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+<div class="title">ConvImpl.cpp</div>  </div>
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+<a href="_conv_impl_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="_conv_impl_8hpp.xhtml">ConvImpl.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 &lt;boost/assert.hpp&gt;</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 &lt;cmath&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;limits&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;{</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"><a class="line" href="structarmnn_1_1_quantized_multiplier_smaller_than_one.xhtml#a1ec4f749fbbdacbe2cc7e8895d5b65ed">   16</a></span>&#160;<a class="code" href="structarmnn_1_1_quantized_multiplier_smaller_than_one.xhtml#a1ec4f749fbbdacbe2cc7e8895d5b65ed">QuantizedMultiplierSmallerThanOne::QuantizedMultiplierSmallerThanOne</a>(<span class="keywordtype">float</span> multiplier)</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;{</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;    BOOST_ASSERT(multiplier &gt;= 0.0f &amp;&amp; multiplier &lt; 1.0f);</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;    <span class="keywordflow">if</span> (multiplier == 0.0f)</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;    {</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;        m_Multiplier = 0;</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;        m_RightShift = 0;</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;    <span class="keywordflow">else</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;    {</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">double</span> q = std::frexp(multiplier, &amp;m_RightShift);</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;        m_RightShift = -m_RightShift;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;        int64_t qFixed = <span class="keyword">static_cast&lt;</span>int64_t<span class="keyword">&gt;</span>(std::round(q * (1ll &lt;&lt; 31)));</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;        BOOST_ASSERT(qFixed &lt;= (1ll &lt;&lt; 31));</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;        <span class="keywordflow">if</span> (qFixed == (1ll &lt;&lt; 31))</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;        {</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;            qFixed /= 2;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;            --m_RightShift;</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;        BOOST_ASSERT(m_RightShift &gt;= 0);</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;        BOOST_ASSERT(qFixed &lt;= std::numeric_limits&lt;int32_t&gt;::max());</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;        m_Multiplier = <span class="keyword">static_cast&lt;</span>int32_t<span class="keyword">&gt;</span>(qFixed);</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    }</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;}</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"><a class="line" href="structarmnn_1_1_quantized_multiplier_smaller_than_one.xhtml#ac04834893e568dfea4642ecb575faed8">   41</a></span>&#160;int32_t <a class="code" href="structarmnn_1_1_quantized_multiplier_smaller_than_one.xhtml#ac04834893e568dfea4642ecb575faed8">QuantizedMultiplierSmallerThanOne::operator*</a>(int32_t rhs)<span class="keyword"> const</span></div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    int32_t x = SaturatingRoundingDoublingHighMul(rhs, m_Multiplier);</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <span class="keywordflow">return</span> RoundingDivideByPOT(x, m_RightShift);</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;}</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;int32_t QuantizedMultiplierSmallerThanOne::SaturatingRoundingDoublingHighMul(int32_t a, int32_t b)</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;{</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    <span class="comment">// Check for overflow.</span></div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    <span class="keywordflow">if</span> (a == b &amp;&amp; a == std::numeric_limits&lt;int32_t&gt;::min())</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    {</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        <span class="keywordflow">return</span> std::numeric_limits&lt;int32_t&gt;::max();</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    }</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    int64_t a_64(a);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    int64_t b_64(b);</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    int64_t ab_64 = a_64 * b_64;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    int32_t nudge = ab_64 &gt;= 0 ? (1 &lt;&lt; 30) : (1 - (1 &lt;&lt; 30));</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    int32_t ab_x2_high32 = <span class="keyword">static_cast&lt;</span>std::int32_t<span class="keyword">&gt;</span>((ab_64 + nudge) / (1ll &lt;&lt; 31));</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <span class="keywordflow">return</span> ab_x2_high32;</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;}</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;int32_t QuantizedMultiplierSmallerThanOne::RoundingDivideByPOT(int32_t x, <span class="keywordtype">int</span> exponent)</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;{</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    BOOST_ASSERT(exponent &gt;= 0 &amp;&amp; exponent &lt;= 31);</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    int32_t mask = (1 &lt;&lt; exponent) - 1;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    int32_t remainder = x &amp; mask;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    int32_t threshold = (mask &gt;&gt; 1) + (x &lt; 0 ? 1 : 0);</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <span class="keywordflow">return</span> (x &gt;&gt; exponent) + (remainder &gt; threshold ? 1 : 0);</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;}</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"><a class="line" href="namespacearmnn.xhtml#af98115cd07776d3fa8424434d2a7a897">   71</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#af98115cd07776d3fa8424434d2a7a897">Convolve</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; rInputShape,</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;              <a class="code" href="classarmnn_1_1_decoder.xhtml">Decoder&lt;float&gt;</a>&amp; rInputDecoder,</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;              <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; rOutputShape,</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;              <a class="code" href="classarmnn_1_1_encoder.xhtml">Encoder&lt;float&gt;</a>&amp; rOutputEncoder,</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;              <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; rFilterShape,</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;              <a class="code" href="classarmnn_1_1_decoder.xhtml">Decoder&lt;float&gt;</a>&amp; rFilterDecoder,</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;              <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;              <a class="code" href="classarmnn_1_1_decoder.xhtml">Decoder&lt;float&gt;</a>* pBiasDecoder,</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;              <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;              <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddingTop,</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;              <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddingLeft,</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;              <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xStride,</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;              <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yStride,</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;              <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xDilation,</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;              <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yDilation,</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;              <span class="keywordtype">bool</span> depthwise)</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;{</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    <span class="keywordflow">if</span> (biasEnabled &amp;&amp; !pBiasDecoder)</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    {</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">&quot;Bias is enabled but the bias data is invalid&quot;</span>);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    }</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml">armnnUtils::DataLayoutIndexed</a> dataLayoutIndexed(dataLayout);</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelsIndex = dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>();</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> heightIndex   = dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>();</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> widthIndex    = dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>();</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier = depthwise ? rFilterShape[0] : 1;</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels   = depthwise ? rFilterShape[1] : rFilterShape[channelsIndex];</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels  = depthwise ? inputChannels * depthMultiplier : rFilterShape[0];</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize    = rOutputShape[0];</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = rOutputShape[heightIndex];</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth  = rOutputShape[widthIndex];</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight  = rInputShape[heightIndex];</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth   = rInputShape[widthIndex];</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = depthwise ? rFilterShape[2] : rFilterShape[heightIndex];</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth  = depthwise ? rFilterShape[3] : rFilterShape[widthIndex];</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchIdx = 0; batchIdx &lt; batchSize; batchIdx++)</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    {</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> cOutput = 0; cOutput &lt; outputChannels; cOutput++)</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;        {</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yOutput = 0; yOutput &lt; outputHeight; yOutput++)</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;            {</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xOutput = 0; xOutput &lt; outputWidth; xOutput++)</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;                {</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;                    <span class="comment">// This loop goes over each output element.</span></div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;                    <span class="keywordtype">float</span> sum =  0.0f;</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">// For depthwise, each output channel corresponds to exactly one input channel.</span></div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;                    <span class="comment">// For normal, must loop over each input channel.</span></div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;                    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> cInput = 0; cInput &lt; (depthwise ? 1 : inputChannels); cInput++)</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;                    {</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;                        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthwiseMultiplierIdx = 0;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;                        <span class="keywordflow">if</span> (depthwise)</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;                            cInput = cOutput / depthMultiplier;</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;                            depthwiseMultiplierIdx = cOutput % depthMultiplier;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;                        }</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;                        <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yFilter = 0; yFilter &lt; filterHeight; yFilter++)</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;                        {</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;                            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xFilter = 0; xFilter &lt; filterWidth; xFilter++)</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;                            {</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;                                <span class="comment">// This loop goes over each input element for each output element.</span></div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;                                <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterIndex = 0;</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;                                <span class="comment">// Since dimensionality of kernel depends on depthwiseness, so does index.</span></div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;                                <span class="keywordflow">if</span> (depthwise)</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;                                {</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;                                    filterIndex = depthwiseMultiplierIdx * filterWidth * filterHeight * inputChannels +</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;                                                  cInput * filterWidth * filterHeight +</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;                                                  yFilter * filterWidth +</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;                                                  xFilter;</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;                                }</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;                                <span class="keywordflow">else</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;                                {</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;                                    <span class="comment">// Keep this implementation, as using DataLayoutIndexed::GetIndex causes great</span></div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;                                    <span class="comment">// performance regression.</span></div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;                                    <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;                                    {</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;                                        filterIndex = cOutput * filterHeight * filterWidth * inputChannels +</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;                                                      yFilter * filterWidth * inputChannels +</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;                                                      xFilter * inputChannels +</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;                                                      cInput;</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;                                    }</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;                                    <span class="keywordflow">else</span></div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;                                    {</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;                                        filterIndex = cOutput * filterWidth * filterHeight * inputChannels +</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;                                                      cInput  * filterWidth * filterHeight +</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;                                                      yFilter * filterWidth +</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;                                                      xFilter;</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;                                    }</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;                                }</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;                                rFilterDecoder.<a class="code" href="classarmnn_1_1_base_iterator.xhtml#a1ec75b077d774dbfebf3662e8e4363c9">SetIndex</a>(filterIndex, cOutput);</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;                                <span class="keywordtype">float</span> filterValue = rFilterDecoder.<a class="code" href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;                                <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yInput = yOutput * yStride + yFilter * yDilation;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;                                <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xInput = xOutput * xStride + xFilter * xDilation;</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;                                <span class="keywordtype">float</span> inputValue;</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;                                <span class="comment">// Check if we&#39;re in the padding.</span></div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                                <span class="keywordflow">if</span> (yInput &lt; paddingTop || yInput &gt;= inputHeight + paddingTop ||</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;                                    xInput &lt; paddingLeft || xInput &gt;= inputWidth + paddingLeft )</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;                                {</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;                                    inputValue = 0.0f;</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;                                }</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;                                <span class="keywordflow">else</span></div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;                                {</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                                    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputIndex = 0;</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;                                    <span class="comment">// Keep this implementation, as using DataLayoutIndexed::GetIndex causes great</span></div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;                                    <span class="comment">// performance regression.</span></div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;                                    <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;                                    {</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;                                        inputIndex = batchIdx * inputHeight * inputWidth  * inputChannels +</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;                                                     (yInput - paddingTop) * inputWidth * inputChannels +</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;                                                     (xInput - paddingLeft) * inputChannels +</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;                                                     cInput;</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;                                    }</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;                                    <span class="keywordflow">else</span></div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;                                    {</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;                                        inputIndex = batchIdx * inputWidth * inputHeight * inputChannels +</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;                                                     inputWidth * inputHeight * cInput +</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;                                                     inputWidth * (yInput - paddingTop) +</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;                                                     xInput - paddingLeft;</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;                                    }</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;                                    rInputDecoder[inputIndex];</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;                                    inputValue = rInputDecoder.<a class="code" href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;                                }</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;                                sum += filterValue * inputValue;</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;                            }</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;                        }</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;                    }</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;                    <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;                    {</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;                        (*pBiasDecoder).SetIndex(cOutput, cOutput);</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;                        sum += pBiasDecoder-&gt;<a class="code" href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;                    }</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;                    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outIdx = dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(rOutputShape, batchIdx, cOutput, yOutput, xOutput);</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;                    rOutputEncoder[outIdx];</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;                    rOutputEncoder.<a class="code" href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">Set</a>(sum);</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;                }</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;            }</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;        }</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    }</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;}</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;} <span class="comment">// namespace armnn</span></div><div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div>
+<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a414e6f95548e6f7a01d5028b55ad3941">armnnUtils::DataLayoutIndexed::GetWidthIndex</a></div><div class="ttdeci">unsigned int GetWidthIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00025">DataLayoutIndexed.hpp:25</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_multiplier_smaller_than_one_xhtml_ac04834893e568dfea4642ecb575faed8"><div class="ttname"><a href="structarmnn_1_1_quantized_multiplier_smaller_than_one.xhtml#ac04834893e568dfea4642ecb575faed8">armnn::QuantizedMultiplierSmallerThanOne::operator*</a></div><div class="ttdeci">int32_t operator*(int32_t rhs) const</div><div class="ttdoc">The implementation of this function is adapted from Android NN&amp;#39;s MultiplyByQuantizedMultiplierSmaller...</div><div class="ttdef"><b>Definition:</b> <a href="_conv_impl_8cpp_source.xhtml#l00041">ConvImpl.cpp:41</a></div></div>
+<div class="ttc" id="classarmnn_1_1_encoder_xhtml_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div>
+<div class="ttc" id="classarmnn_1_1_encoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml">armnn::Encoder&lt; float &gt;</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="_conv_impl_8hpp_xhtml"><div class="ttname"><a href="_conv_impl_8hpp.xhtml">ConvImpl.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a61c00316c443adc233c24e85c6c5b740"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a61c00316c443adc233c24e85c6c5b740">armnnUtils::DataLayoutIndexed::GetHeightIndex</a></div><div class="ttdeci">unsigned int GetHeightIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00024">DataLayoutIndexed.hpp:24</a></div></div>
+<div class="ttc" id="classarmnn_1_1_decoder_xhtml_ac729108381e2340bea12877971713ecb"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">armnn::Decoder::Get</a></div><div class="ttdeci">virtual IType Get() const =0</div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_multiplier_smaller_than_one_xhtml_a1ec4f749fbbdacbe2cc7e8895d5b65ed"><div class="ttname"><a href="structarmnn_1_1_quantized_multiplier_smaller_than_one.xhtml#a1ec4f749fbbdacbe2cc7e8895d5b65ed">armnn::QuantizedMultiplierSmallerThanOne::QuantizedMultiplierSmallerThanOne</a></div><div class="ttdeci">QuantizedMultiplierSmallerThanOne(float multiplier)</div><div class="ttdoc">Constructs a QuantizedMultiplierSmallerThanOne which will multiply by the given multiplier. </div><div class="ttdef"><b>Definition:</b> <a href="_conv_impl_8cpp_source.xhtml#l00016">ConvImpl.cpp:16</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_af98115cd07776d3fa8424434d2a7a897"><div class="ttname"><a href="namespacearmnn.xhtml#af98115cd07776d3fa8424434d2a7a897">armnn::Convolve</a></div><div class="ttdeci">void Convolve(const TensorShape &amp;rInputShape, Decoder&lt; float &gt; &amp;rInputDecoder, const TensorShape &amp;rOutputShape, Encoder&lt; float &gt; &amp;rOutputEncoder, const TensorShape &amp;rFilterShape, Decoder&lt; float &gt; &amp;rFilterDecoder, bool biasEnabled, Decoder&lt; float &gt; *pBiasDecoder, DataLayout dataLayout, unsigned int paddingTop, unsigned int paddingLeft, unsigned int xStride, unsigned int yStride, unsigned int xDilation, unsigned int yDilation, bool depthwise)</div><div class="ttdef"><b>Definition:</b> <a href="_conv_impl_8cpp_source.xhtml#l00071">ConvImpl.cpp:71</a></div></div>
+<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml">armnnUtils::DataLayoutIndexed</a></div><div class="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00017">DataLayoutIndexed.hpp:17</a></div></div>
+<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a1e25d8623da985a43597b5756c73b206"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a1e25d8623da985a43597b5756c73b206">armnnUtils::DataLayoutIndexed::GetIndex</a></div><div class="ttdeci">unsigned int GetIndex(const armnn::TensorShape &amp;shape, unsigned int batchIndex, unsigned int channelIndex, unsigned int heightIndex, unsigned int widthIndex) const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00027">DataLayoutIndexed.hpp:27</a></div></div>
+<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div>
+<div class="ttc" id="classarmnn_1_1_base_iterator_xhtml_a1ec75b077d774dbfebf3662e8e4363c9"><div class="ttname"><a href="classarmnn_1_1_base_iterator.xhtml#a1ec75b077d774dbfebf3662e8e4363c9">armnn::BaseIterator::SetIndex</a></div><div class="ttdeci">virtual BaseIterator &amp; SetIndex(unsigned int index, unsigned int axisIndex=0)=0</div></div>
+<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a861b2621ee46e4b63379988b360b8cd9">armnnUtils::DataLayoutIndexed::GetChannelsIndex</a></div><div class="ttdeci">unsigned int GetChannelsIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00023">DataLayoutIndexed.hpp:23</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
+<div class="ttc" id="classarmnn_1_1_decoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml">armnn::Decoder&lt; float &gt;</a></div></div>
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