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<div class="title">GraphUtils.cpp</div> </div>
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<a href="_graph_utils_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 (c) 2017 ARM Limited.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_graph_utils_8h.xhtml">utils/GraphUtils.h</a>&quot;</span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="utils_2_utils_8h.xhtml">utils/Utils.h</a>&quot;</span></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;<span class="preprocessor">#ifdef ARM_COMPUTE_CL</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#include &quot;<a class="code" href="_open_c_l_8h.xhtml">arm_compute/core/CL/OpenCL.h</a>&quot;</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_tensor_8h.xhtml">arm_compute/runtime/CL/CLTensor.h</a>&quot;</span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_CL */</span><span class="preprocessor"></span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_error_8h.xhtml">arm_compute/core/Error.h</a>&quot;</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_pixel_value_8h.xhtml">arm_compute/core/PixelValue.h</a>&quot;</span></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;<span class="preprocessor">#include &quot;libnpy/npy.hpp&quot;</span></div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor">#include &lt;random&gt;</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;<span class="preprocessor">#include &lt;sstream&gt;</span></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;<span class="keyword">using namespace </span>arm_compute::graph_utils;</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"><a class="line" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#a9ea94bf5b7d00ddb836df1b8dcedb93a"> 42</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#a9ea94bf5b7d00ddb836df1b8dcedb93a">PPMWriter::PPMWriter</a>(std::string name, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> maximum)</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; : _name(std::move(name)), _iterator(0), _maximum(maximum)</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;{</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;}</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"><a class="line" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#ab469d593b4bc92e1d1132a03de0aedca"> 47</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#ab469d593b4bc92e1d1132a03de0aedca">PPMWriter::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</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; std::stringstream ss;</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; ss &lt;&lt; _name &lt;&lt; _iterator &lt;&lt; <span class="stringliteral">&quot;.ppm&quot;</span>;</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keywordflow">if</span>(dynamic_cast&lt;Tensor *&gt;(&amp;tensor) != <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; {</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <a class="code" href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">arm_compute::utils::save_to_ppm</a>(dynamic_cast&lt;Tensor &amp;&gt;(tensor), ss.str());</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; }</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;<span class="preprocessor">#ifdef ARM_COMPUTE_CL</span></div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160;<span class="preprocessor"></span> <span class="keywordflow">else</span> <span class="keywordflow">if</span>(dynamic_cast&lt;CLTensor *&gt;(&amp;tensor) != <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; {</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <a class="code" href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">arm_compute::utils::save_to_ppm</a>(dynamic_cast&lt;CLTensor &amp;&gt;(tensor), ss.str());</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; }</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_CL */</span><span class="preprocessor"></span></div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; _iterator++;</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keywordflow">if</span>(_maximum == 0)</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; {</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; }</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keywordflow">return</span> _iterator &lt; _maximum;</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160;}</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"><a class="line" href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ac5ae9597ba20e5581726743fe7c154b5"> 70</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ac5ae9597ba20e5581726743fe7c154b5">DummyAccessor::DummyAccessor</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> maximum)</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; : _iterator(0), _maximum(maximum)</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;{</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160;}</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;</div>
<div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca"> 75</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">DummyAccessor::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160;{</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <a class="code" href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(tensor);</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordtype">bool</span> <a class="code" href="hwc_8hpp.xhtml#a4fef07ab304fc672e0407e7598fb1870">ret</a> = _maximum == 0 || _iterator &lt; _maximum;</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordflow">if</span>(_iterator == _maximum)</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; {</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; _iterator = 0;</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; }</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; {</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; _iterator++;</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; }</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordflow">return</span> <a class="code" href="hwc_8hpp.xhtml#a4fef07ab304fc672e0407e7598fb1870">ret</a>;</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160;}</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"><a class="line" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#a47e2e3f731e842dde7baaf69634a9530"> 90</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#a47e2e3f731e842dde7baaf69634a9530">RandomAccessor::RandomAccessor</a>(<a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> lower, <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> upper, std::random_device::result_type seed)</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; : _lower(lower), _upper(upper), _seed(seed)</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;{</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160;}</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keyword">typename</span> D&gt;</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;<span class="keywordtype">void</span> RandomAccessor::fill(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor, D &amp;&amp;distribution)</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; std::mt19937 gen(_seed);</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordflow">if</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">padding</a>().<a class="code" href="structarm__compute_1_1_border_size.xhtml#adffbf97e7b8b64e7cf32f0254cddf3c4">empty</a>())</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="keywordflow">for</span>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> = 0; <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> &lt; tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>(); <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> += tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">element_size</a>())</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; {</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keyword">const</span> T <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a> = distribution(gen);</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>T *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>() + <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>) = value;</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; }</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="keywordflow">else</span></div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; {</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="comment">// If tensor has padding accessing tensor elements through execution window.</span></div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; Window window;</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; window.use_tensor_dimensions(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>());</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160;</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&amp;](<span class="keyword">const</span> Coordinates &amp; <span class="keywordtype">id</span>)</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; {</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keyword">const</span> T <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a> = distribution(gen);</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; *<span class="keyword">reinterpret_cast&lt;</span>T *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>)) = value;</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; }</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;}</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"><a class="line" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca"> 122</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">RandomAccessor::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;{</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="keywordflow">switch</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>())</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="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>:</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; {</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; std::uniform_int_distribution&lt;uint8_t&gt; distribution_u8(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint8_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint8_t&gt;());</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; fill&lt;uint8_t&gt;(tensor, distribution_u8);</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="keywordflow">break</span>;</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; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">DataType::S8</a>:</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">DataType::QS8</a>:</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; std::uniform_int_distribution&lt;int8_t&gt; distribution_s8(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int8_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int8_t&gt;());</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; fill&lt;int8_t&gt;(tensor, distribution_s8);</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; }</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">DataType::U16</a>:</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; {</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; std::uniform_int_distribution&lt;uint16_t&gt; distribution_u16(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint16_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint16_t&gt;());</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; fill&lt;uint16_t&gt;(tensor, distribution_u16);</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; }</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>:</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9">DataType::QS16</a>:</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; std::uniform_int_distribution&lt;int16_t&gt; distribution_s16(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int16_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int16_t&gt;());</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; fill&lt;int16_t&gt;(tensor, distribution_s16);</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; }</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</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; std::uniform_int_distribution&lt;uint32_t&gt; distribution_u32(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint32_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint32_t&gt;());</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; fill&lt;uint32_t&gt;(tensor, distribution_u32);</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; }</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>:</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; {</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; std::uniform_int_distribution&lt;int32_t&gt; distribution_s32(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int32_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int32_t&gt;());</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; fill&lt;int32_t&gt;(tensor, distribution_s32);</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; }</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">DataType::U64</a>:</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; std::uniform_int_distribution&lt;uint64_t&gt; distribution_u64(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint64_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint64_t&gt;());</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; fill&lt;uint64_t&gt;(tensor, distribution_u64);</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; }</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">DataType::S64</a>:</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; {</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; std::uniform_int_distribution&lt;int64_t&gt; distribution_s64(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int64_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int64_t&gt;());</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; fill&lt;int64_t&gt;(tensor, distribution_s64);</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <span class="keywordflow">break</span>;</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="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>:</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; {</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; std::uniform_real_distribution&lt;float&gt; distribution_f16(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;());</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; fill&lt;float&gt;(tensor, distribution_f16);</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="keywordflow">break</span>;</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">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</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; std::uniform_real_distribution&lt;float&gt; distribution_f32(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;());</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; fill&lt;float&gt;(tensor, distribution_f32);</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; }</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">DataType::F64</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; std::uniform_real_distribution&lt;double&gt; distribution_f64(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">double</span>&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">double</span>&gt;());</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; fill&lt;double&gt;(tensor, distribution_f64);</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; }</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;NOT SUPPORTED!&quot;</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; <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160;}</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160;</div>
<div class="line"><a name="l00200"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab708c11aea0f419821cd053e3e7dae89"> 200</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab708c11aea0f419821cd053e3e7dae89">NumPyBinLoader::NumPyBinLoader</a>(std::string filename)</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; : _filename(std::move(filename))</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;}</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160;</div>
<div class="line"><a name="l00205"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab469d593b4bc92e1d1132a03de0aedca"> 205</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab469d593b4bc92e1d1132a03de0aedca">NumPyBinLoader::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</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; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> tensor_shape = tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; std::vector&lt;unsigned long&gt; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>;</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; <span class="comment">// Open file</span></div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; std::ifstream stream(_filename, std::ios::in | std::ios::binary);</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(!stream.good(), <span class="stringliteral">&quot;Failed to load binary data&quot;</span>);</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; <span class="comment">// Check magic bytes and version number</span></div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> v_major = 0;</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> v_minor = 0;</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; npy::read_magic(stream, &amp;v_major, &amp;v_minor);</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="comment">// Read header</span></div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; std::string <a class="code" href="hwc_8hpp.xhtml#a9d9174de5edba1e56fbfd90dc5e60f75">header</a>;</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; <span class="keywordflow">if</span>(v_major == 1 &amp;&amp; v_minor == 0)</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; {</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; header = npy::read_header_1_0(stream);</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; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(v_major == 2 &amp;&amp; v_minor == 0)</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; header = npy::read_header_2_0(stream);</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="keywordflow">else</span></div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; {</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Unsupported file format version&quot;</span>);</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; }</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160;</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; <span class="comment">// Parse header</span></div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; <span class="keywordtype">bool</span> fortran_order = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; std::string typestr;</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; npy::ParseHeader(header, typestr, &amp;fortran_order, shape);</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160;</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; <span class="comment">// Check if the typestring matches the given one</span></div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; std::string expect_typestr = <a class="code" href="namespacearm__compute_1_1utils.xhtml#a7990fd2b875e2f6d4c1eded54539cb19">arm_compute::utils::get_typestring</a>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>());</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(typestr != expect_typestr, <span class="stringliteral">&quot;Typestrings mismatch&quot;</span>);</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160;</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; <span class="comment">// Validate tensor shape</span></div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(shape.size() != tensor_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">num_dimensions</a>(), <span class="stringliteral">&quot;Tensor ranks mismatch&quot;</span>);</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="keywordflow">if</span>(fortran_order)</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; {</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; shape.size(); ++i)</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; {</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(tensor_shape[i] != shape[i], <span class="stringliteral">&quot;Tensor dimensions mismatch&quot;</span>);</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; }</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; }</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; {</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; shape.size(); ++i)</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; {</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(tensor_shape[i] != shape[shape.size() - i - 1], <span class="stringliteral">&quot;Tensor dimensions mismatch&quot;</span>);</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; }</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; }</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160;</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <span class="comment">// Read data</span></div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; <span class="keywordflow">if</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">padding</a>().<a class="code" href="structarm__compute_1_1_border_size.xhtml#adffbf97e7b8b64e7cf32f0254cddf3c4">empty</a>())</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; {</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <span class="comment">// If tensor has no padding read directly from stream.</span></div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; stream.read(reinterpret_cast&lt;char *&gt;(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>()), tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>());</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; }</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; {</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <span class="comment">// If tensor has padding accessing tensor elements through execution window.</span></div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> window;</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; window.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(tensor_shape);</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160;</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; {</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; stream.read(reinterpret_cast&lt;char *&gt;(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>)), tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">element_size</a>());</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; });</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; }</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160;}</div>
<div class="ttc" id="_pixel_value_8h_xhtml"><div class="ttname"><a href="_pixel_value_8h.xhtml">PixelValue.h</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1utils_xhtml_a301d0b7bfd70f73fc1924f4281938d08"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">arm_compute::utils::save_to_ppm</a></div><div class="ttdeci">void save_to_ppm(T &amp;tensor, const std::string &amp;ppm_filename)</div><div class="ttdoc">Template helper function to save a tensor image to a PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00281">Utils.h:281</a></div></div>
<div class="ttc" id="structarm__compute_1_1_border_size_xhtml_adffbf97e7b8b64e7cf32f0254cddf3c4"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#adffbf97e7b8b64e7cf32f0254cddf3c4">arm_compute::BorderSize::empty</a></div><div class="ttdeci">constexpr bool empty() const </div><div class="ttdoc">Check if the entire border is zero. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00163">Types.h:163</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pixel_value_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pixel_value.xhtml">arm_compute::PixelValue</a></div><div class="ttdoc">Class describing the value of a pixel for any image format. </div><div class="ttdef"><b>Definition:</b> <a href="_pixel_value_8h_source.xhtml#l00034">PixelValue.h:34</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9">arm_compute::DataType::QS16</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_min_max_location_8cpp_source.xhtml#l00089">MinMaxLocation.cpp:89</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00038">TensorShape.h:38</a></div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a9d9174de5edba1e56fbfd90dc5e60f75"><div class="ttname"><a href="hwc_8hpp.xhtml#a9d9174de5edba1e56fbfd90dc5e60f75">header</a></div><div class="ttdeci">union kbase_uk_hwcnt_header header</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00261">hwc.hpp:261</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::DataType::QS8</a></div></div>
<div class="ttc" id="utils_2_utils_8h_xhtml"><div class="ttname"><a href="utils_2_utils_8h.xhtml">Utils.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">Unknown image format. </div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor. </div></div>
<div class="ttc" id="_error_8h_xhtml_a4103adbb45806b2f2002d44b91d0d206"><div class="ttname"><a href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(var)</div><div class="ttdoc">To avoid unused variables warnings. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00049">Error.h:49</a></div></div>
<div class="ttc" id="_c_l_tensor_8h_xhtml"><div class="ttname"><a href="_c_l_tensor_8h.xhtml">CLTensor.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F16 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::NumPyBinLoader::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00205">GraphUtils.cpp:205</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 S16 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_random_accessor_xhtml_a47e2e3f731e842dde7baaf69634a9530"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#a47e2e3f731e842dde7baaf69634a9530">arm_compute::graph_utils::RandomAccessor::RandomAccessor</a></div><div class="ttdeci">RandomAccessor(PixelValue lower, PixelValue upper, const std::random_device::result_type seed=0)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00090">GraphUtils.cpp:90</a></div></div>
<div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00295">helpers.h:295</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml">arm_compute::ITensor</a></div><div class="ttdoc">Interface for NEON tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00036">ITensor.h:36</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_a14470b4cb59140a1b6ff3b8f16c89ab6"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">arm_compute::Window::use_tensor_dimensions</a></div><div class="ttdeci">void use_tensor_dimensions(const TensorShape &amp;shape, size_t first_dimension=Window::DimX)</div><div class="ttdoc">Use the tensor&#39;s dimensions to fill the window dimensions. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00204">Window.inl:204</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 U32 per channel </div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a4fef07ab304fc672e0407e7598fb1870"><div class="ttname"><a href="hwc_8hpp.xhtml#a4fef07ab304fc672e0407e7598fb1870">ret</a></div><div class="ttdeci">uint32_t ret</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00254">hwc.hpp:254</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 U16 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::DataType::S64</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1utils_xhtml_a7990fd2b875e2f6d4c1eded54539cb19"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml#a7990fd2b875e2f6d4c1eded54539cb19">arm_compute::utils::get_typestring</a></div><div class="ttdeci">std::string get_typestring(DataType data_type)</div><div class="ttdoc">Obtain numpy type string from DataType. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00411">Utils.h:411</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pixel_value_xhtml_a3997ae7153b94a3595d1a33186356a5b"><div class="ttname"><a href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">arm_compute::PixelValue::get</a></div><div class="ttdeci">void get(uint8_t &amp;v) const </div><div class="ttdoc">Interpret the pixel value as a U8. </div><div class="ttdef"><b>Definition:</b> <a href="_pixel_value_8h_source.xhtml#l00157">PixelValue.h:157</a></div></div>
<div class="ttc" id="_graph_utils_8h_xhtml"><div class="ttname"><a href="_graph_utils_8h.xhtml">GraphUtils.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_random_accessor_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::RandomAccessor::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00122">GraphUtils.cpp:122</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a48c7a05cc63f541d732250e39339cee2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">arm_compute::ITensor::ptr_to_element</a></div><div class="ttdeci">uint8_t * ptr_to_element(const Coordinates &amp;id) const </div><div class="ttdoc">Return a pointer to the element at the passed coordinates. </div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00063">ITensor.h:63</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 S32 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape &amp; tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a6c0dcc38187027dcb89cd9724bc5a823"><div class="ttname"><a href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">arm_compute::execute_window_loop</a></div><div class="ttdeci">void execute_window_loop(const Window &amp;w, L &amp;&amp;lambda_function, Ts &amp;&amp;...iterators)</div><div class="ttdoc">Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00127">Helpers.inl:127</a></div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item. </div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_ab988210662dbd3bf32fd563c7dd1bdbf"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">arm_compute::ITensor::buffer</a></div><div class="ttdeci">virtual uint8_t * buffer() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return a pointer to CPU memory. ...</div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor&#39;s metadata. </div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_aa459796b5489eca8a9160cb5dcf1a103"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">arm_compute::ITensorInfo::element_size</a></div><div class="ttdeci">virtual size_t element_size() const =0</div><div class="ttdoc">Element size in bytes calculated as data_size() * num_channels() </div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader_xhtml_ab708c11aea0f419821cd053e3e7dae89"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab708c11aea0f419821cd053e3e7dae89">arm_compute::graph_utils::NumPyBinLoader::NumPyBinLoader</a></div><div class="ttdeci">NumPyBinLoader(std::string filename)</div><div class="ttdoc">Default Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00200">GraphUtils.cpp:200</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a07b929c34ad1dc823d8315876aa403ce"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">arm_compute::ITensorInfo::padding</a></div><div class="ttdeci">virtual PaddingSize padding() const =0</div><div class="ttdoc">Padding of tensor. </div></div>
<div class="ttc" id="_error_8h_xhtml"><div class="ttname"><a href="_error_8h.xhtml">Error.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 U8 per channel </div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes. </div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a0f59f175e7682c7ed5f4ea30ef687834"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">arm_compute::Dimensions::num_dimensions</a></div><div class="ttdeci">unsigned int num_dimensions() const </div><div class="ttdoc">Returns the effective dimensionality of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00109">Dimensions.h:109</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_p_p_m_writer_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::PPMWriter::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00047">GraphUtils.cpp:47</a></div></div>
<div class="ttc" id="_open_c_l_8h_xhtml"><div class="ttname"><a href="_open_c_l_8h.xhtml">OpenCL.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_dummy_accessor_xhtml_ac5ae9597ba20e5581726743fe7c154b5"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ac5ae9597ba20e5581726743fe7c154b5">arm_compute::graph_utils::DummyAccessor::DummyAccessor</a></div><div class="ttdeci">DummyAccessor(unsigned int maximum=1)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00070">GraphUtils.cpp:70</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_p_p_m_writer_xhtml_a9ea94bf5b7d00ddb836df1b8dcedb93a"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#a9ea94bf5b7d00ddb836df1b8dcedb93a">arm_compute::graph_utils::PPMWriter::PPMWriter</a></div><div class="ttdeci">PPMWriter(std::string name, unsigned int maximum=1)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00042">GraphUtils.cpp:42</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_dummy_accessor_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::DummyAccessor::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00075">GraphUtils.cpp:75</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::DataType::F64</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::DataType::U64</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::DataType::S8</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00115">Error.h:115</a></div></div>
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