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<div class="title">RefFakeQuantizationFloat32Workload.cpp</div> </div>
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<a href="_ref_fake_quantization_float32_workload_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. 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;</div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_ref_fake_quantization_float32_workload_8hpp.xhtml">RefFakeQuantizationFloat32Workload.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_ref_workload_utils_8hpp.xhtml">RefWorkloadUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_profiling_8hpp.xhtml">Profiling.hpp</a>&quot;</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;boost/numeric/conversion/cast.hpp&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;{</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"><a class="line" href="namespacearmnn.xhtml#ab3c0b7e1a78b1b98c24934221f36a7c3"> 17</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#ab3c0b7e1a78b1b98c24934221f36a7c3">FakeQuantization</a>(<span class="keyword">const</span> <span class="keywordtype">float</span>* inputData, <span class="keywordtype">float</span>* outputData, uint32_t numElements, <span class="keywordtype">float</span> min, <span class="keywordtype">float</span> max)</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;{</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <span class="keywordtype">float</span> scale = (max - min) / 255.f;</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; int32_t offset = <a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a>&lt;int32_t&gt;((-min * 255.f) / (max - min));</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; <span class="keywordflow">for</span> (uint32_t i = 0; i &lt; numElements; i++)</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; {</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; outputData[i] = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(armnn::Quantize&lt;uint8_t&gt;(inputData[i], scale, offset));</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; }</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;}</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno"><a class="line" href="classarmnn_1_1_ref_fake_quantization_float32_workload.xhtml#ae071e8822437c78baea75c3aef3a263a"> 29</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_ref_fake_quantization_float32_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">RefFakeQuantizationFloat32Workload::Execute</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">Compute::CpuRef</a>, <span class="stringliteral">&quot;RefFakeQuantizationFloat32Workload_Execute&quot;</span>);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; inputInfo = <a class="code" href="namespacearmnn.xhtml#a93d269806f34407695dc10f510001c30">GetTensorInfo</a>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span>* inputData = <a class="code" href="namespacearmnn.xhtml#a691846a9eee59b0cd5b22fb5f674e007">GetInputTensorDataFloat</a>(0, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>);</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keywordtype">float</span>* outputData = <a class="code" href="namespacearmnn.xhtml#ab5f0afc1e37fd100843ecd55d8f284c1">GetOutputTensorDataFloat</a>(0, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48">FakeQuantization</a>(inputData, outputData, inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(),</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.m_Parameters.m_Min,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.m_Parameters.m_Max);</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="comment">//namespace armnn</span></div><div class="ttc" id="namespacearmnn_xhtml_a691846a9eee59b0cd5b22fb5f674e007"><div class="ttname"><a href="namespacearmnn.xhtml#a691846a9eee59b0cd5b22fb5f674e007">armnn::GetInputTensorDataFloat</a></div><div class="ttdeci">const float * GetInputTensorDataFloat(unsigned int idx, const PayloadType &amp;data)</div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.xhtml#l00048">RefWorkloadUtils.hpp:48</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a></div><div class="ttdoc">CPU Execution: Reference C++ kernels. </div></div>
<div class="ttc" id="classarmnn_1_1_ref_fake_quantization_float32_workload_xhtml_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_ref_fake_quantization_float32_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">armnn::RefFakeQuantizationFloat32Workload::Execute</a></div><div class="ttdeci">virtual void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_ref_fake_quantization_float32_workload_8cpp_source.xhtml#l00029">RefFakeQuantizationFloat32Workload.cpp:29</a></div></div>
<div class="ttc" id="_ref_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_ref_workload_utils_8hpp.xhtml">RefWorkloadUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_workload_xhtml_a0a487c549c63319505095b855ea3c195"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">armnn::BaseWorkload::m_Data</a></div><div class="ttdeci">const QueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00046">Workload.hpp:46</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a93d269806f34407695dc10f510001c30"><div class="ttname"><a href="namespacearmnn.xhtml#a93d269806f34407695dc10f510001c30">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo(const ITensorHandle *tensorHandle)</div><div class="ttdoc">float32 helpers </div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.xhtml#l00025">RefWorkloadUtils.hpp:25</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ab3c0b7e1a78b1b98c24934221f36a7c3"><div class="ttname"><a href="namespacearmnn.xhtml#ab3c0b7e1a78b1b98c24934221f36a7c3">armnn::FakeQuantization</a></div><div class="ttdeci">void FakeQuantization(const float *inputData, float *outputData, uint32_t numElements, float min, float max)</div><div class="ttdef"><b>Definition:</b> <a href="_ref_fake_quantization_float32_workload_8cpp_source.xhtml#l00017">RefFakeQuantizationFloat32Workload.cpp:17</a></div></div>
<div class="ttc" id="_profiling_8hpp_xhtml_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00169">Profiling.hpp:169</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a37fa39012e90d568df7f774cd6d1e956"><div class="ttname"><a href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t&lt; std::is_unsigned&lt; Source &gt;::value &amp;&amp;std::is_unsigned&lt; Dest &gt;::value, Dest &gt; numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00033">NumericCast.hpp:33</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48">armnn::LayerType::FakeQuantization</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00030">WorkloadData.hpp:30</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ab5f0afc1e37fd100843ecd55d8f284c1"><div class="ttname"><a href="namespacearmnn.xhtml#ab5f0afc1e37fd100843ecd55d8f284c1">armnn::GetOutputTensorDataFloat</a></div><div class="ttdeci">float * GetOutputTensorDataFloat(unsigned int idx, const PayloadType &amp;data)</div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.xhtml#l00054">RefWorkloadUtils.hpp:54</a></div></div>
<div class="ttc" id="_profiling_8hpp_xhtml"><div class="ttname"><a href="_profiling_8hpp.xhtml">Profiling.hpp</a></div></div>
<div class="ttc" id="_ref_fake_quantization_float32_workload_8hpp_xhtml"><div class="ttname"><a href="_ref_fake_quantization_float32_workload_8hpp.xhtml">RefFakeQuantizationFloat32Workload.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00093">Tensor.hpp:93</a></div></div>
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