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| 87 | <a href="backends_2reference_2workloads_2_strided_slice_8cpp.html">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 © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_strided_slice_8hpp.html">StridedSlice.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.html">ResolveType.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <boost/assert.hpp></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <boost/numeric/conversion/cast.hpp></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <cstring></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> {</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="keywordtype">void</span> PadParams(StridedSliceDescriptor& p, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimCount)</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> {</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  BOOST_ASSERT_MSG(dimCount <= 4, <span class="stringliteral">"Expected input with at most 4 dimensions"</span>);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> beginIndicesCount =</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  boost::numeric_cast<<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(p.m_Begin.size());</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  BOOST_ASSERT(dimCount >= beginIndicesCount);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> padCount = dimCount - beginIndicesCount;</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>  p.m_Begin.resize(dimCount);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  p.m_End.resize(dimCount);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  p.m_Stride.resize(dimCount);</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = beginIndicesCount; i > 0; --i)</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>  p.m_Stride[i + padCount - 1] = p.m_Stride[i - 1];</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  p.m_Begin[i + padCount - 1] = p.m_Begin[i - 1];</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  p.m_End[i + padCount - 1] = p.m_End[i - 1];</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> </div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < padCount; ++i)</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>  p.m_Stride[i] = 1;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  p.m_Begin[i] = 0;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  p.m_End[i] = 0;</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> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  p.m_ShrinkAxisMask <<= padCount;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  p.m_EllipsisMask <<= padCount;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  p.m_NewAxisMask <<= padCount;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  p.m_BeginMask <<= padCount;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  p.m_EndMask <<= padCount;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  p.m_BeginMask |= (1 << padCount) - 1;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  p.m_EndMask |= (1 << padCount) - 1;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> }</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="keywordtype">bool</span> LoopCondition(<span class="keywordtype">int</span> index, <span class="keywordtype">int</span> stop, <span class="keywordtype">int</span> stride)</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordflow">return</span> stride > 0 ? index >= stop : index <= stop;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> }</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> TensorShape ExtendShape(<span class="keyword">const</span> TensorShape& inputShape,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> newNumDimensions)</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">if</span> (inputShape.GetNumDimensions() >= newNumDimensions)</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="keywordflow">return</span> inputShape;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  }</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  std::vector<unsigned int> newSizes(newNumDimensions, 0);</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> diff = newNumDimensions - inputShape.GetNumDimensions();</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < diff; i++)</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  {</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  newSizes[i] = 1;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  }</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = diff; i < newNumDimensions; i++)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  {</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  newSizes[i] = inputShape[i - diff];</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keywordflow">return</span> TensorShape(newNumDimensions, newSizes.data());</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</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="comment">// Anonymous namespace</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a86d7a7168ac00b75b4971f9aad623698"> 90</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a86d7a7168ac00b75b4971f9aad623698">StridedSlice</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& inputInfo,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_strided_slice_descriptor.html">StridedSliceDescriptor</a>& params,</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keyword">const</span> <span class="keywordtype">void</span>* inputData,</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">void</span>* outputData,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dataTypeSize)</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>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>* input = <span class="keyword">reinterpret_cast<</span><span class="keyword">const </span><span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>*<span class="keyword">></span>(inputData);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>* output = <span class="keyword">reinterpret_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>*<span class="keyword">></span>(outputData);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape = ExtendShape(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), 4);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="structarmnn_1_1_strided_slice_descriptor.html">StridedSliceDescriptor</a> paddedParams = params;</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">// Pad parameters to 4 dimensions</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  PadParams(paddedParams, 4);</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="keyword">const</span> <span class="keywordtype">int</span> start0 = paddedParams.GetStartForAxis(inputShape, 0);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> stop0 = paddedParams.GetStopForAxis (inputShape, 0, start0);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> start1 = paddedParams.GetStartForAxis(inputShape, 1);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> stop1 = paddedParams.GetStopForAxis (inputShape, 1, start1);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> start2 = paddedParams.GetStartForAxis(inputShape, 2);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> stop2 = paddedParams.GetStopForAxis (inputShape, 2, start2);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> start3 = paddedParams.GetStartForAxis(inputShape, 3);</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> stop3 = paddedParams.GetStopForAxis (inputShape, 3, start3);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> step = boost::numeric_cast<<span class="keywordtype">int</span>>(dataTypeSize);</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="keywordflow">for</span> (<span class="keywordtype">int</span> in0 = start0;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  !LoopCondition(in0, stop0, paddedParams.m_Stride[0]);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  in0 += paddedParams.m_Stride[0])</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>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> in1 = start1;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  !LoopCondition(in1, stop1, paddedParams.m_Stride[1]);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  in1 += paddedParams.m_Stride[1])</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> in2 = start2;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  !LoopCondition(in2, stop2, paddedParams.m_Stride[2]);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  in2 += paddedParams.m_Stride[2])</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  {</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> in3 = start3;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  !LoopCondition(in3, stop3, paddedParams.m_Stride[3]);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  in3 += paddedParams.m_Stride[3])</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="keywordtype">int</span> dim1 = boost::numeric_cast<<span class="keywordtype">int</span>>(inputShape[1]);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordtype">int</span> dim2 = boost::numeric_cast<<span class="keywordtype">int</span>>(inputShape[2]);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordtype">int</span> dim3 = boost::numeric_cast<<span class="keywordtype">int</span>>(inputShape[3]);</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>  <span class="keywordtype">int</span> inputOffset = (((in0 * dim1 + in1) * dim2 + in2) * dim3 + in3) * step;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  ::memcpy(output, input + inputOffset, dataTypeSize);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  output += step;</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>  }</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  }</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  }</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> }</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div> |
| 88 | <div class="ttc" id="_resolve_type_8hpp_html"><div class="ttname"><a href="_resolve_type_8hpp.html">ResolveType.hpp</a></div></div> |
| 89 | <div class="ttc" id="_strided_slice_8hpp_html"><div class="ttname"><a href="_strided_slice_8hpp.html">StridedSlice.hpp</a></div></div> |
| 90 | <div class="ttc" id="namespacearmnn_html_a86d7a7168ac00b75b4971f9aad623698"><div class="ttname"><a href="namespacearmnn.html#a86d7a7168ac00b75b4971f9aad623698">armnn::StridedSlice</a></div><div class="ttdeci">void StridedSlice(const TensorInfo &inputInfo, const StridedSliceDescriptor &params, const void *inputData, void *outputData, unsigned int dataTypeSize)</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_strided_slice_8cpp_source.html#l00090">StridedSlice.cpp:90</a></div></div> |
| 91 | <div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div> |
| 92 | <div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| 93 | <div class="ttc" id="classarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00088">Tensor.hpp:88</a></div></div> |
| 94 | <div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.html">armnn::StridedSliceDescriptor</a></div><div class="ttdoc">A StridedSliceDescriptor for the StridedSliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01002">Descriptors.hpp:1002</a></div></div> |
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