override</div><div class="ttdoc">Free allocated OpenCL memory.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00152">CLTensorAllocator.cpp:152</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator::allocate()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00337">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_c_l_tensor_allocator_8cpp_source.xhtml#l00152">CLTensorAllocator::free()</a>, <a class="el" href="_i_tensor_8cpp_source.xhtml#l00162">ITensor::is_used()</a>, <a class="el" href="_i_tensor_8cpp_source.xhtml#l00167">ITensor::mark_as_unused()</a>, <a class="el" href="_c_l_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00437">CLGEMMLowpMatrixMultiplyCore::prepare()</a>, <a class="el" href="_c_l_g_e_m_m_8cpp_source.xhtml#l00632">CLGEMM::prepare()</a>, and <a class="el" href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction::run()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00301">CLGEMMDeconvolutionLayer::run()</a>.</p> |
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| </div> |
| </div> |
| <a id="ad1717410afd0be936c6213a63c8005fb"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">◆ </a></span>run()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void run </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td> |
| </tr> |
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| </div><div class="memdoc"> |
| |
| <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_g_e_m_m_deconvolution_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> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00301">301</a> of file <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml">CLGEMMDeconvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> {</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>();</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  MemoryGroupResourceScope scope_mg(_memory_group);</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keywordflow">if</span>(_is_nchw)</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  {</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  _permute_input_to_nhwc.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  }</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keywordflow">if</span>(_is_quantized)</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  {</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  _mm_gemmlowp.<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  }</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  {</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  _mm_gemm.<a class="code" href="classarm__compute_1_1_c_l_g_e_m_m.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  }</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> </div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <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#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_deconv_reshape, <span class="keyword">false</span>);</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> </div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">if</span>(_is_quantized)</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  {</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  _gemmlowp_output_stage.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  }</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> </div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordflow">if</span>(_padded_input)</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  {</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  _slice_gemm.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  }</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> }</div><div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::CLGEMM::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_8cpp_source.xhtml#l00572">CLGEMM.cpp:572</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="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::CLGEMMLowpMatrixMultiplyCore::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00381">CLGEMMLowpMatrixMultiplyCore.cpp:381</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::ICLSimpleFunction::run</a></div><div class="ttdeci">void run() override final</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction.cpp:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_ae1a643e517f50bf0392fb6516dd7cf67"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">arm_compute::CLScheduler::enqueue</a></div><div class="ttdeci">void enqueue(ICLKernel &kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler.cpp:95</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_deconvolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::CLGEMMDeconvolutionLayer::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_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00334">CLGEMMDeconvolutionLayer.cpp:334</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler::enqueue()</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</a>, <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00334">CLGEMMDeconvolutionLayer::prepare()</a>, <a class="el" href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction::run()</a>, <a class="el" href="_c_l_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00381">CLGEMMLowpMatrixMultiplyCore::run()</a>, and <a class="el" href="_c_l_g_e_m_m_8cpp_source.xhtml#l00572">CLGEMM::run()</a>.</p> |
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| <a id="a97f50b89cbcb5b3a3d1c45a1a71cb4ed"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a97f50b89cbcb5b3a3d1c45a1a71cb4ed">◆ </a></span>validate()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
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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> |
| </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>bias</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>deconv_info</em> </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> |
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| </div><div class="memdoc"> |
| |
| <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_deconvolution_layer.xhtml">CLDeconvolutionLayer</a>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layout supported: NHWC </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as <code>input</code>. Data layout supported: same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">bias</td><td>(Optional) The biases have one dimension. Data type supported: Same as <code>input</code>. Data layout supported: same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Output tensor info. The output has the same number of dimensions as the <code>input</code>. Data layout supported: same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">deconv_info</td><td>Contains padding and policies to be used in the deconvolution, this is described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <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_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00093">93</a> of file <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml">CLGEMMDeconvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</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="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <a class="code" href="_validate_8h.xhtml#abdb9168800c70e5e2c4c020a3b905738">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT</a>(input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</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> = input->data_layout();</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> padded_input = deconv_info.pad_bottom() > 0 || deconv_info.pad_left() > 0 || deconv_info.pad_right() > 0 || deconv_info.pad_top() > 0;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> is_nchw = input->data_layout() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> is_quantized = <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input->data_type());</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</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>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</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>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_b = <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>, <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a">DataLayoutDimension::BATCHES</a>);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_w) != deconv_info.stride().first);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_h) != deconv_info.stride().second);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  TensorShape nhwc_weights_shape = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->tensor_shape();</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  TensorShape nhwc_input_shape = input->tensor_shape();</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">if</span>(is_nchw)</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>  <a class="code" href="namespacearm__compute.xhtml#a21c3e11887f3acf9284ca763372c7da0">permute</a>(nhwc_weights_shape, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(2, 0, 1));</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="namespacearm__compute.xhtml#a21c3e11887f3acf9284ca763372c7da0">permute</a>(nhwc_input_shape, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(2, 0, 1));</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  TensorInfo nhwc_input_info = input->clone()->set_is_resizable(<span class="keyword">true</span>).reset_padding().set_tensor_shape(nhwc_input_shape).set_data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  TensorInfo nhwc_weights_info = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->clone()->set_is_resizable(<span class="keyword">true</span>).reset_padding().set_tensor_shape(nhwc_weights_shape).set_data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="classarm__compute_1_1_c_l_permute.xhtml#a97f09e05a72865753ecb1948b38d4843">CLPermute::validate</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, &nhwc_weights_info, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(2, 0, 1));</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <a class="code" href="classarm__compute_1_1_c_l_permute.xhtml#a97f09e05a72865753ecb1948b38d4843">CLPermute::validate</a>(input, &nhwc_input_info, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(2, 0, 1));</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> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">const</span> TensorShape reshaped_shape = TensorShape(nhwc_weights_shape[0], nhwc_weights_shape[1] * nhwc_weights_shape[2] * nhwc_weights_shape[3]);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">const</span> TensorInfo reshaped_info = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->clone()->set_tensor_shape(reshaped_shape).set_data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>).set_is_resizable(<span class="keyword">true</span>);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</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_reshape_layer.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">CLReshapeLayer::validate</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, &reshaped_info));</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>  TensorShape transposed_shape(reshaped_shape[1], reshaped_shape[0]);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keyword">const</span> TensorInfo reshaped_t_info = reshaped_info.clone()->set_is_resizable(<span class="keyword">true</span>).set_tensor_shape(transposed_shape);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</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_transpose.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">CLTranspose::validate</a>(&reshaped_info, &reshaped_t_info));</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  TensorShape gemm_output_shape(<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) * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->dimension(idx_b),</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  input->dimension(idx_w),</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  input->dimension(idx_h),</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  input->dimension(idx_b));</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  TensorInfo gemm_output_info = reshaped_t_info.clone()->set_tensor_shape(gemm_output_shape).set_is_resizable(<span class="keyword">true</span>);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  GEMMInfo gemm_info(<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>, input->dimension(idx_h), <span class="keyword">true</span>);</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="keywordflow">if</span>(is_quantized)</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</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_lowp_matrix_multiply_core.xhtml#a8c3cf2d65afb288e39909171ada19566">CLGEMMLowpMatrixMultiplyCore::validate</a>(&input->clone()->set_tensor_shape(nhwc_input_shape), &reshaped_t_info, <span class="keyword">nullptr</span>, &gemm_output_info.set_data_type(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>),</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  gemm_info));</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  {</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</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.xhtml#a3493ba7d1f2057740ff5931fa00a44ac">CLGEMM::validate</a>(&input->clone()->set_tensor_shape(nhwc_input_shape).set_is_resizable(<span class="keyword">true</span>), &reshaped_t_info, <span class="keyword">nullptr</span>, &gemm_output_info, 1.0f, 0.0f, gemm_info));</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  }</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="keyword">auto</span> out_dims = <a class="code" href="namespacearm__compute.xhtml#a9491bea9e3fcf8ac4a7cf79be64cc765">deconvolution_output_dimensions</a>(input->dimension(idx_w), input->dimension(idx_h), <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="l00155"></a><span class="lineno"> 155</span>  0, 0, deconv_info.stride().first, deconv_info.stride().second);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keyword">const</span> TensorShape deconv_shape = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#ae270329cfe3dbab009b700318e8af8b4">misc::shape_calculator::compute_deconvolution_output_shape</a>(out_dims, *input, *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  TensorInfo col2im_output_info = gemm_output_info.clone()->set_tensor_shape(deconv_shape).set_is_resizable(<span class="keyword">true</span>);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keywordflow">if</span>(padded_input && is_quantized)</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  {</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keyword">const</span> <span class="keyword">auto</span> start_end = compute_start_end_slice_coordinates(col2im_output_info, deconv_info, is_nchw);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</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_deconvolution_reshape_output_kernel.xhtml#accd99a897d85785ef6b2d1583a6137ec">CLDeconvolutionReshapeOutputKernel::validate</a>(&gemm_output_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>, &col2im_output_info, input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, deconv_info));</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</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_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml#aee63e7671cf04d15be2da1b83d90e61b">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate</a>(&col2im_output_info, <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  &col2im_output_info.clone()->set_is_resizable(<span class="keyword">true</span>).set_data_type(<a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>)));</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</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_slice.xhtml#afb48914092f4bb2fdf249fa1e3fcd17c">CLSlice::validate</a>(&col2im_output_info.clone()->set_is_resizable(<span class="keyword">true</span>).set_data_type(<a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>), output, start_end.first, start_end.second));</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>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(padded_input)</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">const</span> <span class="keyword">auto</span> start_end = compute_start_end_slice_coordinates(col2im_output_info, deconv_info, is_nchw);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</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_deconvolution_reshape_output_kernel.xhtml#accd99a897d85785ef6b2d1583a6137ec">CLDeconvolutionReshapeOutputKernel::validate</a>(&gemm_output_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>, &col2im_output_info, input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, deconv_info));</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</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_slice.xhtml#afb48914092f4bb2fdf249fa1e3fcd17c">CLSlice::validate</a>(&col2im_output_info, output, start_end.first, start_end.second));</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  }</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(is_quantized)</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  {</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</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_deconvolution_reshape_output_kernel.xhtml#accd99a897d85785ef6b2d1583a6137ec">CLDeconvolutionReshapeOutputKernel::validate</a>(&gemm_output_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>, &col2im_output_info, input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, deconv_info));</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</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_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml#aee63e7671cf04d15be2da1b83d90e61b">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate</a>(&col2im_output_info, <span class="keyword">nullptr</span>, output));</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  {</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</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_deconvolution_reshape_output_kernel.xhtml#accd99a897d85785ef6b2d1583a6137ec">CLDeconvolutionReshapeOutputKernel::validate</a>(&gemm_output_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">bias</a>, output, input, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, deconv_info));</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> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordflow">return</span> Status{};</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> }</div><div class="ttc" id="classarm__compute_1_1_c_l_reshape_layer_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_c_l_reshape_layer.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::CLReshapeLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLReshapeLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_reshape_layer_8cpp_source.xhtml#l00040">CLReshapeLayer.cpp:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_deconvolution_reshape_output_kernel_xhtml_accd99a897d85785ef6b2d1583a6137ec"><div class="ttname"><a href="classarm__compute_1_1_c_l_deconvolution_reshape_output_kernel.xhtml#accd99a897d85785ef6b2d1583a6137ec">arm_compute::CLDeconvolutionReshapeOutputKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const ITensorInfo *input_info, const ITensorInfo *weights_info, const PadStrideInfo &deconv_info)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDeconvolutionReshapeOu...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_deconvolution_reshape_output_kernel_8cpp_source.xhtml#l00173">CLDeconvolutionReshapeOutputKernel.cpp:173</a></div></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="_validate_8h_xhtml_abdb9168800c70e5e2c4c020a3b905738"><div class="ttname"><a href="_validate_8h.xhtml#abdb9168800c70e5e2c4c020a3b905738">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00494">Validate.h:494</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a8f3ff7da485ff7e75dab07baadf5b4bd"><div class="ttname"><a href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00545">Validate.h:545</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="_validate_8h_xhtml_ae7eed178dac535c6e727061b1f5bc6eb"><div class="ttname"><a href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00791">Validate.h:791</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</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="namespacearm__compute_xhtml_a33e65be485104e2e9e69fca551d6f492"><div class="ttname"><a href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">arm_compute::PermutationVector</a></div><div class="ttdeci">Strides PermutationVector</div><div class="ttdoc">Permutation vector.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00047">Types.h:47</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(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#l00244">Error.h:244</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point_xhtml_aee63e7671cf04d15be2da1b83d90e61b"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_quantize_down_int32_to_uint8_scale_by_fixed_point.xhtml#aee63e7671cf04d15be2da1b83d90e61b">arm_compute::CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min=0, int max=0)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLGEMMLowpQuantizeDownIn...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_output_stage_8cpp_source.xhtml#l00056">CLGEMMLowpOutputStage.cpp:56</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a21c3e11887f3acf9284ca763372c7da0"><div class="ttname"><a href="namespacearm__compute.xhtml#a21c3e11887f3acf9284ca763372c7da0">arm_compute::permute</a></div><div class="ttdeci">void permute(Dimensions< T > &dimensions, const PermutationVector &perm)</div><div class="ttdoc">Permutes given Dimensions according to a permutation vector.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00570">Helpers.h:570</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_ae270329cfe3dbab009b700318e8af8b4"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#ae270329cfe3dbab009b700318e8af8b4">arm_compute::misc::shape_calculator::compute_deconvolution_output_shape</a></div><div class="ttdeci">TensorShape compute_deconvolution_output_shape(const std::pair< unsigned int, unsigned int > &out_dims, const ITensorInfo &input, const ITensorInfo &weights)</div><div class="ttdoc">Calculate the output shape of the deconvolution layer.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00483">ShapeCalculator.h:483</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core_xhtml_a8c3cf2d65afb288e39909171ada19566"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_core.xhtml#a8c3cf2d65afb288e39909171ada19566">arm_compute::CLGEMMLowpMatrixMultiplyCore::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, const GEMMInfo &gemm_info=GEMMInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLGEMMLowpMatrixMultiply...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00237">CLGEMMLowpMatrixMultiplyCore.cpp:237</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_slice_xhtml_afb48914092f4bb2fdf249fa1e3fcd17c"><div class="ttname"><a href="classarm__compute_1_1_c_l_slice.xhtml#afb48914092f4bb2fdf249fa1e3fcd17c">arm_compute::CLSlice::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Coordinates &starts, const Coordinates &ends)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLSlice.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_slice_8cpp_source.xhtml#l00046">CLSlice.cpp:46</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a3a77be8aebd8e00522b32061d46ccdbd"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a3a77be8aebd8e00522b32061d46ccdbd">arm_compute::test::validation::bias</a></div><div class="ttdeci">CLTensor bias</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00181">ConvolutionLayer.cpp:181</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a">arm_compute::DataLayoutDimension::BATCHES</a></div><div class="ttdoc">batches</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_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">Utils.h:1030</a></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_a9491bea9e3fcf8ac4a7cf79be64cc765"><div class="ttname"><a href="namespacearm__compute.xhtml#a9491bea9e3fcf8ac4a7cf79be64cc765">arm_compute::deconvolution_output_dimensions</a></div><div class="ttdeci">std::pair< unsigned int, unsigned int > deconvolution_output_dimensions(unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, unsigned int padx, unsigned int pady, unsigned int stride_x, unsigned int stride_y)</div><div class="ttdoc">Returns expected width and height of the deconvolution's output tensor.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_utils_8cpp_source.xhtml#l00374">Utils.cpp:374</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_transpose_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_c_l_transpose.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::CLTranspose::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLTranspose.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_transpose_8cpp_source.xhtml#l00040">CLTranspose.cpp:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_g_e_m_m_xhtml_a3493ba7d1f2057740ff5931fa00a44ac"><div class="ttname"><a href="classarm__compute_1_1_c_l_g_e_m_m.xhtml#a3493ba7d1f2057740ff5931fa00a44ac">arm_compute::CLGEMM::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info=GEMMInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLGEMM.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_g_e_m_m_8cpp_source.xhtml#l00525">CLGEMM.cpp:525</a></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="classarm__compute_1_1_c_l_permute_xhtml_a97f09e05a72865753ecb1948b38d4843"><div class="ttname"><a href="classarm__compute_1_1_c_l_permute.xhtml#a97f09e05a72865753ecb1948b38d4843">arm_compute::CLPermute::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output, const PermutationVector &perm)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLPermute.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_permute_8cpp_source.xhtml#l00040">CLPermute.cpp:40</a></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_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> |
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| <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00244">ARM_COMPUTE_RETURN_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00791">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>, <a class="el" href="_validate_8h_source.xhtml#l00494">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT</a>, <a class="el" href="_validate_8h_source.xhtml#l00545">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</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="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a">arm_compute::BATCHES</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00181">arm_compute::test::validation::bias</a>, <a class="el" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">ICloneable< T >::clone()</a>, <a class="el" href="src_2core_2_tensor_info_8cpp_source.xhtml#l00306">TensorInfo::clone()</a>, <a class="el" href="_shape_calculator_8h_source.xhtml#l00483">arm_compute::misc::shape_calculator::compute_deconvolution_output_shape()</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="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">ITensorInfo::data_type()</a>, <a class="el" href="src_2core_2_utils_8cpp_source.xhtml#l00374">arm_compute::deconvolution_output_dimensions()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::F16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="_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="arm__compute_2core_2_utils_8h_source.xhtml#l01030">arm_compute::is_data_type_quantized_asymmetric()</a>, <a class="el" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::NCHW</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00765">PadStrideInfo::pad_bottom()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00750">PadStrideInfo::pad_left()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00755">PadStrideInfo::pad_right()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00760">PadStrideInfo::pad_top()</a>, <a class="el" href="arm__compute_2core_2_helpers_8h_source.xhtml#l00570">arm_compute::permute()</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::QASYMM8</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, <a class="el" href="src_2core_2_tensor_info_8cpp_source.xhtml#l00311">TensorInfo::set_data_type()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00724">PadStrideInfo::stride()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">ITensorInfo::tensor_shape()</a>, <a class="el" href="_c_l_reshape_layer_8cpp_source.xhtml#l00040">CLReshapeLayer::validate()</a>, <a class="el" href="_c_l_transpose_8cpp_source.xhtml#l00040">CLTranspose::validate()</a>, <a class="el" href="_c_l_permute_8cpp_source.xhtml#l00040">CLPermute::validate()</a>, <a class="el" href="_c_l_slice_8cpp_source.xhtml#l00046">CLSlice::validate()</a>, <a class="el" href="_c_l_deconvolution_reshape_output_kernel_8cpp_source.xhtml#l00173">CLDeconvolutionReshapeOutputKernel::validate()</a>, <a class="el" href="_c_l_g_e_m_m_lowp_matrix_multiply_core_8cpp_source.xhtml#l00237">CLGEMMLowpMatrixMultiplyCore::validate()</a>, <a class="el" href="_c_l_g_e_m_m_8cpp_source.xhtml#l00525">CLGEMM::validate()</a>, <a class="el" href="_c_l_g_e_m_m_lowp_output_stage_8cpp_source.xhtml#l00056">CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00180">arm_compute::test::validation::weights</a>, and <a class="el" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::WIDTH</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml#l00186">CLGEMMDeconvolutionLayer::configure()</a>, and <a class="el" href="_c_l_deconvolution_layer_8cpp_source.xhtml#l00071">CLDeconvolutionLayer::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_g_e_m_m_deconvolution_layer_8h_source.xhtml">CLGEMMDeconvolutionLayer.h</a></li> |
| <li>src/runtime/CL/functions/<a class="el" href="_c_l_g_e_m_m_deconvolution_layer_8cpp_source.xhtml">CLGEMMDeconvolutionLayer.cpp</a></li> |
| </ul> |
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