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| <a href="quantization__layer_8cl.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <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> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <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> <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> <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> <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> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <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> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <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> <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> <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> <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> <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> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml">helpers.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"><a class="line" href="quantization__layer_8cl.xhtml#ab448fef4390583fc4b3832f8c590a2b0"> 26</a></span> <span class="preprocessor">#define CONVERT_RTE(x, type) (convert_##type##_rte((x)))</span></div><div class="line"><a name="l00027"></a><span class="lineno"><a class="line" href="quantization__layer_8cl.xhtml#a85ea2f9c49c7c00d41c25f6d5e0687e1"> 27</a></span> <span class="preprocessor">#define CONVERT_RTE_VEC_STR(x, type, size) (convert_##type##size##_rte((x)))</span></div><div class="line"><a name="l00028"></a><span class="lineno"><a class="line" href="quantization__layer_8cl.xhtml#a69f26e0fbc99605b9464b5500d4c461a"> 28</a></span> <span class="preprocessor">#define CONVERT_RTE_VEC(x, type, size) CONVERT_RTE_VEC_STR(x, type, size)</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#if defined(VEC_SIZE) && defined(DATA_TYPE_IN) && defined(DATA_TYPE_OUT) && defined(SCALE) && defined(OFFSET) && defined(MIN_QUANT_VAL) && defined(MAX_QUANT_VAL)</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"></span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment">/** This performs the quantization of floating point inputs to 8-bit unsigned integers.</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> *</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> * @note Input data type should be given as a preprocessor argument using -DDATA_TYPE_IN=type. e.g. -DDATA_TYPE=short</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"> * @note Output data type should be given as a preprocessor argument using -DDATA_TYPE_OUT=type. e.g. -DDATA_TYPE=short</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> * @note Quantization scale should be given as a preprocessor argument using -DSCALE=scale. e.g. -DSCALE=0.125</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"> * @note Quantization offset should be given as a preprocessor argument using -DOFFSET=offset. e.g. -DOFFSET=125</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"> * @note Minimum value for quantized type should be given as a preprocessor argument using -DMIN_QUANT_VAL=value. e.g. -DMIN_QUANT_VAL=0</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"> * @note Maximum value for quantized type should be given as a preprocessor argument using -DMAX_QUANT_VAL=value. e.g. -DMAXIN_QUANT_VAL=255</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"> *</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"> * @param[in] input_ptr Pointer to the source tensor. Supported data types: F32</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"> * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"> * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"> * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"> * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> * @param[out] output_ptr Pointer to the destination tensor. Supported data types: U8</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"> * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment"> * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"> * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> */</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> __kernel <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aa37bd9080cc939b24df4a76fd27a38ae">quantization_layer</a>(</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>),</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(output))</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// Get pixels pointer</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a> = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> output = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(output);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="preprocessor">#if defined(VEC_SIZE) && defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (int)(get_global_id(0) * <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * input_stride_x;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * output_stride_x;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">// Load data</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(DATA_TYPE_IN, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  val = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)(0, (__global DATA_TYPE_IN *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// Create scale and offset vectors</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(DATA_TYPE_IN, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>) vscale = SCALE;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>) voffset = OFFSET;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="comment">// Quantize</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  res = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aabdbe431f2713c5c2604cb9872b66aab">CLAMP</a>(<a class="code" href="quantization__layer_8cl.xhtml#a69f26e0fbc99605b9464b5500d4c461a">CONVERT_RTE_VEC</a>(val / vscale, <span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>) + voffset, MIN_QUANT_VAL, MAX_QUANT_VAL);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="comment">// Store result</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  (<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(res, <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#ac06f3e24d3fffd3c465d8b2a6e7c985e">DATA_TYPE_OUT</a>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)), 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#ac06f3e24d3fffd3c465d8b2a6e7c985e">DATA_TYPE_OUT</a> *)output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="preprocessor">#else </span><span class="comment">//!defined(VEC_SIZE) || !defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="comment"></span> *((__global DATA_TYPE_OUT *)(output.ptr)) = (DATA_TYPE_OUT)CLAMP(CONVERT_RTE(((float) * (__global DATA_TYPE_IN *)input.ptr) / ((float)SCALE), int) + (int)OFFSET, MIN_QUANT_VAL, MAX_QUANT_VAL);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="preprocessor">#endif // defined(VEC_SIZE) && defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="preprocessor">#endif //defined(VEC_SIZE) && defined(DATA_TYPE_IN) && defined(DATA_TYPE_OUT) && defined(SCALE) && defined(OFFSET) && defined(MIN_QUANT_VAL) && defined(MAX_QUANT_VAL)</span></div><div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_aa37bd9080cc939b24df4a76fd27a38ae"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#aa37bd9080cc939b24df4a76fd27a38ae">arm_compute::test::validation::reference::quantization_layer</a></div><div class="ttdeci">SimpleTensor< Tout > quantization_layer(const SimpleTensor< Tin > &src, DataType output_data_type, const QuantizationInfo &quantization_info)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_quantization_layer_8cpp_source.xhtml#l00037">QuantizationLayer.cpp:37</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_aa8d95ba04fc73845abc6045952cae5be"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a></div><div class="ttdeci">#define CONVERT(x, type)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00261">helpers.h:261</a></div></div> |
| <div class="ttc" id="depthwise__convolution__quantized_8cl_xhtml_a3fffea119c04c7680f2e9cf3fadf63b4"><div class="ttname"><a href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a></div><div class="ttdeci">#define VEC_SIZE</div><div class="ttdef"><b>Definition:</b> <a href="depthwise__convolution__quantized_8cl_source.xhtml#l00031">depthwise_convolution_quantized.cl:31</a></div></div> |
| <div class="ttc" id="struct_tensor3_d_xhtml"><div class="ttname"><a href="struct_tensor3_d.xhtml">Tensor3D</a></div><div class="ttdoc">Structure to hold 3D tensor information.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00358">helpers.h:358</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a8fcf2ddd9a1d58b1b280f5c0aed71845"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">arm_compute::test::validation::input</a></div><div class="ttdeci">auto input</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">LSTMLayerQuantized.cpp:487</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_aabdbe431f2713c5c2604cb9872b66aab"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aabdbe431f2713c5c2604cb9872b66aab">CLAMP</a></div><div class="ttdeci">#define CLAMP(x, min_val, max_val)</div><div class="ttdoc">Clamp the given value between an upper and lower bound.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00071">helpers.h:71</a></div></div> |
| <div class="ttc" id="quantization__layer_8cl_xhtml_a69f26e0fbc99605b9464b5500d4c461a"><div class="ttname"><a href="quantization__layer_8cl.xhtml#a69f26e0fbc99605b9464b5500d4c461a">CONVERT_RTE_VEC</a></div><div class="ttdeci">#define CONVERT_RTE_VEC(x, type, size)</div><div class="ttdef"><b>Definition:</b> <a href="quantization__layer_8cl_source.xhtml#l00028">quantization_layer.cl:28</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a31c8c760f08fb1a331b16b7c204321dc"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR3D_STRUCT(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00326">helpers.h:326</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml">helpers.h</a></div></div> |
| <div class="ttc" id="convolution3x3_8cl_xhtml_ac06f3e24d3fffd3c465d8b2a6e7c985e"><div class="ttname"><a href="convolution3x3_8cl.xhtml#ac06f3e24d3fffd3c465d8b2a6e7c985e">DATA_TYPE_OUT</a></div><div class="ttdeci">#define DATA_TYPE_OUT</div><div class="ttdef"><b>Definition:</b> <a href="convolution3x3_8cl_source.xhtml#l00031">convolution3x3.cl:31</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_acb282042d1edeeaa3cc979a206f78b54"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a></div><div class="ttdeci">#define VSTORE(size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00198">helpers.h:198</a></div></div> |
| <div class="ttc" id="struct_tensor3_d_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">Tensor3D::ptr</a></div><div class="ttdeci">__global uchar * ptr</div><div class="ttdoc">Pointer to the starting postion of the buffer.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00360">helpers.h:360</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a287e2fc366c312b468382c95bb90f91f"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a></div><div class="ttdeci">#define VLOAD(size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00195">helpers.h:195</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a6b83038822d1ae7ab619b684ed3b7fc0"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a></div><div class="ttdeci">#define TENSOR3D_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00283">helpers.h:283</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a36f754c05b6fddf6df0d8d0a74f8159f"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a></div><div class="ttdeci">#define VEC_DATA_TYPE(type, size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00255">helpers.h:255</a></div></div> |
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