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| <a href="_n_e_f_f_t_convolution_layer_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "<a class="code" href="_n_e_f_f_t_convolution_layer_8h.xhtml">arm_compute/runtime/NEON/functions/NEFFTConvolutionLayer.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "<a class="code" href="_i_tensor_8h.xhtml">arm_compute/core/ITensor.h</a>"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_utils_8h.xhtml">arm_compute/core/Utils.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_validate_8h.xhtml">arm_compute/core/Validate.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="fft_8h.xhtml">arm_compute/core/utils/helpers/fft.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_shape_calculator_8h.xhtml">arm_compute/core/utils/misc/ShapeCalculator.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keywordtype">int</span> pad_decomposable(<span class="keywordtype">int</span> N)</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">const</span> <span class="keyword">auto</span> supported_radix = <a class="code" href="classarm__compute_1_1_n_e_f_f_t_radix_stage_kernel.xhtml#a058f31a004475bd61913f02fbf251ddb">NEFFTRadixStageKernel::supported_radix</a>();</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">int</span> pad = 0;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">bool</span> is_decomposed = <span class="keyword">false</span>;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">while</span>(!is_decomposed)</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keyword">const</span> <span class="keyword">auto</span> decomposed_vector = <a class="code" href="namespacearm__compute_1_1helpers_1_1fft.xhtml#a359fcf05844c0a2f1aed6e4386a86aee">arm_compute::helpers::fft::decompose_stages</a>(N++, supported_radix);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  is_decomposed = !decomposed_vector.empty();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordflow">if</span>(!is_decomposed)</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  ++pad;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  }</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  }</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">return</span> pad;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> }</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#abf5b3544ece1ef65b6388a9967d48575"> 55</a></span> <a class="code" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#abf5b3544ece1ef65b6388a9967d48575">NEFFTConvolutionLayer::NEFFTConvolutionLayer</a>(std::shared_ptr<IMemoryManager> memory_manager)</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  : _memory_group(memory_manager),</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  _flip_weights_func(),</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  _permute_input_func(),</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  _permute_output_func(),</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  _permute_weights_func(),</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  _permute_bias_func(),</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  _pad_input_func(),</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  _pad_weights_func(),</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  _transform_input_func(memory_manager),</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  _transform_weights_func(),</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  _itransform_output_func(memory_manager),</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  _prod_func(),</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  _reduce_func(),</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  _extract_output_func(),</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  _bias_add_func(),</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  _activation_layer_func(),</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  _permuted_input(),</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  _permuted_weights(),</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  _permuted_bias(),</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  _permuted_output(),</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  _padded_input(),</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  _padded_weights(),</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  _flip_axis(),</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  _flipped_weights(),</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  _transformed_input(),</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  _transformed_weights(),</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  _input_weights_product(),</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  _output_product(),</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  _output_reduced(),</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  _itransformed_output(),</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  _reshaped_output(),</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  _bias_output(),</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  _original_weights(nullptr),</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  _original_bias(nullptr),</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  _is_activationlayer_enabled(false),</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  _needs_permute(false),</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  _has_bias(false),</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  _is_prepared(false)</div><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> }</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#a064452b83d4907c001b65886876d89c1"> 97</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#a064452b83d4907c001b65886876d89c1">NEFFTConvolutionLayer::configure</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *biases, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</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>  _original_weights = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  _original_bias = biases;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">// Flat if bias addition is required</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  _has_bias = biases != <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="comment">// Get indices for the width and height</span></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_width = <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#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->info()->data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_height = <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#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->info()->data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// Input shape, kernel size and output tile</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> input_dims = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->info()->tensor_shape()[idx_width], <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->info()->tensor_shape()[idx_height]);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> kernel_size = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><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#a269b19ce3f357ac65f41f9951906e38e">tensor_shape</a>()[idx_width], <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#a269b19ce3f357ac65f41f9951906e38e">tensor_shape</a>()[idx_height]);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> pad_valid = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(pad_decomposable(input_dims.x() + kernel_size.x() - 1),</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  pad_decomposable(input_dims.y() + kernel_size.y() - 1));</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="comment">// Tensors to use</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input_to_use = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *weights_to_use = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output_to_use = _has_bias ? &_bias_output : output;</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>  <span class="comment">// Permute bias</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">if</span>(biases != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  _permute_bias_func.<a class="code" href="classarm__compute_1_1_n_e_permute.xhtml#a93c836ab36443b23753d99495761daf7">configure</a>(biases, &_permuted_bias, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  _permuted_bias.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#abb9481fe056b9749f9b4c08db101cc15">set_data_layout</a>(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  }</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="comment">// Permute input if needed</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  _needs_permute = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->info()->data_layout() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_permuted_input);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// Configure the function to transform the input tensor from NHWC -> NCHW</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  _permute_input_func.<a class="code" href="classarm__compute_1_1_n_e_permute.xhtml#a93c836ab36443b23753d99495761daf7">configure</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &_permuted_input, <a class="code" href="namespacearm__compute.xhtml#a33e65be485104e2e9e69fca551d6f492">PermutationVector</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  _permuted_input.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#abb9481fe056b9749f9b4c08db101cc15">set_data_layout</a>(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</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>  <span class="comment">// Configure the function to transform the weights tensor from HWI -> IHW</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  _permute_weights_func.<a class="code" href="classarm__compute_1_1_n_e_permute.xhtml#a93c836ab36443b23753d99495761daf7">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>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 0<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>));</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  _permuted_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#abb9481fe056b9749f9b4c08db101cc15">set_data_layout</a>(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  input_to_use = &_permuted_input;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  weights_to_use = &_permuted_weights;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</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="comment">// Flip weights</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  _flipped_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(weights_to_use-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_is_resizable(<span class="keyword">true</span>).reset_padding());</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  _flip_axis.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(2<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>));</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  _flip_weights_func.<a class="code" href="classarm__compute_1_1_n_e_reverse.xhtml#abaed98d5f33f212b61484a7ef0c53874">configure</a>(weights_to_use, &_flipped_weights, &_flip_axis);</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="comment">// Pad weights</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> padding_w = { { 0, input_dims.x() + pad_valid.x() - 1 }, { 0, input_dims.y() + pad_valid.y() - 1 } };</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  _pad_weights_func.<a class="code" href="classarm__compute_1_1_n_e_pad_layer.xhtml#ac5a4e9c1564aa9892dfe02cdce2f55b3">configure</a>(&_flipped_weights, &_padded_weights, padding_w);</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>  <span class="comment">// Transform weights</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  _transform_weights_func = support::cpp14::make_unique<NEFFT2D>();</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  _transform_weights_func->configure(&_padded_weights, &_transformed_weights, <a class="code" href="structarm__compute_1_1_f_f_t2_d_info.xhtml">FFT2DInfo</a>());</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="comment">// Pad input</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> padding_in = { { 0, kernel_size.x() + pad_valid.x() - 1 }, { 0, kernel_size.y() + pad_valid.y() - 1 } };</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_padded_input);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  _pad_input_func.<a class="code" href="classarm__compute_1_1_n_e_pad_layer.xhtml#ac5a4e9c1564aa9892dfe02cdce2f55b3">configure</a>(input_to_use, &_padded_input, padding_in);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  {</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  _permuted_input.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  }</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="comment">// Transform input</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_transformed_input);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  _transform_input_func.<a class="code" href="classarm__compute_1_1_n_e_f_f_t2_d.xhtml#a4d704db199385825fcc6fa9fbed62924">configure</a>(&_padded_input, &_transformed_input, <a class="code" href="structarm__compute_1_1_f_f_t2_d_info.xhtml">FFT2DInfo</a>());</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  _padded_input.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="comment">// Perform product</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_output_product);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  _prod_func.<a class="code" href="classarm__compute_1_1_n_e_complex_pixel_wise_multiplication.xhtml#a151f73d8df86064f806f8b3256571b0a">configure</a>(&_transformed_input, &_transformed_weights, &_output_product);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  _transformed_input.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="comment">// Perform reduction</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_output_reduced);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  _reduce_func.<a class="code" href="classarm__compute_1_1_n_e_reduction_operation.xhtml#a61cb078b47a1282258de69e3292dc8c8">configure</a>(&_output_product, &_output_reduced, 2, <a class="code" href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45ba6970bdc2201030b9c03fbdcf3973858a">ReductionOperation::SUM</a>);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  _output_product.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// Transform output</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_itransformed_output);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="structarm__compute_1_1_f_f_t2_d_info.xhtml">FFT2DInfo</a> itranform_info;</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  itranform_info.<a class="code" href="structarm__compute_1_1_f_f_t2_d_info.xhtml#a95156d4d94b2a8b7c429e05e546dc2c1">direction</a> = <a class="code" href="namespacearm__compute.xhtml#a86a0c8e195c900a895c249662cfaa564a9f87f02f2da8f99c571b2a1c2a96132b">FFTDirection::Inverse</a>;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  _itransformed_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(_output_reduced.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_is_resizable(<span class="keyword">true</span>).set_num_channels(1).reset_padding());</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  _itransform_output_func.<a class="code" href="classarm__compute_1_1_n_e_f_f_t2_d.xhtml#a4d704db199385825fcc6fa9fbed62924">configure</a>(&_output_reduced, &_itransformed_output, itranform_info);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  _output_reduced.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="comment">// Reshape output</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> reshaped_shape = _itransformed_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  reshaped_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#acb74edf42335de0dca0da5158b704c4b">remove_dimension</a>(2);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  _reshaped_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(_itransformed_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(reshaped_shape));</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="comment">// Extract correct region</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> start_left = kernel_size.x() - <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left() - 1;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> start_top = kernel_size.y() - <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top() - 1;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> end_right = _reshaped_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#aa87f8fc26981b0f3228a78c83b95b802">x</a>() - (kernel_size.x() - <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right() - 1) - pad_valid.x();</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> end_botton = _reshaped_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ac4a1050be02b20b3f791b9a483f3abe2">y</a>() - (kernel_size.y() - <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_bottom() - 1) - pad_valid.y();</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">if</span>(_has_bias)</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  {</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_bias_output);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  }</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  {</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  output_to_use = &_permuted_output;</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_permuted_output);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  }</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  _extract_output_func.<a class="code" href="classarm__compute_1_1_n_e_slice.xhtml#a5c2f378cb28b6c33a699fcf3d24b7ab3">configure</a>(&_reshaped_output, output_to_use, <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(start_left, start_top), <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(end_right, end_botton));</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  _reshaped_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  _itransformed_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</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>  <span class="comment">// Add bias</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keywordflow">if</span>(biases != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  {</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  output_to_use = output;</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">if</span>(_needs_permute)</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>  output_to_use = &_permuted_output;</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_permuted_output);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  }</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output_to_use-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), *_bias_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>());</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  _bias_add_func.<a class="code" href="classarm__compute_1_1_n_e_arithmetic_addition.xhtml#a17b1a968874510a32f0bdcc78e0cb360">configure</a>(&_bias_output, &_permuted_bias, output_to_use, <a class="code" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fae1c8555fcf0ea2bb648a6fd527d658c0">ConvertPolicy::WRAP</a>);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  _bias_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  }</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="comment">// Permute output</span></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">if</span>(_needs_permute)</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  {</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="comment">// Configure the function to transform the convoluted output to ACL's native ordering format NCHW</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  _permuted_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#abb9481fe056b9749f9b4c08db101cc15">set_data_layout</a>(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  _permute_output_func.<a class="code" href="classarm__compute_1_1_n_e_permute.xhtml#a93c836ab36443b23753d99495761daf7">configure</a>(&_permuted_output, output, <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="l00232"></a><span class="lineno"> 232</span> </div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="comment">// Allocate tensors</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  _permuted_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</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>  <span class="comment">// Configure Activation Layer</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  _is_activationlayer_enabled = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>.enabled();</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">if</span>(_is_activationlayer_enabled)</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  {</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  _activation_layer_func.<a class="code" href="classarm__compute_1_1_n_e_activation_layer.xhtml#adfb5ef37594fc9371c4a2b95e3d5e31b">configure</a>(output, <span class="keyword">nullptr</span>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>);</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  }</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>  <span class="comment">// Setup flip axis data</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  _flip_axis.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keyword">auto</span> axis_data = reinterpret_cast<uint32_t *>(_flip_axis.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a24954cca5108a24706441fd99a7fb04c">buffer</a>());</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  axis_data[0] = 0;</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  axis_data[1] = 1;</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> </div><div class="line"><a name="l00252"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd"> 252</a></span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">NEFFTConvolutionLayer::validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *biases, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>,</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>)</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> {</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>);</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> </div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="comment">// Get indices for the width and height</span></div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_width = <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#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_height = <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#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="comment">// Input shape, kernel size and output tile</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> kernel_size = <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->tensor_shape()[idx_width], <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>->tensor_shape()[idx_height]);</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>  <span class="comment">// Strides</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keyword">const</span> <span class="keyword">auto</span> strides = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.stride();</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(strides.first != strides.second && strides.first != 1);</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(kernel_size.x() != kernel_size.y());</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</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#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_left() != (kernel_size.x() / 2) || <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_right() != (kernel_size.x() / 2));</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</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#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_top() != (kernel_size.y() / 2) || <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>.pad_bottom() != (kernel_size.y() / 2));</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="comment">// Validate biases</span></div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordflow">if</span>(biases != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  {</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_channels = <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#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->data_layout(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>);</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, biases);</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</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#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->tensor_shape()[idx_channels] != biases-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#aa87f8fc26981b0f3228a78c83b95b802">x</a>());</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  }</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="comment">// Checks performed when output is configured</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">if</span>((output != <span class="keyword">nullptr</span>) && (output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() != 0))</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  {</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, output);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</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#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->tensor_shape()[idx_height] != output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[idx_height]) || (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->tensor_shape()[idx_width] != output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[idx_width]));</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> </div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="comment">// Validate Activation Layer</span></div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>.enabled())</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  {</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_n_e_activation_layer.xhtml#aa37e2d0b4cd4f835bfa2a2df4a0bdd2c">NEActivationLayer::validate</a>(output, <span class="keyword">nullptr</span>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</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> </div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</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> </div><div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb"> 296</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">NEFFTConvolutionLayer::run</a>()</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> {</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <a class="code" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">prepare</a>();</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="classarm__compute_1_1_memory_group_resource_scope.xhtml">MemoryGroupResourceScope</a> scope_mg(_memory_group);</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> </div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="comment">// Transform input</span></div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">if</span>(_needs_permute)</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>  _permute_input_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</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>  _pad_input_func.<a class="code" href="classarm__compute_1_1_n_e_pad_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  _transform_input_func.<a class="code" href="classarm__compute_1_1_n_e_f_f_t2_d.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="comment">// Perform operations to frequency domain</span></div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  _prod_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  _reduce_func.<a class="code" href="classarm__compute_1_1_n_e_reduction_operation.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> </div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="comment">// Transform output</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  _itransform_output_func.<a class="code" href="classarm__compute_1_1_n_e_f_f_t2_d.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  _reshaped_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a84052cebf66a6126051a166a078253a4">import_memory</a>(_itransformed_output.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a24954cca5108a24706441fd99a7fb04c">buffer</a>());</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  _extract_output_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">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>  <span class="comment">// Add bias</span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordflow">if</span>(_has_bias)</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>  _bias_add_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</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>  <span class="keywordflow">if</span>(_needs_permute)</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>  _permute_output_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  }</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>  <span class="comment">// Run activation layer</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keywordflow">if</span>(_is_activationlayer_enabled)</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  {</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  _activation_layer_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  }</div><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> </div><div class="line"><a name="l00337"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77"> 337</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">NEFFTConvolutionLayer::prepare</a>()</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> {</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">if</span>(!_is_prepared)</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  {</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="comment">// Permute bias to NCHW</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">if</span>(_original_bias != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  {</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  _permuted_bias.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  _permute_bias_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  _original_bias-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  }</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="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *cur_weights = _original_weights;</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>  <span class="comment">// Permute weights</span></div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">if</span>(_needs_permute)</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>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!cur_weights-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a209ea2ddfdfa80703799c92da8beb643">is_used</a>());</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> </div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  _permuted_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  _permute_weights_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  cur_weights-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  cur_weights = &_permuted_weights;</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  }</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="comment">// Flip weights</span></div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  _flipped_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  _flip_weights_func.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  cur_weights-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</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">// Pad weights</span></div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  _padded_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  _pad_weights_func.<a class="code" href="classarm__compute_1_1_n_e_pad_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  _flipped_weights.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  _flipped_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a1468b0adb6ec3f9d38aa7d60b8a91974">free</a>();</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>  <span class="comment">// Transform weights to frequency domain</span></div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  _transformed_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  _transform_weights_func->run();</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  _transform_weights_func.reset();</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  _padded_weights.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a9bc00234de9adf8c99a21eb1d7d494c2">mark_as_unused</a>();</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  _padded_weights.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a1468b0adb6ec3f9d38aa7d60b8a91974">free</a>();</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  _is_prepared = <span class="keyword">true</span>;</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  }</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> }</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> } <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="classarm__compute_1_1_n_e_arithmetic_addition_xhtml_a17b1a968874510a32f0bdcc78e0cb360"><div class="ttname"><a href="classarm__compute_1_1_n_e_arithmetic_addition.xhtml#a17b1a968874510a32f0bdcc78e0cb360">arm_compute::NEArithmeticAddition::configure</a></div><div class="ttdeci">void configure(ITensor *input1, ITensor *input2, ITensor *output, ConvertPolicy policy)</div><div class="ttdoc">Initialise the kernel's inputs, output and conversion policy.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_arithmetic_addition_8cpp_source.xhtml#l00034">NEArithmeticAddition.cpp:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_f_f_t_convolution_layer_xhtml_aa9b93ef660fc3c5b4b19d3fc7b891b77"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#aa9b93ef660fc3c5b4b19d3fc7b891b77">arm_compute::NEFFTConvolutionLayer::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="_n_e_f_f_t_convolution_layer_8cpp_source.xhtml#l00337">NEFFTConvolutionLayer.cpp:337</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_f_f_t2_d_info_xhtml_a95156d4d94b2a8b7c429e05e546dc2c1"><div class="ttname"><a href="structarm__compute_1_1_f_f_t2_d_info.xhtml#a95156d4d94b2a8b7c429e05e546dc2c1">arm_compute::FFT2DInfo::direction</a></div><div class="ttdeci">FFTDirection direction</div><div class="ttdoc">Direction of the FFT.</div><div class="ttdef"><b>Definition:</b> <a href="_function_descriptors_8h_source.xhtml#l00048">FunctionDescriptors.h:48</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_acb74edf42335de0dca0da5158b704c4b"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#acb74edf42335de0dca0da5158b704c4b">arm_compute::TensorShape::remove_dimension</a></div><div class="ttdeci">void remove_dimension(size_t n)</div><div class="ttdoc">Accessor to remove the dimension n from the tensor shape.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00110">TensorShape.h:110</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_n_e_simple_function_no_border_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::INESimpleFunctionNoBorder::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_n_e_simple_function_no_border_8cpp_source.xhtml#l00037">INESimpleFunctionNoBorder.cpp:37</a></div></div> |
| <div class="ttc" id="_i_tensor_8h_xhtml"><div class="ttname"><a href="_i_tensor_8h.xhtml">ITensor.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_reduction_operation_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_reduction_operation.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEReductionOperation::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="_n_e_reduction_operation_8cpp_source.xhtml#l00221">NEReductionOperation.cpp:221</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#l00041">CLTensor.cpp:41</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a3fc6adad84b23f10d54d5a7b6928f872"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">arm_compute::TensorAllocator::init</a></div><div class="ttdeci">void init(const TensorAllocator &allocator, const Coordinates &coords, TensorInfo &sub_info)</div><div class="ttdoc">Shares the same backing memory with another tensor allocator, while the tensor info might be differen...</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00108">TensorAllocator.cpp:108</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00183">ConvolutionLayer.cpp:183</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ac1a1b012674e0f1de071a611391828ad"><div class="ttname"><a href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">arm_compute::PaddingList</a></div><div class="ttdeci">std::vector< PaddingInfo > PaddingList</div><div class="ttdoc">List of padding information.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00455">Types.h:455</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_n_e_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_n_e_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::INESimpleFunction::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_n_e_simple_function_8cpp_source.xhtml#l00036">INESimpleFunction.cpp:36</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1helpers_1_1fft_xhtml_a359fcf05844c0a2f1aed6e4386a86aee"><div class="ttname"><a href="namespacearm__compute_1_1helpers_1_1fft.xhtml#a359fcf05844c0a2f1aed6e4386a86aee">arm_compute::helpers::fft::decompose_stages</a></div><div class="ttdeci">std::vector< unsigned int > decompose_stages(unsigned int N, const std::set< unsigned int > &supported_factors)</div><div class="ttdoc">Decompose a given 1D input size using the provided supported factors.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2utils_2helpers_2fft_8cpp_source.xhtml#l00034">fft.cpp:34</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="structarm__compute_1_1_f_f_t2_d_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_f_f_t2_d_info.xhtml">arm_compute::FFT2DInfo</a></div><div class="ttdoc">Descriptor used by the FFT2D function.</div><div class="ttdef"><b>Definition:</b> <a href="_function_descriptors_8h_source.xhtml#l00045">FunctionDescriptors.h:45</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00597">Winograd.cpp:597</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#l00204">Error.h:204</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="classarm__compute_1_1_n_e_activation_layer_xhtml_aa37e2d0b4cd4f835bfa2a2df4a0bdd2c"><div class="ttname"><a href="classarm__compute_1_1_n_e_activation_layer.xhtml#aa37e2d0b4cd4f835bfa2a2df4a0bdd2c">arm_compute::NEActivationLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ActivationLayerInfo &act_info)</div><div class="ttdoc">[NEActivationLayer snippet]</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_activation_layer_8cpp_source.xhtml#l00043">NEActivationLayer.cpp:43</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#l00792">Validate.h:792</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="classarm__compute_1_1_n_e_f_f_t_convolution_layer_xhtml_ac89fb11a78baf66222f50cd5ee725ebd"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#ac89fb11a78baf66222f50cd5ee725ebd">arm_compute::NEFFTConvolutionLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NEFFTConvolutionLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_f_f_t_convolution_layer_8cpp_source.xhtml#l00252">NEFFTConvolutionLayer.cpp:252</a></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#l00048">Types.h:48</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#l00466">Error.h:466</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml">arm_compute::ITensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_info_8h_source.xhtml#l00040">ITensorInfo.h:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div> |
| <div class="ttc" id="_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#l00296">Error.h:296</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_activation_layer_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_activation_layer_info.xhtml">arm_compute::ActivationLayerInfo</a></div><div class="ttdoc">Activation Layer Information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01615">Types.h:1615</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml">arm_compute::ITensor</a></div><div class="ttdoc">Interface for NEON tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00036">ITensor.h:36</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2020 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00202">Helpers.inl:202</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_reverse_xhtml_abaed98d5f33f212b61484a7ef0c53874"><div class="ttname"><a href="classarm__compute_1_1_n_e_reverse.xhtml#abaed98d5f33f212b61484a7ef0c53874">arm_compute::NEReverse::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output, const ITensor *axis)</div><div class="ttdoc">Initialize the function.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reverse_8cpp_source.xhtml#l00031">NEReverse.cpp:31</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_f_f_t_convolution_layer_xhtml_a064452b83d4907c001b65886876d89c1"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#a064452b83d4907c001b65886876d89c1">arm_compute::NEFFTConvolutionLayer::configure</a></div><div class="ttdeci">void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info=ActivationLayerInfo())</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_f_f_t_convolution_layer_8cpp_source.xhtml#l00097">NEFFTConvolutionLayer.cpp:97</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_xhtml_adbd0cf83a8e1b335a9bf405a8e5019fa"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">arm_compute::Tensor::allocator</a></div><div class="ttdeci">TensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8cpp_source.xhtml#l00048">Tensor.cpp:48</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_xhtml_a47d74e4e51f9b1a636c4831bd747a97c"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">arm_compute::Tensor::info</a></div><div class="ttdeci">ITensorInfo * 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="runtime_2_tensor_8cpp_source.xhtml#l00033">Tensor.cpp:33</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a8fcf2ddd9a1d58b1b280f5c0aed71845"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">arm_compute::test::validation::input</a></div><div class="ttdeci">auto input</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">LSTMLayerQuantized.cpp:487</a></div></div> |
| <div class="ttc" id="fft_8h_xhtml"><div class="ttname"><a href="fft_8h.xhtml">fft.h</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_memory_group_xhtml_a6fc0a49304c152c20a0f6df0634fb3cd"><div class="ttname"><a href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">arm_compute::MemoryGroup::manage</a></div><div class="ttdeci">void manage(IMemoryManageable *obj) override</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_8h_source.xhtml#l00079">MemoryGroup.h:79</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_aa87f8fc26981b0f3228a78c83b95b802"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#aa87f8fc26981b0f3228a78c83b95b802">arm_compute::Dimensions::x</a></div><div class="ttdeci">T x() const</div><div class="ttdoc">Alias to access the size of the first dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00081">Dimensions.h:81</a></div></div> |
| <div class="ttc" id="arm__compute_2core_2_utils_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_utils_8h.xhtml">Utils.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a5827eb9cb394e74af87f74bd354fb45ba6970bdc2201030b9c03fbdcf3973858a"><div class="ttname"><a href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45ba6970bdc2201030b9c03fbdcf3973858a">arm_compute::ReductionOperation::SUM</a></div><div class="ttdoc">Sum.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_slice_xhtml_a5c2f378cb28b6c33a699fcf3d24b7ab3"><div class="ttname"><a href="classarm__compute_1_1_n_e_slice.xhtml#a5c2f378cb28b6c33a699fcf3d24b7ab3">arm_compute::NESlice::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output, const Coordinates &starts, const Coordinates &ends)</div><div class="ttdoc">Configure kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_slice_8cpp_source.xhtml#l00036">NESlice.cpp:36</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_complex_pixel_wise_multiplication_xhtml_a151f73d8df86064f806f8b3256571b0a"><div class="ttname"><a href="classarm__compute_1_1_n_e_complex_pixel_wise_multiplication.xhtml#a151f73d8df86064f806f8b3256571b0a">arm_compute::NEComplexPixelWiseMultiplication::configure</a></div><div class="ttdeci">void configure(ITensor *input1, ITensor *input2, ITensor *output)</div><div class="ttdoc">Initialise the kernel's inputs, output.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_pixel_wise_multiplication_8cpp_source.xhtml#l00055">NEPixelWiseMultiplication.cpp:55</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_f_f_t_convolution_layer_xhtml_abf5b3544ece1ef65b6388a9967d48575"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#abf5b3544ece1ef65b6388a9967d48575">arm_compute::NEFFTConvolutionLayer::NEFFTConvolutionLayer</a></div><div class="ttdeci">NEFFTConvolutionLayer(std::shared_ptr< IMemoryManager > memory_manager=nullptr)</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_f_f_t_convolution_layer_8cpp_source.xhtml#l00055">NEFFTConvolutionLayer.cpp:55</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 U32 per channel</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_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape & tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_abb9481fe056b9749f9b4c08db101cc15"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#abb9481fe056b9749f9b4c08db101cc15">arm_compute::ITensorInfo::set_data_layout</a></div><div class="ttdeci">virtual ITensorInfo & set_data_layout(const DataLayout &data_layout)=0</div><div class="ttdoc">Set the data layout of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::TensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of CPU memory.</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00133">TensorAllocator.cpp:133</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_f_f_t_radix_stage_kernel_xhtml_a058f31a004475bd61913f02fbf251ddb"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t_radix_stage_kernel.xhtml#a058f31a004475bd61913f02fbf251ddb">arm_compute::NEFFTRadixStageKernel::supported_radix</a></div><div class="ttdeci">static std::set< unsigned int > supported_radix()</div><div class="ttdoc">Returns the radix that are support by the FFT kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_f_f_t_radix_stage_kernel_8cpp_source.xhtml#l01035">NEFFTRadixStageKernel.cpp:1035</a></div></div> |
| <div class="ttc" id="_shape_calculator_8h_xhtml"><div class="ttname"><a href="_shape_calculator_8h.xhtml">ShapeCalculator.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr< T > clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_pad_stride_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pad_stride_info.xhtml">arm_compute::PadStrideInfo</a></div><div class="ttdoc">Padding and stride information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00686">Types.h:686</a></div></div> |
| <div class="ttc" id="_n_e_f_f_t_convolution_layer_8h_xhtml"><div class="ttname"><a href="_n_e_f_f_t_convolution_layer_8h.xhtml">NEFFTConvolutionLayer.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">arm_compute::DataLayoutDimension::CHANNEL</a></div><div class="ttdoc">channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a1468b0adb6ec3f9d38aa7d60b8a91974"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a1468b0adb6ec3f9d38aa7d60b8a91974">arm_compute::TensorAllocator::free</a></div><div class="ttdeci">void free() override</div><div class="ttdoc">Free allocated CPU memory.</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00148">TensorAllocator.cpp:148</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_memory_group_resource_scope_xhtml"><div class="ttname"><a href="classarm__compute_1_1_memory_group_resource_scope.xhtml">arm_compute::MemoryGroupResourceScope</a></div><div class="ttdoc">Memory group resources scope handling class.</div><div class="ttdef"><b>Definition:</b> <a href="_i_memory_group_8h_source.xhtml#l00082">IMemoryGroup.h:82</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_f_f_t_convolution_layer_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t_convolution_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEFFTConvolutionLayer::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="_n_e_f_f_t_convolution_layer_8cpp_source.xhtml#l00296">NEFFTConvolutionLayer.cpp:296</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_size2_d_xhtml"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml">arm_compute::Size2D</a></div><div class="ttdoc">Class for specifying the size of an image or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00034">Size2D.h:34</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a82b8ac759c804bc1fb4e2d21e178fb6fae1c8555fcf0ea2bb648a6fd527d658c0"><div class="ttname"><a href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fae1c8555fcf0ea2bb648a6fd527d658c0">arm_compute::ConvertPolicy::WRAP</a></div><div class="ttdoc">Wrap around.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_activation_layer_xhtml_adfb5ef37594fc9371c4a2b95e3d5e31b"><div class="ttname"><a href="classarm__compute_1_1_n_e_activation_layer.xhtml#adfb5ef37594fc9371c4a2b95e3d5e31b">arm_compute::NEActivationLayer::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, ActivationLayerInfo activation_info)</div><div class="ttdoc">[NEActivationLayer snippet]</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_activation_layer_8cpp_source.xhtml#l00036">NEActivationLayer.cpp:36</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_pad_layer_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_pad_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEPadLayer::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="_n_e_pad_layer_8cpp_source.xhtml#l00247">NEPadLayer.cpp:247</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_f_f_t2_d_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t2_d.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEFFT2D::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="_n_e_f_f_t2_d_8cpp_source.xhtml#l00086">NEFFT2D.cpp:86</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_xhtml_a24954cca5108a24706441fd99a7fb04c"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#a24954cca5108a24706441fd99a7fb04c">arm_compute::Tensor::buffer</a></div><div class="ttdeci">uint8_t * buffer() const override</div><div class="ttdoc">Interface to be implemented by the child class to return a pointer to CPU memory.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8cpp_source.xhtml#l00043">Tensor.cpp:43</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="_c_l_2_convolution_layer_8cpp_source.xhtml#l00188">ConvolutionLayer.cpp:188</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_pad_layer_xhtml_ac5a4e9c1564aa9892dfe02cdce2f55b3"><div class="ttname"><a href="classarm__compute_1_1_n_e_pad_layer.xhtml#ac5a4e9c1564aa9892dfe02cdce2f55b3">arm_compute::NEPadLayer::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, const PaddingList &padding, const PixelValue constant_value=PixelValue(), const PaddingMode mode=PaddingMode::CONSTANT)</div><div class="ttdoc">Initialize the function.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_pad_layer_8cpp_source.xhtml#l00164">NEPadLayer.cpp:164</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a84052cebf66a6126051a166a078253a4"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a84052cebf66a6126051a166a078253a4">arm_compute::TensorAllocator::import_memory</a></div><div class="ttdeci">Status import_memory(void *memory)</div><div class="ttdoc">Import an existing memory as a tensor's backing memory.</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00154">TensorAllocator.cpp:154</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_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a86a0c8e195c900a895c249662cfaa564a9f87f02f2da8f99c571b2a1c2a96132b"><div class="ttname"><a href="namespacearm__compute.xhtml#a86a0c8e195c900a895c249662cfaa564a9f87f02f2da8f99c571b2a1c2a96132b">arm_compute::FFTDirection::Inverse</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_ac4a1050be02b20b3f791b9a483f3abe2"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#ac4a1050be02b20b3f791b9a483f3abe2">arm_compute::Dimensions::y</a></div><div class="ttdeci">T y() const</div><div class="ttdoc">Alias to access the size of the second dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00086">Dimensions.h:86</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#l00327">Helpers.inl:327</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_permute_xhtml_a93c836ab36443b23753d99495761daf7"><div class="ttname"><a href="classarm__compute_1_1_n_e_permute.xhtml#a93c836ab36443b23753d99495761daf7">arm_compute::NEPermute::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output, const PermutationVector &perm)</div><div class="ttdoc">Configure the permute NEON kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_permute_8cpp_source.xhtml#l00031">NEPermute.cpp:31</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a269b19ce3f357ac65f41f9951906e38e"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">arm_compute::TensorInfo::tensor_shape</a></div><div class="ttdeci">const TensorShape & tensor_shape() const override</div><div class="ttdoc">Size for each dimension of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00261">TensorInfo.h:261</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_f_f_t2_d_xhtml_a4d704db199385825fcc6fa9fbed62924"><div class="ttname"><a href="classarm__compute_1_1_n_e_f_f_t2_d.xhtml#a4d704db199385825fcc6fa9fbed62924">arm_compute::NEFFT2D::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output, const FFT2DInfo &config)</div><div class="ttdoc">Initialise the function's source and destinations.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_f_f_t2_d_8cpp_source.xhtml#l00037">NEFFT2D.cpp:37</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml"><div class="ttname"><a href="_validate_8h.xhtml">Validate.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_reduction_operation_xhtml_a61cb078b47a1282258de69e3292dc8c8"><div class="ttname"><a href="classarm__compute_1_1_n_e_reduction_operation.xhtml#a61cb078b47a1282258de69e3292dc8c8">arm_compute::NEReductionOperation::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output, unsigned int axis, ReductionOperation op, bool keep_dims=true)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reduction_operation_8cpp_source.xhtml#l00100">NEReductionOperation.cpp:100</a></div></div> |
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| <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_bf9f26469d00835ba20ff8d80ee5a804.xhtml">runtime</a></li><li class="navelem"><a class="el" href="dir_a36523fc4c32a6b0076906589b6fc202.xhtml">NEON</a></li><li class="navelem"><a class="el" href="dir_4d03f28cfd35f8f734a3b0a2f1168d27.xhtml">functions</a></li><li class="navelem"><a class="el" href="_n_e_f_f_t_convolution_layer_8cpp.xhtml">NEFFTConvolutionLayer.cpp</a></li> |
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