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<div class="title">NEReduceMean.cpp</div> </div>
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<a href="_n_e_reduce_mean_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>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2018-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<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>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<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>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_n_e_reduce_mean_8h.xhtml">arm_compute/runtime/NEON/functions/NEReduceMean.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_p_p_2_validate_8h.xhtml">arm_compute/core/CPP/Validate.h</a>&quot;</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_error_8h.xhtml">arm_compute/core/Error.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_helpers_8h.xhtml">arm_compute/core/Helpers.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_shape_calculator_8h.xhtml">arm_compute/core/utils/misc/ShapeCalculator.h</a>&quot;</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_n_e_scheduler_8h.xhtml">arm_compute/runtime/NEON/NEScheduler.h</a>&quot;</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<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>&#160;{</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="keyword">namespace</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;} <span class="comment">// namespace</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;</div><div class="line"><a name="l00038"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a1f208adec0739b6ce732abb5cc8e5a58"> 38</a></span>&#160;<a class="code" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a1f208adec0739b6ce732abb5cc8e5a58">NEReduceMean::NEReduceMean</a>(std::shared_ptr&lt;IMemoryManager&gt; memory_manager)</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; : _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), _reduction_ops(), _keep_dims()</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;}</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#aa88c74fbf9be5e1f2afd2cb81e371287"> 43</a></span>&#160;<a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="namespacearm__compute.xhtml#aa88c74fbf9be5e1f2afd2cb81e371287">validate_config</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_coordinates.xhtml">Coordinates</a> &amp;reduction_axis, <span class="keywordtype">bool</span> keep_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output)</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;{</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(keep_dims);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, output);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <a class="code" href="_c_p_p_2_validate_8h.xhtml#ad2633f3560322e1f8d926949dec1b730">ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <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#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>() &lt; 1);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>() &gt; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;num_dimensions());</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> reduction_ops = reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>();</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> input_dims = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;num_dimensions();</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> axis_local = reduction_axis;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>(); ++i)</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; {</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="comment">//axis: The dimensions to reduce. Must be in the range [-rank(input_tensor), rank(input_tensor)).</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(axis_local[i] &lt; (-static_cast&lt;int&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;num_dimensions())));</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(axis_local[i] &gt;= static_cast&lt;int&gt;(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;num_dimensions()));</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; }</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keywordflow">if</span>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>().<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a0fdcb923dfd4c74858cc2bc326321efb">total_size</a>() != 0)</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="comment">// Only validate if not using auto_init for the output tensor</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> out_shape = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;tensor_shape();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="comment">// Validate output_shape only if not using auto_init</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a519df47124aa903c7de8be2624640c1b">convert_negative_axis</a>(axis_local, input_dims);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; std::sort(axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>(), axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>() + reduction_ops);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; reduction_ops; ++i)</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(axis_local[i] &gt; 3);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(static_cast&lt;unsigned int&gt;(axis_local[i]) &gt; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;num_dimensions() - 1);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="keywordflow">if</span>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() &gt; 0 &amp;&amp; keep_dims)</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; {</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(axis_local[i]) != 1);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; }</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">if</span>(keep_dims)</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; out_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(axis_local[i], 1);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; }</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; {</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(i &gt; static_cast&lt;unsigned int&gt;(axis_local[i]));</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> remove_index = axis_local[i] - i;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(remove_index &gt;= out_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>());</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; out_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#acb74edf42335de0dca0da5158b704c4b">remove_dimension</a>(remove_index);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; }</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> out_info = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;clone()-&gt;set_tensor_shape(out_shape);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <a class="code" href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a>(output, &amp;out_info);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;}</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160;</div><div class="line"><a name="l00096"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a4399d123b93fac32d66025caa251cdfe"> 96</a></span>&#160;<a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a4399d123b93fac32d66025caa251cdfe">NEReduceMean::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_coordinates.xhtml">Coordinates</a> &amp;reduction_axis, <span class="keywordtype">bool</span> keep_dims, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output)</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160;{</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#aa88c74fbf9be5e1f2afd2cb81e371287">validate_config</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, reduction_axis, keep_dims, output);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;}</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160;</div><div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ac741a3edd9fdd407099870bbb27925d7"> 101</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ac741a3edd9fdd407099870bbb27925d7">NEReduceMean::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_coordinates.xhtml">Coordinates</a> &amp;reduction_axis, <span class="keywordtype">bool</span> keep_dims, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output)</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160;{</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="comment">// Perform validate step</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(<a class="code" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a4399d123b93fac32d66025caa251cdfe">NEReduceMean::validate</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info(), reduction_axis, keep_dims, output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()));</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="comment">// Output auto inizialitation if not yet initialized</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ab1806bf0c5a41f674fb9d2dc6af644f5">output_shape</a> = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a7e4084fbf8d78731ea649eee03aaaab7">arm_compute::misc::shape_calculator::calculate_reduce_mean_shape</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, reduction_axis, keep_dims);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;clone()-&gt;set_tensor_shape(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ab1806bf0c5a41f674fb9d2dc6af644f5">output_shape</a>));</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; _reduction_ops = reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>();</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; _reduction_kernels.resize(_reduction_ops);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; _reduced_outs.resize(_reduction_ops - (keep_dims ? 1 : 0));</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; _keep_dims = keep_dims;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> axis_local = reduction_axis;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> input_dims = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;num_dimensions();</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a519df47124aa903c7de8be2624640c1b">convert_negative_axis</a>(axis_local, input_dims);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="comment">// Perform reduction for every axis</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i &lt; _reduction_ops; ++i)</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> out_shape = i == 0 ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;tensor_shape() : (&amp;_reduced_outs[i - 1])-&gt;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>()-&gt;tensor_shape();</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; out_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(axis_local[i], 1);</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="keyword">auto</span> in = (i == 0) ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a> : (&amp;_reduced_outs[i - 1]);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keywordflow">if</span>(i == _reduction_ops - 1 &amp;&amp; keep_dims)</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; _reduction_kernels[i].configure(in, output, axis_local[i], <a class="code" href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5">ReductionOperation::MEAN_SUM</a>);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; {</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; _reduced_outs[i].allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(out_shape, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;num_channels(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;data_type(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;quantization_info()));</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_reduced_outs[i]);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; _reduction_kernels[i].configure(in, &amp;_reduced_outs[i], axis_local[i], <a class="code" href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5">ReductionOperation::MEAN_SUM</a>);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; }</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; }</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i &lt; _reduction_ops - (keep_dims ? 1 : 0); ++i)</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; {</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; _reduced_outs[i].allocator()-&gt;allocate();</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; }</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="comment">// Configure reshape layer if we want to drop the dimensions</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keywordflow">if</span>(!keep_dims)</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> out_shape = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;tensor_shape();</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <span class="comment">// We have to sort the reduction axis vectors in order for remove_dimension</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="comment">// to work properly</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; std::sort(axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>(), axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>() + _reduction_ops);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i &lt; _reduction_ops; ++i)</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; {</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; out_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#acb74edf42335de0dca0da5158b704c4b">remove_dimension</a>(axis_local[i] - i);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; }</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;clone()-&gt;set_tensor_shape(out_shape));</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; _reshape.<a class="code" href="classarm__compute_1_1_n_e_reshape_layer.xhtml#a83a344e60eb7db895953a942abf16628">configure</a>(&amp;_reduced_outs[_reduction_ops - 1], output);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; }</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160;}</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ad1717410afd0be936c6213a63c8005fb"> 160</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ad1717410afd0be936c6213a63c8005fb">NEReduceMean::run</a>()</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160;{</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <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="l00163"></a><span class="lineno"> 163</span>&#160; <span class="keywordflow">for</span>(<span class="keyword">auto</span> &amp;kernel : _reduction_kernels)</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; {</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; kernel.run();</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; }</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <span class="keywordflow">if</span>(!_keep_dims)</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; {</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; _reshape.<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="l00171"></a><span class="lineno"> 171</span>&#160; }</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;}</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;} <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#l00039">TensorShape.h:39</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="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</div></div>
<div class="ttc" id="_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="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="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00455">Error.h:455</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_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 &amp;info, const TensorShape &amp;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="_c_p_p_2_validate_8h_xhtml_ad2633f3560322e1f8d926949dec1b730"><div class="ttname"><a href="_c_p_p_2_validate_8h.xhtml#ad2633f3560322e1f8d926949dec1b730">ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(tensor)</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_2_validate_8h_source.xhtml#l00071">Validate.h:71</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</div></div>
<div class="ttc" id="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="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="_n_e_reduce_mean_8h_xhtml"><div class="ttname"><a href="_n_e_reduce_mean_8h.xhtml">NEReduceMean.h</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00152">Error.h:152</a></div></div>
<div class="ttc" id="_c_p_p_2_validate_8h_xhtml"><div class="ttname"><a href="_c_p_p_2_validate_8h.xhtml">Validate.h</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a27e4638546c88b8916f967e6e54480a9"><div class="ttname"><a href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00443">Validate.h:443</a></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 &amp; tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number unsigned</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_shape_xhtml_a0fdcb923dfd4c74858cc2bc326321efb"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a0fdcb923dfd4c74858cc2bc326321efb">arm_compute::TensorShape::total_size</a></div><div class="ttdeci">size_t total_size() const</div><div class="ttdoc">Collapses all dimensions to a single linear total size.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00171">TensorShape.h:171</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_1_n_e_reduce_mean_xhtml_ac741a3edd9fdd407099870bbb27925d7"><div class="ttname"><a href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ac741a3edd9fdd407099870bbb27925d7">arm_compute::NEReduceMean::configure</a></div><div class="ttdeci">void configure(ITensor *input, const Coordinates &amp;reduction_axis, bool keep_dims, ITensor *output)</div><div class="ttdoc">Configure kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reduce_mean_8cpp_source.xhtml#l00101">NEReduceMean.cpp:101</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div>
<div class="ttc" id="_n_e_scheduler_8h_xhtml"><div class="ttname"><a href="_n_e_scheduler_8h.xhtml">NEScheduler.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_ab2878b67ca384a699c1270900b31290b"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">arm_compute::Dimensions::begin</a></div><div class="ttdeci">std::array&lt; T, num_max_dimensions &gt;::iterator begin()</div><div class="ttdoc">Returns a read/write iterator that points to the first element in the dimension array.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00194">Dimensions.h:194</a></div></div>
<div class="ttc" id="_error_8h_xhtml"><div class="ttname"><a href="_error_8h.xhtml">Error.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_reduce_mean_xhtml_a1f208adec0739b6ce732abb5cc8e5a58"><div class="ttname"><a href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a1f208adec0739b6ce732abb5cc8e5a58">arm_compute::NEReduceMean::NEReduceMean</a></div><div class="ttdeci">NEReduceMean(std::shared_ptr&lt; IMemoryManager &gt; memory_manager=nullptr)</div><div class="ttdoc">Constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reduce_mean_8cpp_source.xhtml#l00038">NEReduceMean.cpp:38</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div>
<div class="ttc" id="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_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_dimensions_xhtml_a80a5f2d6e3a697c9aad893a3b4242615"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">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#l00122">Dimensions.h:122</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5"><div class="ttname"><a href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5">arm_compute::ReductionOperation::MEAN_SUM</a></div><div class="ttdoc">Mean of sum.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_aa88c74fbf9be5e1f2afd2cb81e371287"><div class="ttname"><a href="namespacearm__compute.xhtml#aa88c74fbf9be5e1f2afd2cb81e371287">arm_compute::validate_config</a></div><div class="ttdeci">Status validate_config(const ITensorInfo *input, const Coordinates &amp;reduction_axis, bool keep_dims, const ITensorInfo *output)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reduce_mean_8cpp_source.xhtml#l00043">NEReduceMean.cpp:43</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ab1806bf0c5a41f674fb9d2dc6af644f5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ab1806bf0c5a41f674fb9d2dc6af644f5">arm_compute::test::validation::output_shape</a></div><div class="ttdeci">output_shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_reshape_layer_xhtml_a83a344e60eb7db895953a942abf16628"><div class="ttname"><a href="classarm__compute_1_1_n_e_reshape_layer.xhtml#a83a344e60eb7db895953a942abf16628">arm_compute::NEReshapeLayer::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output)</div><div class="ttdoc">Initialise the kernel's inputs and outputs.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reshape_layer_8cpp_source.xhtml#l00034">NEReshapeLayer.cpp:34</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a9c54fb6cea3557692fe7c00c40bb40ad"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">arm_compute::TensorShape::set</a></div><div class="ttdeci">TensorShape &amp; set(size_t dimension, size_t value, bool apply_dim_correction=true)</div><div class="ttdoc">Accessor to set the value of one of the dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00078">TensorShape.h:78</a></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="arm__compute_2core_2_helpers_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_helpers_8h.xhtml">Helpers.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a519df47124aa903c7de8be2624640c1b"><div class="ttname"><a href="namespacearm__compute.xhtml#a519df47124aa903c7de8be2624640c1b">arm_compute::convert_negative_axis</a></div><div class="ttdeci">Coordinates &amp; convert_negative_axis(Coordinates &amp;coords, int max_value)</div><div class="ttdoc">Convert negative coordinates to positive in the range [0, num_dims_input].</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00774">Helpers.h:774</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_reduce_mean_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEReduceMean::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_reduce_mean_8cpp_source.xhtml#l00160">NEReduceMean.cpp:160</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_reduce_mean_xhtml_a4399d123b93fac32d66025caa251cdfe"><div class="ttname"><a href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a4399d123b93fac32d66025caa251cdfe">arm_compute::NEReduceMean::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const Coordinates &amp;reduction_axis, bool keep_dims, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NEReduceMean.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reduce_mean_8cpp_source.xhtml#l00096">NEReduceMean.cpp:96</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_a7e4084fbf8d78731ea649eee03aaaab7"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a7e4084fbf8d78731ea649eee03aaaab7">arm_compute::misc::shape_calculator::calculate_reduce_mean_shape</a></div><div class="ttdeci">TensorShape calculate_reduce_mean_shape(ITensor *input, const Coordinates &amp;reduction_axis, bool keep_dims)</div><div class="ttdoc">Calculate the output tensor shape for the reduce mean operation.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00050">ShapeCalculator.h:50</a></div></div>
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