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1 files changed, 166 insertions, 138 deletions
diff --git a/latest/_quantize_operator_8cpp_source.html b/latest/_quantize_operator_8cpp_source.html index bb2dc01b17..e800bd93b2 100644 --- a/latest/_quantize_operator_8cpp_source.html +++ b/latest/_quantize_operator_8cpp_source.html @@ -36,7 +36,7 @@ <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 15rem; margin-top: .5rem; margin-left 13px"/> <td id="projectalign" style="padding-left: 0.9em;"> <div id="projectname"> -  <span id="projectnumber">24.02</span> +  <span id="projectnumber">24.05</span> </div> </td> </tr> @@ -97,7 +97,7 @@ $(document).ready(function(){initNavTree('_quantize_operator_8cpp_source.html',' </div><!--header--> <div class="contents"> <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> <span class="comment">//</span></div> -<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.</span></div> +<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2023-2024 Arm Ltd and Contributors. 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> <span class="comment">// Copyright © 2020 The TensorFlow Authors. All Rights Reserved.</span></div> @@ -106,160 +106,188 @@ $(document).ready(function(){initNavTree('_quantize_operator_8cpp_source.html',' <div class="line"><a name="l00008"></a><span class="lineno"> 8</span>  </div> <div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_quantize_operator_8hpp.html">QuantizeOperator.hpp</a>"</span></div> <div class="line"><a name="l00010"></a><span class="lineno"> 10</span>  </div> -<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment">// This function is paraphrased from:</span></div> -<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <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> 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>  <span class="keyword">const</span> std::vector<const TensorInfo*>& inputs,</div> -<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>  <span class="keyword">const</span> std::vector<const TensorInfo*>& outputs)</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>  <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>  <span class="stringliteral">"ConvertQuantizeToTosaOperator: Quantize must have only one input"</span> );</div> -<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <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>  <span class="stringliteral">"ConvertQuantizeToTosaOperator: Quantize must have only one output"</span> );</div> -<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  </div> -<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  std::string inputName = std::string(<span class="stringliteral">"input0_"</span>);</div> -<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  std::string outputNameZeroPoint = std::string(<span class="stringliteral">"intermediate0_"</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>  std::string outputNameScale = std::string(<span class="stringliteral">"intermediate1_"</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>  std::string outputNameMul = std::string(<span class="stringliteral">"intermediate2_"</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>  std::string outputNameAdd = std::string(<span class="stringliteral">"intermediate3_"</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>  std::string outputName = std::string(<span class="stringliteral">"output0_"</span>);</div> -<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  std::string blockName = std::string(<span class="stringliteral">"Op_QUANTIZE_block_"</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>  </div> -<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <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>  <span class="comment">// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.</span></div> -<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keywordflow">if</span>(layer != <span class="keyword">nullptr</span>)</div> -<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  {</div> -<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="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>  <a class="code" href="classarmnn_1_1_layer.html">Layer</a>& connectedLayer = layer-><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>()-><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>  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>  </div> -<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="comment">// Determine unique output tensor name.</span></div> -<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  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>  }</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="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>  <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>  </div> -<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// Extract quantization detail from Tensor</span></div> -<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">float</span> zeroPoint = <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></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>  <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>  <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="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "<a class="code" href="_tosa_rescale_operator_utils_8hpp.html">TosaRescaleOperatorUtils.hpp</a>"</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="comment">// This function is paraphrased from:</span></div> +<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment">// tensorflow/compiler/mlir/tosa/transforms/legalize_common.cc from function convertQuantizeOp</span></div> +<div class="line"><a name="l00015"></a><span class="lineno"><a class="line" href="_quantize_operator_8hpp.html#a0c01e0628e152677de40807856e20d15"> 15</a></span> 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="l00016"></a><span class="lineno"> 16</span>  <span class="keyword">const</span> std::vector<const TensorInfo*>& inputs,</div> +<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keyword">const</span> std::vector<const TensorInfo*>& outputs)</div> +<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> {</div> +<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>( inputs.size() == 1,</div> +<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="stringliteral">"ConvertQuantizeToTosaOperator: Quantize must have only one input"</span> );</div> +<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="_exceptions_8hpp.html#a5b0cd1f24b12298894d6367f186ea6dc">ARMNN_THROW_INVALIDARG_MSG_IF_FALSE</a>( outputs.size() == 1,</div> +<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="stringliteral">"ConvertQuantizeToTosaOperator: Quantize must have only one output"</span> );</div> +<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  </div> +<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  std::string inputName = std::string(<span class="stringliteral">"input_"</span>);</div> +<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  std::string outputName = std::string(<span class="stringliteral">"output0_"</span>);</div> +<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  std::string blockName = std::string(<span class="stringliteral">"Op_QUANTIZE_block_"</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>  </div> +<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <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="l00029"></a><span class="lineno"> 29</span>  <span class="comment">// using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.</span></div> +<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordflow">if</span>(layer != <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  {</div> +<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  inputName = <a class="code" href="_tosa_operator_utils_8hpp.html#a8863b57c08a748fd2dd16880337f4b69">GenerateUniqueInputName</a>(layer-><a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div> +<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  outputName = <a class="code" href="_tosa_operator_utils_8hpp.html#a1e5b1f8dcc21f10bc7b0d8517e05049d">GenerateUniqueOutputName</a>(*layer);</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>  </div> +<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <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="l00037"></a><span class="lineno"> 37</span>  <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="l00038"></a><span class="lineno"> 38</span>  </div> +<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">// Extract quantization detail from Tensor</span></div> +<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">float</span> zeroPoint = <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></span>(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</div> +<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="comment">// No per axis support in Tensorflow TOSA code</span></div> +<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <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="l00043"></a><span class="lineno"> 43</span>  </div> +<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="comment">// As per the Tensorflow quantization specification</span></div> +<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// Tensorflow TOSA code calculates quantization using multiplication by scale</span></div> +<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="comment">// Armnn code calculates quantization using division by scale</span></div> +<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="comment">// Invert scale factor passed from Armnn for tf TOSA code</span></div> +<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  scale = (scale != 0) ? (1 / scale) : scale;</div> <div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  </div> -<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="comment">// As per the Tensorflow quantization specification</span></div> -<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <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>  <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>  <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>  scale = (scale != 0) ? (1 / scale) : scale;</div> +<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  std::vector<TosaSerializationTensor*> tensors;</div> +<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  </div> +<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  std::vector<int32_t> 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="l00053"></a><span class="lineno"> 53</span>  DType 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="l00054"></a><span class="lineno"> 54</span>  <span class="keywordtype">bool</span> isFloatInput = inputDType0 == DType::DType_FP16 || inputDType0 == DType::DType_FP32;</div> <div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  </div> -<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  std::vector<TosaSerializationTensor*> tensors;</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="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>  <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>  <span class="comment">// There also can't be duplicate tensor.</span></div> -<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  std::vector<int32_t> inputShape0;</div> -<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  DType inputDType0 = DType::DType_UNKNOWN;</div> -<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">if</span>(inputName.find(<span class="stringliteral">"input0_"</span>) != std::string::npos)</div> -<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  {</div> -<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  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>  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>  <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>  <span class="stringliteral">"ConvertQuantizeToTosaOperator: Quantize input must be of type Float"</span> );</div> -<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  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>  }</div> -<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  </div> -<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  std::vector<int32_t> 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>  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>  </div> -<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// quantize:</span></div> -<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// const_zeroPoint = constant(zeroPoint)</span></div> -<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="comment">// const_scale = constant(scale)</span></div> -<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// out_mul = mul(input, const_scale)</span></div> -<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// out_add = add(out_mul, const_zeroPoint)</span></div> -<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">// output = cast<output_type>(out_add)</span></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>  <span class="comment">// const_zeroPoint</span></div> -<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  TosaSerializationOperator* zeroPointOp = <span class="keyword">nullptr</span>;</div> -<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  TosaSerializationTensor* zeroPointTensor = <span class="keyword">nullptr</span>;</div> -<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  CreateConstTosaOperator<float>(outputNameZeroPoint,</div> -<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  zeroPoint,</div> -<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  inputDType0,</div> -<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  inputShape0,</div> -<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  zeroPointOp,</div> -<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  zeroPointTensor);</div> -<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  tensors.push_back(zeroPointTensor);</div> -<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  </div> -<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="comment">// const_scale</span></div> -<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  TosaSerializationOperator *scaleOp = <span class="keyword">nullptr</span>;</div> -<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  TosaSerializationTensor* scaleTensor = <span class="keyword">nullptr</span>;</div> -<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  CreateConstTosaOperator<float>(outputNameScale,</div> -<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  scale,</div> -<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  inputDType0,</div> -<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  inputShape0,</div> -<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  scaleOp,</div> -<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  scaleTensor);</div> -<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  tensors.push_back(scaleTensor);</div> -<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  </div> -<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="comment">// mul</span></div> -<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  int32_t shift = 0;</div> -<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  TosaMulAttribute mulAttribute(shift);</div> -<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  TosaSerializationOperator* mulOp = <span class="keyword">new</span> TosaSerializationOperator(Op_MUL,</div> -<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  Attribute_MulAttribute,</div> -<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  &mulAttribute,</div> -<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  {inputName, outputNameScale},</div> -<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  {outputNameMul});</div> -<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  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>  </div> -<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="comment">// add</span></div> -<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  TosaSerializationOperator* addOp = <span class="keyword">new</span> TosaSerializationOperator(Op_ADD,</div> -<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  Attribute_NONE,</div> -<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keyword">nullptr</span>,</div> -<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  {outputNameMul, outputNameZeroPoint},</div> -<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  {outputNameAdd});</div> -<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  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>  </div> -<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// cast</span></div> -<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  TosaSerializationOperator* castOp = <span class="keyword">new</span> TosaSerializationOperator(Op_CAST,</div> -<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  Attribute_NONE,</div> -<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">nullptr</span>,</div> -<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  {outputNameAdd},</div> -<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  {outputName});</div> -<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  </div> -<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  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>  </div> -<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <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>  <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>  <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>  <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>  {zeroPointOp, scaleOp, mulOp, addOp, castOp}, <span class="comment">// operators</span></div> -<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  tensors, <span class="comment">// tensors</span></div> -<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  {inputName}, <span class="comment">// inputs</span></div> -<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  {outputName}); <span class="comment">// outputs</span></div> -<div class="line"><a name="l00139"></a><span class="lineno"> 139</span> }</div> +<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// Only add input tensors if connected layer is an input layer.</span></div> +<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// As intermediate or constant tensors will be created separately.</span></div> +<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="comment">// There also can't be duplicate tensor.</span></div> +<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordflow">if</span>(inputName.find(<span class="stringliteral">"input_"</span>) != std::string::npos)</div> +<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  {</div> +<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(inputName, inputShape0, inputDType0, {}));</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>  </div> +<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  std::vector<int32_t> 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="l00065"></a><span class="lineno"> 65</span>  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="l00066"></a><span class="lineno"> 66</span>  </div> +<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">if</span> (isFloatInput)</div> +<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div> +<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="comment">// quantize:</span></div> +<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="comment">// const_zeroPoint = constant(zeroPoint)</span></div> +<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="comment">// const_scale = constant(scale)</span></div> +<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="comment">// out_mul = mul(input, const_scale)</span></div> +<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// out_add = add(out_mul, const_zeroPoint)</span></div> +<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">// output = cast<output_type>(out_add)</span></div> +<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  </div> +<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  std::string outputNameScale = std::string(<span class="stringliteral">"input1_"</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div> +<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  std::string outputNameZeroPoint = std::string(<span class="stringliteral">"input2_"</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div> +<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  std::string outputNameMul = std::string(<span class="stringliteral">"intermediate0_"</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div> +<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  std::string outputNameAdd = std::string(<span class="stringliteral">"intermediate1_"</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div> +<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  </div> +<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="comment">// const_zeroPoint</span></div> +<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  TosaSerializationOperator* zeroPointOp = <span class="keyword">nullptr</span>;</div> +<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  TosaSerializationTensor* zeroPointTensor = <span class="keyword">nullptr</span>;</div> +<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  CreateConstTosaOperator<float>(outputNameZeroPoint,</div> +<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  zeroPoint,</div> +<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  inputDType0,</div> +<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  inputShape0,</div> +<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  zeroPointOp,</div> +<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  zeroPointTensor);</div> +<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  tensors.push_back(zeroPointTensor);</div> +<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  </div> +<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="comment">// const_scale</span></div> +<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  TosaSerializationOperator *scaleOp = <span class="keyword">nullptr</span>;</div> +<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  TosaSerializationTensor* scaleTensor = <span class="keyword">nullptr</span>;</div> +<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  CreateConstTosaOperator<float>(outputNameScale,</div> +<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  scale,</div> +<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  inputDType0,</div> +<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  inputShape0,</div> +<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  scaleOp,</div> +<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  scaleTensor);</div> +<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  tensors.push_back(scaleTensor);</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">// mul</span></div> +<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  int32_t shift = 0;</div> +<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  TosaMulAttribute mulAttribute(shift);</div> +<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  TosaSerializationOperator* mulOp = <span class="keyword">new</span> TosaSerializationOperator(Op_MUL,</div> +<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  Attribute_MulAttribute,</div> +<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  &mulAttribute,</div> +<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  {inputName, outputNameScale},</div> +<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  {outputNameMul});</div> +<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputNameMul, inputShape0, inputDType0, {}));</div> +<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  </div> +<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="comment">// add</span></div> +<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  TosaSerializationOperator* addOp = <span class="keyword">new</span> TosaSerializationOperator(Op_ADD,</div> +<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  Attribute_NONE,</div> +<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keyword">nullptr</span>,</div> +<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  {outputNameMul, outputNameZeroPoint},</div> +<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  {outputNameAdd});</div> +<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputNameAdd, inputShape0, inputDType0, {}));</div> +<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  </div> +<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="comment">// cast</span></div> +<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  TosaSerializationOperator* castOp = <span class="keyword">new</span> TosaSerializationOperator(Op_CAST,</div> +<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  Attribute_NONE,</div> +<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">nullptr</span>,</div> +<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  {outputNameAdd},</div> +<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  {outputName});</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>  tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputName, outputShape0, outputDType0, {}));</div> +<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  </div> +<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="comment">// operatorInputNames/operatorOutputNames ends up being the same as</span></div> +<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="comment">// blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings</span></div> +<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> TosaSerializationBasicBlock(blockName, <span class="comment">// name</span></div> +<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <a class="code" href="_tosa_operator_utils_8hpp.html#a28514b014a4fe0841044f1868064bc65">mainName</a>, <span class="comment">// region name</span></div> +<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  {zeroPointOp, scaleOp, mulOp, addOp, castOp}, <span class="comment">// operators</span></div> +<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  tensors, <span class="comment">// tensors</span></div> +<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  {inputName}, <span class="comment">// inputs</span></div> +<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  {outputName}); <span class="comment">// outputs</span></div> +<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  }</div> +<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordflow">else</span></div> +<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  {</div> +<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordtype">double</span> scale_alpha = inputs[0]->GetQuantizationScale() / outputs[0]->GetQuantizationScale();</div> +<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  int32_t input_zp = inputs[0]->GetQuantizationOffset();</div> +<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  int32_t output_zp = outputs[0]->GetQuantizationOffset();</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>  TosaSerializationOperator* rescaleOp = <span class="keyword">nullptr</span>;</div> +<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="_tosa_rescale_operator_utils_8hpp.html#a94df4e987955bf744ebca8211da1c26b">CreateRescaleTosaOperator</a>(inputName,</div> +<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  outputName,</div> +<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  scale_alpha,</div> +<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  input_zp,</div> +<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  output_zp,</div> +<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keyword">true</span>,</div> +<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">true</span>,</div> +<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  &rescaleOp);</div> +<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputName,</div> +<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  inputShape0,</div> +<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  outputDType0, {}));</div> +<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  </div> +<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// operatorInputNames/operatorOutputNames ends up being the same as</span></div> +<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings</span></div> +<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> TosaSerializationBasicBlock(blockName, <span class="comment">// name</span></div> +<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <a class="code" href="_tosa_operator_utils_8hpp.html#a28514b014a4fe0841044f1868064bc65">mainName</a>, <span class="comment">// region name</span></div> +<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  {rescaleOp}, <span class="comment">// operators</span></div> +<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  tensors, <span class="comment">// tensors</span></div> +<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  {inputName}, <span class="comment">// inputs</span></div> +<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  {outputName}); <span class="comment">// outputs</span></div> +<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  }</div> +<div class="line"><a name="l00167"></a><span class="lineno"> 167</span> }</div> </div><!-- fragment --></div><!-- contents --> </div><!-- doc-content --> <div class="ttc" id="a_quantize_operator_8hpp_html"><div class="ttname"><a href="_quantize_operator_8hpp.html">QuantizeOperator.hpp</a></div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00461">Tensor.cpp:461</a></div></div> <div class="ttc" id="aclassarmnn_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#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="a_tosa_rescale_operator_utils_8hpp_html"><div class="ttname"><a href="_tosa_rescale_operator_utils_8hpp.html">TosaRescaleOperatorUtils.hpp</a></div></div> +<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a1e5b1f8dcc21f10bc7b0d8517e05049d"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a1e5b1f8dcc21f10bc7b0d8517e05049d">GenerateUniqueOutputName</a></div><div class="ttdeci">std::string GenerateUniqueOutputName(const Layer &layer, uint32_t layerSlot=0)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00120">TosaOperatorUtils.hpp:120</a></div></div> <div class="ttc" id="aclassarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00337">Layer.hpp:337</a></div></div> <div class="ttc" id="aclassarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00230">Layer.hpp:230</a></div></div> <div class="ttc" id="a_tosa_operator_utils_8hpp_html_a28514b014a4fe0841044f1868064bc65"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a28514b014a4fe0841044f1868064bc65">mainName</a></div><div class="ttdeci">const std::string mainName</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00019">TosaOperatorUtils.hpp:19</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_output_slot_html_a7ddaf04177053a536f0e7be83a642bc6"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7ddaf04177053a536f0e7be83a642bc6">armnn::OutputSlot::GetOwningLayer</a></div><div class="ttdeci">Layer & GetOwningLayer() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00132">Layer.hpp:132</a></div></div> <div class="ttc" id="a_tosa_operator_utils_8hpp_html_a45d66f17ad6b0469e469f443b3e03226"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a></div><div class="ttdeci">DType ArmNNToDType(const DataType &type)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00022">TosaOperatorUtils.hpp:22</a></div></div> -<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a246662c69dac647833be50ba6dcee024"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a246662c69dac647833be50ba6dcee024">GenerateUniqueOutputName</a></div><div class="ttdeci">std::string GenerateUniqueOutputName(const Layer &layer, uint32_t layerSlot)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00082">TosaOperatorUtils.hpp:82</a></div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_info_html_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00200">Tensor.hpp:200</a></div></div> -<div class="ttc" id="a_quantize_operator_8cpp_html_a0c01e0628e152677de40807856e20d15"><div class="ttname"><a href="_quantize_operator_8cpp.html#a0c01e0628e152677de40807856e20d15">ConvertQuantizeToTosaOperator</a></div><div class="ttdeci">TosaSerializationBasicBlock * ConvertQuantizeToTosaOperator(const Layer *layer, const std::vector< const TensorInfo * > &inputs, const std::vector< const TensorInfo * > &outputs)</div><div class="ttdef"><b>Definition:</b> <a href="_quantize_operator_8cpp_source.html#l00013">QuantizeOperator.cpp:13</a></div></div> +<div class="ttc" id="a_quantize_operator_8cpp_html_a0c01e0628e152677de40807856e20d15"><div class="ttname"><a href="_quantize_operator_8cpp.html#a0c01e0628e152677de40807856e20d15">ConvertQuantizeToTosaOperator</a></div><div class="ttdeci">TosaSerializationBasicBlock * ConvertQuantizeToTosaOperator(const Layer *layer, const std::vector< const TensorInfo * > &inputs, const std::vector< const TensorInfo * > &outputs)</div><div class="ttdef"><b>Definition:</b> <a href="_quantize_operator_8cpp_source.html#l00015">QuantizeOperator.cpp:15</a></div></div> <div class="ttc" id="aclassarmnn_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#l00193">Tensor.hpp:193</a></div></div> -<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a1640c964a461e8580837a79829a5c197"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a1640c964a461e8580837a79829a5c197">GenerateUniqueName</a></div><div class="ttdeci">std::string GenerateUniqueName(const Layer &layer, uint32_t layerSlot)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00063">TosaOperatorUtils.hpp:63</a></div></div> -<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a7d97964a65be4eb4a5b4109904f2e7f7"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a></div><div class="ttdeci">std::vector< int32_t > GetTosaTensorShape(const TensorShape &shape)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00052">TosaOperatorUtils.hpp:52</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_input_slot_html_a9effd325a6d512a3f8ff4bd207d53255"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">armnn::InputSlot::GetConnectedOutputSlot</a></div><div class="ttdeci">const OutputSlot * GetConnectedOutputSlot() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00056">Layer.hpp:56</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00478">Tensor.cpp:478</a></div></div> -<div class="ttc" id="a_tosa_operator_utils_8hpp_html_aadc5d73bd0cb81999bcfdc62bce020e8"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a></div><div class="ttdeci">std::string GetUniqueTosaMappingID()</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00100">TosaOperatorUtils.hpp:100</a></div></div> +<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a7d97964a65be4eb4a5b4109904f2e7f7"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a></div><div class="ttdeci">std::vector< int32_t > GetTosaTensorShape(const TensorShape &shape)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00079">TosaOperatorUtils.hpp:79</a></div></div> +<div class="ttc" id="a_tosa_rescale_operator_utils_8hpp_html_a94df4e987955bf744ebca8211da1c26b"><div class="ttname"><a href="_tosa_rescale_operator_utils_8hpp.html#a94df4e987955bf744ebca8211da1c26b">CreateRescaleTosaOperator</a></div><div class="ttdeci">void CreateRescaleTosaOperator(const std::string &inputName, const std::string &outputName, const std::vector< int32_t > &multipliers, const std::vector< int32_t > &shifts, int32_t input_zp, int32_t output_zp, bool double_round, bool scale32, bool per_channel, TosaSerializationOperator **op)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_rescale_operator_utils_8hpp_source.html#l00010">TosaRescaleOperatorUtils.hpp:10</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00482">Tensor.cpp:482</a></div></div> +<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a8863b57c08a748fd2dd16880337f4b69"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a8863b57c08a748fd2dd16880337f4b69">GenerateUniqueInputName</a></div><div class="ttdeci">std::string GenerateUniqueInputName(const armnn::InputSlot &slot)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00109">TosaOperatorUtils.hpp:109</a></div></div> +<div class="ttc" id="a_tosa_operator_utils_8hpp_html_aadc5d73bd0cb81999bcfdc62bce020e8"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a></div><div class="ttdeci">std::string GetUniqueTosaMappingID()</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00138">TosaOperatorUtils.hpp:138</a></div></div> <div class="ttc" 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