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| <div class="title">GCDirectConvolutionLayer Class Reference</div> </div> |
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| |
| <p>Basic function to execute direct convolution function. |
| <a href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_g_c_direct_convolution_layer_8h_source.xhtml">GCDirectConvolutionLayer.h</a>></code></p> |
| <div class="dynheader"> |
| Collaboration diagram for GCDirectConvolutionLayer:</div> |
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| </div> |
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| <table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a> |
| Public Member Functions</h2></td></tr> |
| <tr class="memitem:a457c6a685b2fe36fd12dd640f6155c31"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml#a457c6a685b2fe36fd12dd640f6155c31">GCDirectConvolutionLayer</a> ()</td></tr> |
| <tr class="memdesc:a457c6a685b2fe36fd12dd640f6155c31"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <a href="#a457c6a685b2fe36fd12dd640f6155c31">More...</a><br /></td></tr> |
| <tr class="separator:a457c6a685b2fe36fd12dd640f6155c31"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a17f216ad80126a2e84cd8c1210b9d1da"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml#a17f216ad80126a2e84cd8c1210b9d1da">configure</a> (<a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *input, const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *weights, const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *biases, <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *output, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &conv_info, const <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> &act_info=<a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>())</td></tr> |
| <tr class="memdesc:a17f216ad80126a2e84cd8c1210b9d1da"><td class="mdescLeft"> </td><td class="mdescRight">Set the input and output tensors. <a href="#a17f216ad80126a2e84cd8c1210b9d1da">More...</a><br /></td></tr> |
| <tr class="separator:a17f216ad80126a2e84cd8c1210b9d1da"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a92fe532c342ae2b07956a65520c05362"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml#a92fe532c342ae2b07956a65520c05362">run</a> () override final</td></tr> |
| <tr class="memdesc:a92fe532c342ae2b07956a65520c05362"><td class="mdescLeft"> </td><td class="mdescRight">Run the kernels contained in the function. <a href="#a92fe532c342ae2b07956a65520c05362">More...</a><br /></td></tr> |
| <tr class="separator:a92fe532c342ae2b07956a65520c05362"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="inherit_header pub_methods_classarm__compute_1_1_i_function"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_function')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></td></tr> |
| <tr class="memitem:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">~IFunction</a> ()=default</td></tr> |
| <tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft"> </td><td class="mdescRight">Destructor. <a href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br /></td></tr> |
| <tr class="separator:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">prepare</a> ()</td></tr> |
| <tr class="memdesc:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft"> </td><td class="mdescRight">Prepare the function for executing. <a href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">More...</a><br /></td></tr> |
| <tr class="separator:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>Basic function to execute direct convolution function. </p> |
| <p>This function calls the following kernels:</p> |
| <ol type="1"> |
| <li><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer_kernel.xhtml">GCDirectConvolutionLayerKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml">GCFillBorderKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_g_c_tensor_shift_kernel.xhtml">GCTensorShiftKernel</a></li> |
| </ol> |
| <dl class="section note"><dt>Note</dt><dd>Supported kernel size: 1x1, 3x3, and 5x5 </dd> |
| <dd> |
| This OpenGL ES implementation works with stride_x = 1 and 2 </dd></dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_g_c_direct_convolution_layer_8h_source.xhtml#l00050">50</a> of file <a class="el" href="_g_c_direct_convolution_layer_8h_source.xhtml">GCDirectConvolutionLayer.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a id="a457c6a685b2fe36fd12dd640f6155c31"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a457c6a685b2fe36fd12dd640f6155c31">◆ </a></span>GCDirectConvolutionLayer()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml">GCDirectConvolutionLayer</a> </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Default constructor. </p> |
| |
| <p class="definition">Definition at line <a class="el" href="_g_c_direct_convolution_layer_8cpp_source.xhtml#l00037">37</a> of file <a class="el" href="_g_c_direct_convolution_layer_8cpp_source.xhtml">GCDirectConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  : _kernel(<span class="keyword">nullptr</span>), _border_handler(), _shift_handler()</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <h2 class="groupheader">Member Function Documentation</h2> |
| <a id="a17f216ad80126a2e84cd8c1210b9d1da"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a17f216ad80126a2e84cd8c1210b9d1da">◆ </a></span>configure()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void configure </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> * </td> |
| <td class="paramname"><em>input</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> * </td> |
| <td class="paramname"><em>weights</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> * </td> |
| <td class="paramname"><em>biases</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> * </td> |
| <td class="paramname"><em>output</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> & </td> |
| <td class="paramname"><em>conv_info</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> & </td> |
| <td class="paramname"><em>act_info</em> = <code><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a>()</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Set the input and output tensors. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">input</td><td>Source tensor. 3 lower dimensions represent a single input [width, height, IFM], while every optional dimension from 4 and above represent a batch of inputs. Data types supported: F16/F32. input will be written to only if it is currently left aligned. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">weights</td><td>Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">biases</td><td>Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported:Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. Data types supported: Same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">conv_info</td><td>Contains padding and stride information described in <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">act_info</td><td>(Optional) Activation layer information in case of a fused activation. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_g_c_direct_convolution_layer_8cpp_source.xhtml#l00042">42</a> of file <a class="el" href="_g_c_direct_convolution_layer_8cpp_source.xhtml">GCDirectConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordtype">int</span> kernel_size = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a8813441b655b97c00139c6a5a6390e97">dimension</a>(0);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">if</span>(kernel_size == 1)</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique<GCDirectConvolutionLayer1x1Kernel>();</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  k->configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  _kernel = std::move(k);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  }</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(kernel_size == 3)</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique<GCDirectConvolutionLayer3x3Kernel>();</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  k->configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  _kernel = std::move(k);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(kernel_size == 5)</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  {</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique<GCDirectConvolutionLayer5x5Kernel>();</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  k->configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">weights</a>, biases, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">conv_info</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">act_info</a>);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  _kernel = std::move(k);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  }</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">else</span></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>  <a class="code" href="_error_8h.xhtml#a7cf8d8b669b8f7b05680230be30d60f4">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"kernel size unsupported!"</span>);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">return</span>;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  }</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  _border_handler.<a class="code" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml#a148acc5bac0dddc8d512b4d91bd2a7ba">configure</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, _kernel->border_size(), <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">BorderMode::CONSTANT</a>, <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>());</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  _shift_handler.<a class="code" href="classarm__compute_1_1_g_c_tensor_shift_kernel.xhtml#a2a2ddfadb250e8a4c4d5db67f048f2e8">configure</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> }</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="classarm__compute_1_1_c_l_tensor_xhtml_ad45f0c01a0713dfb6bd7232c7f396fc4"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">arm_compute::CLTensor::info</a></div><div class="ttdeci">TensorInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00041">CLTensor.cpp:41</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a1f8aca235c095df227e7444f6b237eb1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f8aca235c095df227e7444f6b237eb1">arm_compute::test::validation::act_info</a></div><div class="ttdeci">act_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00183">ConvolutionLayer.cpp:183</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a7cf8d8b669b8f7b05680230be30d60f4"><div class="ttname"><a href="_error_8h.xhtml#a7cf8d8b669b8f7b05680230be30d60f4">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(msg)</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#l00352">Error.h:352</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a00525ff582f16038a1d3819aa44a23a3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a00525ff582f16038a1d3819aa44a23a3">arm_compute::test::validation::conv_info</a></div><div class="ttdeci">conv_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00597">Winograd.cpp:597</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a8813441b655b97c00139c6a5a6390e97"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a8813441b655b97c00139c6a5a6390e97">arm_compute::TensorInfo::dimension</a></div><div class="ttdeci">size_t dimension(size_t index) const override</div><div class="ttdoc">Return the size of the requested dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00232">TensorInfo.h:232</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="classarm__compute_1_1_g_c_fill_border_kernel_xhtml_a148acc5bac0dddc8d512b4d91bd2a7ba"><div class="ttname"><a href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml#a148acc5bac0dddc8d512b4d91bd2a7ba">arm_compute::GCFillBorderKernel::configure</a></div><div class="ttdeci">void configure(const IGCTensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &constant_border_value=PixelValue())</div><div class="ttdoc">Initialise the kernel's input, output and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_fill_border_kernel_8cpp_source.xhtml#l00060">GCFillBorderKernel.cpp:60</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92"><div class="ttname"><a href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">arm_compute::PaddingMode::CONSTANT</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a64a08a9fec5aeee8650e7182b6d171d0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a64a08a9fec5aeee8650e7182b6d171d0">arm_compute::test::validation::weights</a></div><div class="ttdeci">CLTensor weights</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00188">ConvolutionLayer.cpp:188</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_tensor_shift_kernel_xhtml_a2a2ddfadb250e8a4c4d5db67f048f2e8"><div class="ttname"><a href="classarm__compute_1_1_g_c_tensor_shift_kernel.xhtml#a2a2ddfadb250e8a4c4d5db67f048f2e8">arm_compute::GCTensorShiftKernel::configure</a></div><div class="ttdeci">void configure(IGCTensor *input)</div><div class="ttdoc">Set the input of the kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_tensor_shift_kernel_8cpp_source.xhtml#l00045">GCTensorShiftKernel.cpp:45</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00183">arm_compute::test::validation::act_info</a>, <a class="el" href="_error_8h_source.xhtml#l00352">ARM_COMPUTE_ERROR</a>, <a class="el" href="_g_c_fill_border_kernel_8cpp_source.xhtml#l00060">GCFillBorderKernel::configure()</a>, <a class="el" href="_g_c_tensor_shift_kernel_8cpp_source.xhtml#l00045">GCTensorShiftKernel::configure()</a>, <a class="el" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">arm_compute::CONSTANT</a>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00597">arm_compute::test::validation::conv_info</a>, <a class="el" href="_tensor_info_8h_source.xhtml#l00232">TensorInfo::dimension()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00041">CLTensor::info()</a>, <a class="el" href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">arm_compute::test::validation::input</a>, and <a class="el" href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00188">arm_compute::test::validation::weights</a>.</p> |
| |
| </div> |
| </div> |
| <a id="a92fe532c342ae2b07956a65520c05362"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a92fe532c342ae2b07956a65520c05362">◆ </a></span>run()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void run </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">final</span><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Run the kernels contained in the function. </p> |
| <p>For NEON kernels:</p><ul> |
| <li>Multi-threading is used for the kernels which are parallelisable.</li> |
| <li>By default std::thread::hardware_concurrency() threads are used.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl> |
| <p>For OpenCL kernels:</p><ul> |
| <li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li> |
| <li>The queue is then flushed.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd> |
| <dd> |
| Will call <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl> |
| |
| <p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p> |
| |
| <p class="definition">Definition at line <a class="el" href="_g_c_direct_convolution_layer_8cpp_source.xhtml#l00076">76</a> of file <a class="el" href="_g_c_direct_convolution_layer_8cpp_source.xhtml">GCDirectConvolutionLayer.cpp</a>.</p> |
| <div class="fragment"><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>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">dispatch</a>(_shift_handler, <span class="keyword">false</span>);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a2dcf87458fcfdfb5e9fdd369e0320d78">memory_barrier</a>();</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">dispatch</a>(_border_handler, <span class="keyword">false</span>);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a2dcf87458fcfdfb5e9fdd369e0320d78">memory_barrier</a>();</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">dispatch</a>(*_kernel);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a2dcf87458fcfdfb5e9fdd369e0320d78">memory_barrier</a>();</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">dispatch</a>(_shift_handler);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> }</div><div class="ttc" id="classarm__compute_1_1_g_c_scheduler_xhtml_a66a29e27a51a13250143981b0ee4ad19"><div class="ttname"><a href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">arm_compute::GCScheduler::dispatch</a></div><div class="ttdeci">void dispatch(IGCKernel &kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_scheduler_8cpp_source.xhtml#l00077">GCScheduler.cpp:77</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_scheduler_xhtml_a2dcf87458fcfdfb5e9fdd369e0320d78"><div class="ttname"><a href="classarm__compute_1_1_g_c_scheduler.xhtml#a2dcf87458fcfdfb5e9fdd369e0320d78">arm_compute::GCScheduler::memory_barrier</a></div><div class="ttdeci">void memory_barrier()</div><div class="ttdoc">Defines a barrier ordering memory transactions.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_scheduler_8cpp_source.xhtml#l00086">GCScheduler.cpp:86</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_scheduler_xhtml_a9c5f715748222ab9607cc52134b36b0b"><div class="ttname"><a href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">arm_compute::GCScheduler::get</a></div><div class="ttdeci">static GCScheduler & get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_scheduler_8cpp_source.xhtml#l00070">GCScheduler.cpp:70</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_g_c_scheduler_8cpp_source.xhtml#l00077">GCScheduler::dispatch()</a>, <a class="el" href="_g_c_scheduler_8cpp_source.xhtml#l00070">GCScheduler::get()</a>, and <a class="el" href="_g_c_scheduler_8cpp_source.xhtml#l00086">GCScheduler::memory_barrier()</a>.</p> |
| |
| </div> |
| </div> |
| <hr/>The documentation for this class was generated from the following files:<ul> |
| <li>arm_compute/runtime/GLES_COMPUTE/functions/<a class="el" href="_g_c_direct_convolution_layer_8h_source.xhtml">GCDirectConvolutionLayer.h</a></li> |
| <li>src/runtime/GLES_COMPUTE/functions/<a class="el" href="_g_c_direct_convolution_layer_8cpp_source.xhtml">GCDirectConvolutionLayer.cpp</a></li> |
| </ul> |
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| <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.15 </li> |
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