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<div class="title">QuantizeOperator.cpp</div> </div>
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<a href="_quantize_operator_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>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment">// Copyright © 2020 The TensorFlow Authors. All Rights Reserved.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment">// SPDX-License-Identifier: Apache-2.0</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160; </div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_quantize_operator_8hpp.html">QuantizeOperator.hpp</a>&quot;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160; </div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment">// This function is paraphrased from:</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment">// tensorflow/compiler/mlir/tosa/transforms/legalize_common.cc from function convertQuantizeOp</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"><a class="line" href="_quantize_operator_8hpp.html#a0c01e0628e152677de40807856e20d15"> 13</a></span>&#160;TosaSerializationBasicBlock* <a class="code" href="_quantize_operator_8cpp.html#a0c01e0628e152677de40807856e20d15">ConvertQuantizeToTosaOperator</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* layer,</div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160; <span class="keyword">const</span> std::vector&lt;const TensorInfo*&gt;&amp; inputs,</div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160; <span class="keyword">const</span> std::vector&lt;const TensorInfo*&gt;&amp; outputs)</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;{</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>( inputs.size() == 1,</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <span class="stringliteral">&quot;ConvertQuantizeToTosaOperator: Quantize must have only one input&quot;</span> );</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>( outputs.size() == 1,</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <span class="stringliteral">&quot;ConvertQuantizeToTosaOperator: Quantize must have only one output&quot;</span> );</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; </div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; std::string inputName = std::string(<span class="stringliteral">&quot;input0_&quot;</span>);</div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; std::string outputNameZeroPoint = std::string(<span class="stringliteral">&quot;intermediate0_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; std::string outputNameScale = std::string(<span class="stringliteral">&quot;intermediate1_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; std::string outputNameMul = std::string(<span class="stringliteral">&quot;intermediate2_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; std::string outputNameAdd = std::string(<span class="stringliteral">&quot;intermediate3_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; std::string outputName = std::string(<span class="stringliteral">&quot;output0_&quot;</span>);</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; std::string blockName = std::string(<span class="stringliteral">&quot;Op_QUANTIZE_block_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; </div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="comment">// If a layer is present then the block will be used for execution, so input and output names need to be determined</span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="comment">// using the previous and following layers so the graph is connected correctly. For validation this doesn&#39;t matter.</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keywordflow">if</span>(layer != <span class="keyword">nullptr</span>)</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="comment">// Get the layers connected to the input slots and determine unique tensor names.</span></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>&amp; connectedLayer = layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-&gt;<a class="code" href="classarmnn_1_1_output_slot.html#a7ddaf04177053a536f0e7be83a642bc6">GetOwningLayer</a>();</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; inputName = <a class="code" href="_tosa_operator_utils_8hpp.html#a1640c964a461e8580837a79829a5c197">GenerateUniqueName</a>(connectedLayer, 0);</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"> 38</span>&#160; <span class="comment">// Determine unique output tensor name.</span></div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; outputName = <a class="code" href="_tosa_operator_utils_8hpp.html#a246662c69dac647833be50ba6dcee024">GenerateUniqueOutputName</a>(*layer, 0);</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; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo = *inputs[0];</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo = *outputs[0];</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; <span class="comment">// Extract quantization detail from Tensor</span></div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keywordtype">float</span> zeroPoint = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="comment">// No per axis support in Tensorflow TOSA code</span></div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keywordtype">float</span> scale = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>();</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; </div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="comment">// As per the Tensorflow quantization specification</span></div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="comment">// Tensorflow TOSA code calculates quantization using multiplication by scale</span></div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="comment">// Armnn code calculates quantization using division by scale</span></div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="comment">// Invert scale factor passed from Armnn for tf TOSA code</span></div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; scale = (scale != 0) ? (1 / scale) : scale;</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; std::vector&lt;TosaSerializationTensor*&gt; tensors;</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">// Only add input tensors if connected layer is an input layer.</span></div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="comment">// As intermediate or constant tensors will be created separately.</span></div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="comment">// There also can&#39;t be duplicate tensor.</span></div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; std::vector&lt;int32_t&gt; inputShape0;</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; DType inputDType0 = DType::DType_UNKNOWN;</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keywordflow">if</span>(inputName.find(<span class="stringliteral">&quot;input0_&quot;</span>) != std::string::npos)</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; inputShape0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>());</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; inputDType0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>());</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>( inputDType0 == DType::DType_FP16 || inputDType0 == DType::DType_FP32,</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="stringliteral">&quot;ConvertQuantizeToTosaOperator: Quantize input must be of type Float&quot;</span> );</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(inputName, inputShape0, inputDType0, {}));</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; }</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; std::vector&lt;int32_t&gt; outputShape0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>());</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; DType outputDType0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>());</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; </div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="comment">// quantize:</span></div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="comment">// const_zeroPoint = constant(zeroPoint)</span></div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="comment">// const_scale = constant(scale)</span></div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="comment">// out_mul = mul(input, const_scale)</span></div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="comment">// out_add = add(out_mul, const_zeroPoint)</span></div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="comment">// output = cast&lt;output_type&gt;(out_add)</span></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="comment">// const_zeroPoint</span></div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; TosaSerializationOperator* zeroPointOp = <span class="keyword">nullptr</span>;</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; TosaSerializationTensor* zeroPointTensor = <span class="keyword">nullptr</span>;</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; CreateConstTosaOperator&lt;float&gt;(outputNameZeroPoint,</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; zeroPoint,</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; inputDType0,</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; inputShape0,</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; zeroPointOp,</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; zeroPointTensor);</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; tensors.push_back(zeroPointTensor);</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="comment">// const_scale</span></div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; TosaSerializationOperator *scaleOp = <span class="keyword">nullptr</span>;</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; TosaSerializationTensor* scaleTensor = <span class="keyword">nullptr</span>;</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; CreateConstTosaOperator&lt;float&gt;(outputNameScale,</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; scale,</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; inputDType0,</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; inputShape0,</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; scaleOp,</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; scaleTensor);</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; tensors.push_back(scaleTensor);</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="comment">// mul</span></div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; int32_t shift = 0;</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; TosaMulAttribute mulAttribute(shift);</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; TosaSerializationOperator* mulOp = <span class="keyword">new</span> TosaSerializationOperator(Op_MUL,</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; Attribute_MulAttribute,</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; &amp;mulAttribute,</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; {inputName, outputNameScale},</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; {outputNameMul});</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputNameMul, inputShape0, inputDType0, {}));</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; <span class="comment">// add</span></div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; TosaSerializationOperator* addOp = <span class="keyword">new</span> TosaSerializationOperator(Op_ADD,</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; Attribute_NONE,</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keyword">nullptr</span>,</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; {outputNameMul, outputNameZeroPoint},</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; {outputNameAdd});</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputNameAdd, inputShape0, inputDType0, {}));</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; <span class="comment">// cast</span></div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; TosaSerializationOperator* castOp = <span class="keyword">new</span> TosaSerializationOperator(Op_CAST,</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; Attribute_NONE,</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keyword">nullptr</span>,</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; {outputNameAdd},</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; {outputName});</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; </div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputName, outputShape0, outputDType0, {}));</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; </div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="comment">// operatorInputNames/operatorOutputNames ends up being the same as</span></div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="comment">// blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings</span></div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keywordflow">return</span> <span class="keyword">new</span> TosaSerializationBasicBlock(blockName, <span class="comment">// name</span></div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <a class="code" href="_tosa_operator_utils_8hpp.html#a28514b014a4fe0841044f1868064bc65">mainName</a>, <span class="comment">// region name</span></div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; {zeroPointOp, scaleOp, mulOp, addOp, castOp}, <span class="comment">// operators</span></div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; tensors, <span class="comment">// tensors</span></div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; {inputName}, <span class="comment">// inputs</span></div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; {outputName}); <span class="comment">// outputs</span></div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160;}</div>
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