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| <div class="title">FullyConnectedLayer.cpp</div> </div> |
| </div><!--header--> |
| <div class="contents"> |
| <a href="validation_2_c_p_p_2_fully_connected_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) 2017 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="tests_2validation_2_c_p_p_2_fully_connected_layer_8h.xhtml">FullyConnectedLayer.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="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div> |
| <div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="tests_2validation_2_fixed_point_8h.xhtml">tests/validation/FixedPoint.h</a>"</span></div> |
| <div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div> |
| <div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <numeric></span></div> |
| <div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div> |
| <div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">namespace </span>arm_compute</div> |
| <div class="line"><a name="l00032"></a><span class="lineno"> 32</span> {</div> |
| <div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">namespace </span>test</div> |
| <div class="line"><a name="l00034"></a><span class="lineno"> 34</span> {</div> |
| <div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">namespace </span>validation</div> |
| <div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div> |
| <div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">namespace </span>reference</div> |
| <div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div> |
| <div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">namespace</span></div> |
| <div class="line"><a name="l00040"></a><span class="lineno"> 40</span> {</div> |
| <div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment">// Vector matrix multiply for floating point</span></div> |
| <div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">template <typename T, typename std::enable_if<is_floating_point<T>::value</a>, <span class="keywordtype">int</span>><a class="code" href="namespacemali__userspace.xhtml#ad44b615021ed3ccb734fcaf583ef4a03">::type</a> = 0></div> |
| <div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="keywordtype">void</span> vector_matrix_multiply(<span class="keyword">const</span> T *src, <span class="keyword">const</span> T *weights, <span class="keyword">const</span> T *bias, T *dst, <span class="keywordtype">int</span> cols_weights, <span class="keywordtype">int</span> rows_weights, uint8_t fixed_point_position)</div> |
| <div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div> |
| <div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(fixed_point_position);</div> |
| <div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div> |
| <div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> y = 0; y < rows_weights; ++y)</div> |
| <div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  {</div> |
| <div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  dst[y] = std::inner_product(src, src + cols_weights, weights, static_cast<T>(0)) + bias[y];</div> |
| <div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  weights += cols_weights;</div> |
| <div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  }</div> |
| <div class="line"><a name="l00052"></a><span class="lineno"> 52</span> }</div> |
| <div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div> |
| <div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment">// Vector matrix multiply for fixed point type</span></div> |
| <div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">template <typename T, typename std::enable_if<std::is_integral<T>::value</a>, <span class="keywordtype">int</span>>::type = 0></div> |
| <div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="keywordtype">void</span> vector_matrix_multiply(<span class="keyword">const</span> T *src, <span class="keyword">const</span> T *weights, <span class="keyword">const</span> T *bias, T *dst, <span class="keywordtype">int</span> cols_weights, <span class="keywordtype">int</span> rows_weights, uint8_t fixed_point_position)</div> |
| <div class="line"><a name="l00057"></a><span class="lineno"> 57</span> {</div> |
| <div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">using namespace </span>fixed_point_arithmetic;</div> |
| <div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">using</span> promoted_type = fixed_point_arithmetic::traits::promote_t<T>;</div> |
| <div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div> |
| <div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> y = 0; y < rows_weights; ++y)</div> |
| <div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {</div> |
| <div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Reset accumulator</span></div> |
| <div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  fixed_point<promoted_type> acc(0, fixed_point_position);</div> |
| <div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div> |
| <div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> x = 0; x < cols_weights; ++x)</div> |
| <div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div> |
| <div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">const</span> fixed_point<promoted_type> i_value(src[x], fixed_point_position, <span class="keyword">true</span>);</div> |
| <div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> fixed_point<promoted_type> w_value(weights[x], fixed_point_position, <span class="keyword">true</span>);</div> |
| <div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  acc = acc + i_value * w_value;</div> |
| <div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  }</div> |
| <div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div> |
| <div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Get the bias</span></div> |
| <div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> fixed_point<T> b(bias[y], fixed_point_position, <span class="keyword">true</span>);</div> |
| <div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div> |
| <div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// Convert back and accumulate the bias</span></div> |
| <div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  fixed_point<T> res(acc);</div> |
| <div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  res = res + b;</div> |
| <div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div> |
| <div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">// Store the result</span></div> |
| <div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  dst[y] = res.raw();</div> |
| <div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div> |
| <div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  weights += cols_weights;</div> |
| <div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  }</div> |
| <div class="line"><a name="l00085"></a><span class="lineno"> 85</span> }</div> |
| <div class="line"><a name="l00086"></a><span class="lineno"> 86</span> } <span class="comment">// namespace</span></div> |
| <div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div> |
| <div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div> |
| <div class="line"><a name="l00089"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a2211dde69485a1533f0b86430e9d0588"> 89</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a2211dde69485a1533f0b86430e9d0588">fully_connected_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &src, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &bias, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &dst_shape)</div> |
| <div class="line"><a name="l00090"></a><span class="lineno"> 90</span> {</div> |
| <div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="comment">// Create reference</span></div> |
| <div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> dst{ <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>{ dst_shape }, src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>(), 1, src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">fixed_point_position</a>() };</div> |
| <div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div> |
| <div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="comment">// Sanity checks</span></div> |
| <div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_batch_dimensions = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(0, static_cast<int>(dst_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">num_dimensions</a>()) - 1);</div> |
| <div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_input_dimensions = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().num_dimensions() - num_batch_dimensions;</div> |
| <div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> linear_input_size = src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().total_size_lower(num_input_dimensions);</div> |
| <div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div> |
| <div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(num_batch_dimensions);</div> |
| <div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <a class="code" href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(num_input_dimensions);</div> |
| <div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(linear_input_size);</div> |
| <div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x() != linear_input_size);</div> |
| <div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y() != bias.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x());</div> |
| <div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y() != dst.shape().x());</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">// Compute reference</span></div> |
| <div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> cols_weights = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().x();</div> |
| <div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> rows_weights = weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>().y();</div> |
| <div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_batches = dst_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a91d8061f66e7f8bc56da91d965f04376">total_size_upper</a>(1);</div> |
| <div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div> |
| <div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < num_batches; ++k)</div> |
| <div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  {</div> |
| <div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  vector_matrix_multiply<T>(src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() + k * cols_weights,</div> |
| <div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  weights.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>(),</div> |
| <div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  bias.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>(),</div> |
| <div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  dst.data() + k * rows_weights,</div> |
| <div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  cols_weights,</div> |
| <div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  rows_weights,</div> |
| <div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  src.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">fixed_point_position</a>());</div> |
| <div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  }</div> |
| <div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div> |
| <div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keywordflow">return</span> dst;</div> |
| <div class="line"><a name="l00123"></a><span class="lineno"> 123</span> }</div> |
| <div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div> |
| <div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a2211dde69485a1533f0b86430e9d0588">fully_connected_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> &src, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> &bias, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &dst_shape);</div> |
| <div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<half></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a2211dde69485a1533f0b86430e9d0588">fully_connected_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<half></a> &src, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<half></a> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<half></a> &bias, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &dst_shape);</div> |
| <div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint8_t></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a2211dde69485a1533f0b86430e9d0588">fully_connected_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint8_t></a> &src, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint8_t></a> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint8_t></a> &bias, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &dst_shape);</div> |
| <div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint16_t></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a2211dde69485a1533f0b86430e9d0588">fully_connected_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint16_t></a> &src, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint16_t></a> &weights, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<qint16_t></a> &bias, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &dst_shape);</div> |
| <div class="line"><a name="l00129"></a><span class="lineno"> 129</span> } <span class="comment">// namespace reference</span></div> |
| <div class="line"><a name="l00130"></a><span class="lineno"> 130</span> } <span class="comment">// namespace validation</span></div> |
| <div class="line"><a name="l00131"></a><span class="lineno"> 131</span> } <span class="comment">// namespace test</span></div> |
| <div class="line"><a name="l00132"></a><span class="lineno"> 132</span> } <span class="comment">// namespace arm_compute</span></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#l00038">TensorShape.h:38</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a4103adbb45806b2f2002d44b91d0d206"><div class="ttname"><a href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(var)</div><div class="ttdoc">To avoid unused variables warnings. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00049">Error.h:49</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a2211dde69485a1533f0b86430e9d0588"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a2211dde69485a1533f0b86430e9d0588">arm_compute::test::validation::reference::fully_connected_layer</a></div><div class="ttdeci">SimpleTensor< T > fully_connected_layer(const SimpleTensor< T > &src, const SimpleTensor< T > &weights, const SimpleTensor< T > &bias, const TensorShape &dst_shape)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_p_p_2_fully_connected_layer_8cpp_source.xhtml#l00089">FullyConnectedLayer.cpp:89</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a9a3e72153aeb3ed212e9c3698774e881"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">arm_compute::test::SimpleTensor::data_type</a></div><div class="ttdeci">DataType data_type() const override</div><div class="ttdoc">Data type of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00265">SimpleTensor.h:265</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00124">Error.h:124</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aba5871b3e4a65d057ec1c28fce8b00ba"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">arm_compute::test::SimpleTensor::shape</a></div><div class="ttdeci">TensorShape shape() const override</div><div class="ttdoc">Shape of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00234">SimpleTensor.h:234</a></div></div> |
| <div class="ttc" id="tests_2validation_2_fixed_point_8h_xhtml"><div class="ttname"><a href="tests_2validation_2_fixed_point_8h.xhtml">FixedPoint.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a91d8061f66e7f8bc56da91d965f04376"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a91d8061f66e7f8bc56da91d965f04376">arm_compute::TensorShape::total_size_upper</a></div><div class="ttdeci">size_t total_size_upper(size_t dimension) const </div><div class="ttdoc">Collapses given dimension and above. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00145">TensorShape.h:145</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a0c52a8f0085b55d907af7210ef2069d0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">arm_compute::test::SimpleTensor::data</a></div><div class="ttdeci">const T * data() const </div><div class="ttdoc">Constant pointer to the underlying buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00311">SimpleTensor.h:311</a></div></div> |
| <div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div> |
| <div class="ttc" id="namespacemali__userspace_xhtml_ad44b615021ed3ccb734fcaf583ef4a03"><div class="ttname"><a href="namespacemali__userspace.xhtml#ad44b615021ed3ccb734fcaf583ef4a03">mali_userspace::type</a></div><div class="ttdeci">uint32_t type</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00204">hwc.hpp:204</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a0f59f175e7682c7ed5f4ea30ef687834"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">arm_compute::Dimensions::num_dimensions</a></div><div class="ttdeci">unsigned int num_dimensions() const </div><div class="ttdoc">Returns the effective dimensionality of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00109">Dimensions.h:109</a></div></div> |
| <div class="ttc" id="tests_2validation_2_c_p_p_2_fully_connected_layer_8h_xhtml"><div class="ttname"><a href="tests_2validation_2_c_p_p_2_fully_connected_layer_8h.xhtml">FullyConnectedLayer.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ad91bb73431b4de1f4946ed949d444849"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">arm_compute::test::fixed_point_arithmetic::detail::max</a></div><div class="ttdeci">fixed_point< T > max(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00889">FixedPoint.h:889</a></div></div> |
| <div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a35ccf2eb0c18a15feab2db98b307b78b"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">arm_compute::test::SimpleTensor::fixed_point_position</a></div><div class="ttdeci">int fixed_point_position() const override</div><div class="ttdoc">The number of bits for the fractional part of the fixed point numbers. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00246">SimpleTensor.h:246</a></div></div> |
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