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&#160;<span id="projectnumber">20.02.1</span>
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<a href="#pub-methods">Public Member Functions</a> </div>
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<div class="title">NECannyEdge Class Reference</div> </div>
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<p>Basic function to execute canny edge on NEON.
<a href="classarm__compute_1_1_n_e_canny_edge.xhtml#details">More...</a></p>
<p><code>#include &lt;<a class="el" href="_n_e_canny_edge_8h_source.xhtml">NECannyEdge.h</a>&gt;</code></p>
<div class="dynheader">
Collaboration diagram for NECannyEdge:</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:ae8ba206ac7ec00eb2f4a1624c047faaa"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml#ae8ba206ac7ec00eb2f4a1624c047faaa">NECannyEdge</a> (std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt; memory_manager=nullptr)</td></tr>
<tr class="memdesc:ae8ba206ac7ec00eb2f4a1624c047faaa"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <a href="#ae8ba206ac7ec00eb2f4a1624c047faaa">More...</a><br /></td></tr>
<tr class="separator:ae8ba206ac7ec00eb2f4a1624c047faaa"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a168eb5b6fa7992e8a6eea6d665f1c006"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml#a168eb5b6fa7992e8a6eea6d665f1c006">NECannyEdge</a> (const <a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a> &amp;)=delete</td></tr>
<tr class="memdesc:a168eb5b6fa7992e8a6eea6d665f1c006"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#a168eb5b6fa7992e8a6eea6d665f1c006">More...</a><br /></td></tr>
<tr class="separator:a168eb5b6fa7992e8a6eea6d665f1c006"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a325fac2836aecb2da2f86b7699e2b359"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml#a325fac2836aecb2da2f86b7699e2b359">operator=</a> (const <a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a> &amp;)=delete</td></tr>
<tr class="memdesc:a325fac2836aecb2da2f86b7699e2b359"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#a325fac2836aecb2da2f86b7699e2b359">More...</a><br /></td></tr>
<tr class="separator:a325fac2836aecb2da2f86b7699e2b359"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0626bbb35eb3e06a00802bbfeecf4f47"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml#a0626bbb35eb3e06a00802bbfeecf4f47">configure</a> (<a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, int32_t upper_thr, int32_t lower_thr, int32_t gradient_size, int32_t norm_type, <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> border_mode, uint8_t constant_border_value=0)</td></tr>
<tr class="memdesc:a0626bbb35eb3e06a00802bbfeecf4f47"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialise the function's source, destination, thresholds, gradient size, normalization type and border mode. <a href="#a0626bbb35eb3e06a00802bbfeecf4f47">More...</a><br /></td></tr>
<tr class="separator:a0626bbb35eb3e06a00802bbfeecf4f47"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr>
<tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Run the kernels contained in the function. <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br /></td></tr>
<tr class="separator:ad1717410afd0be936c6213a63c8005fb"><td class="memSeparator" colspan="2">&#160;</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="-"/>&#160;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&#160;</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">&#160;</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">&#160;</td></tr>
<tr class="memitem:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</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">&#160;</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">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Basic function to execute canny edge on NEON. </p>
<p>This function calls the following NEON kernels and functions:</p>
<ol type="1">
<li><a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a> (if border_mode == REPLICATE or border_mode == CONSTANT)</li>
<li><a class="el" href="classarm__compute_1_1_n_e_sobel3x3.xhtml">NESobel3x3</a> (if gradient_size == 3) or <a class="el" href="classarm__compute_1_1_n_e_sobel5x5.xhtml">NESobel5x5</a> (if gradient_size == 5) or <a class="el" href="classarm__compute_1_1_n_e_sobel7x7.xhtml">NESobel7x7</a> (if gradient_size == 7)</li>
<li><a class="el" href="classarm__compute_1_1_n_e_gradient_kernel.xhtml">NEGradientKernel</a></li>
<li><a class="el" href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml">NEEdgeNonMaxSuppressionKernel</a></li>
<li><a class="el" href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml">NEEdgeTraceKernel</a> </li>
</ol>
<p class="definition">Definition at line <a class="el" href="_n_e_canny_edge_8h_source.xhtml#l00053">53</a> of file <a class="el" href="_n_e_canny_edge_8h_source.xhtml">NECannyEdge.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="ae8ba206ac7ec00eb2f4a1624c047faaa"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ae8ba206ac7ec00eb2f4a1624c047faaa">&#9670;&nbsp;</a></span>NECannyEdge() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a> </td>
<td>(</td>
<td class="paramtype">std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt;&#160;</td>
<td class="paramname"><em>memory_manager</em> = <code>nullptr</code></td><td>)</td>
<td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Constructor. </p>
<p>Initialize Sobel kernel to nullptr.</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">memory_manager</td><td>(Optional) <a class="el" href="classarm__compute_1_1_memory.xhtml" title="CPU implementation of memory object.">Memory</a> manager. </td></tr>
</table>
</dd>
</dl>
<p class="definition">Definition at line <a class="el" href="_n_e_canny_edge_8cpp_source.xhtml#l00045">45</a> of file <a class="el" href="_n_e_canny_edge_8cpp_source.xhtml">NECannyEdge.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; : _memory_group(std::move(memory_manager)),</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; _sobel(),</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; _gradient(),</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; _non_max_suppr(),</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; _edge_trace(),</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; _border_mag_gradient(),</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; _border_edge_trace(),</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; _gx(),</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; _gy(),</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; _magnitude(),</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; _phase(),</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; _nonmax(),</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; _output(<span class="keyword">nullptr</span>)</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;}</div></div><!-- fragment -->
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<a id="a168eb5b6fa7992e8a6eea6d665f1c006"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a168eb5b6fa7992e8a6eea6d665f1c006">&#9670;&nbsp;</a></span>NECannyEdge() <span class="overload">[2/2]</span></h2>
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<td class="mlabels-left">
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<tr>
<td class="memname"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a> </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a> &amp;&#160;</td>
<td class="paramname"></td><td>)</td>
<td></td>
</tr>
</table>
</td>
<td class="mlabels-right">
<span class="mlabels"><span class="mlabel">delete</span></span> </td>
</tr>
</table>
</div><div class="memdoc">
<p>Prevent instances of this class from being copied (As this class contains pointers) </p>
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a id="a0626bbb35eb3e06a00802bbfeecf4f47"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a0626bbb35eb3e06a00802bbfeecf4f47">&#9670;&nbsp;</a></span>configure()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
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<td class="memname">void configure </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
<td class="paramname"><em>input</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
<td class="paramname"><em>output</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>upper_thr</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>lower_thr</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>gradient_size</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>norm_type</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a>&#160;</td>
<td class="paramname"><em>border_mode</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">uint8_t&#160;</td>
<td class="paramname"><em>constant_border_value</em> = <code>0</code>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Initialise the function's source, destination, thresholds, gradient size, normalization type and border mode. </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. Data type supported: U8. (Written to only for <code>border_mode</code> != UNDEFINED) </td></tr>
<tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Data type supported: U8. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">upper_thr</td><td>Upper threhold used for the hysteresis </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">lower_thr</td><td>Lower threshold used for the hysteresis. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">gradient_size</td><td>Gradient size (3, 5 or 7) </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">norm_type</td><td>Normalization type. If 1, L1-Norm otherwise L2-Norm </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">border_mode</td><td>Border mode to use for the convolution. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">constant_border_value</td><td>(Optional) Constant value to use for borders if border_mode is set to CONSTANT. </td></tr>
</table>
</dd>
</dl>
<p class="definition">Definition at line <a class="el" href="_n_e_canny_edge_8cpp_source.xhtml#l00062">62</a> of file <a class="el" href="_n_e_canny_edge_8cpp_source.xhtml">NECannyEdge.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;{</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, output);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(output, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((1 != norm_type) &amp;&amp; (2 != norm_type));</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((gradient_size != 3) &amp;&amp; (gradient_size != 5) &amp;&amp; (gradient_size != 7));</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((lower_thr &lt; 0) || (lower_thr &gt;= upper_thr));</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; _output = output;</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; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a> = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;tensor_shape();</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> gradient_info;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> magnitude_info;</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; <span class="comment">// Initialize images</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">if</span>(gradient_size &lt; 7)</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; gradient_info.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">Format::S16</a>);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; magnitude_info.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">Format::U16</a>);</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; gradient_info.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">Format::S32</a>);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; magnitude_info.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">Format::U32</a>);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; }</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; _gx.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(gradient_info);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; _gy.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(gradient_info);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; _magnitude.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(magnitude_info);</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; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">Format::U8</a>);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; _phase.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; _nonmax.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_gx);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_gy);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="comment">// Configure/Init sobelNxN</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordflow">if</span>(gradient_size == 3)</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">auto</span> k = arm_compute::support::cpp14::make_unique&lt;NESobel3x3&gt;();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; k-&gt;configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &amp;_gx, &amp;_gy, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; _sobel = std::move(k);</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> <span class="keywordflow">if</span>(gradient_size == 5)</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="keyword">auto</span> k = arm_compute::support::cpp14::make_unique&lt;NESobel5x5&gt;();</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; k-&gt;configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &amp;_gx, &amp;_gy, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; _sobel = std::move(k);</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; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(gradient_size == 7)</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">auto</span> k = arm_compute::support::cpp14::make_unique&lt;NESobel7x7&gt;();</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; k-&gt;configure(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &amp;_gx, &amp;_gy, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; _sobel = std::move(k);</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; <span class="keywordflow">else</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <a class="code" href="_error_8h.xhtml#abd040a16dc0dbc75733e07aff93048a8">ARM_COMPUTE_ERROR_VAR</a>(<span class="stringliteral">&quot;Gradient size %+&quot;</span> PRId32 <span class="stringliteral">&quot; not supported\n&quot;</span>, gradient_size);</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;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_magnitude);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_phase);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="comment">// Configure gradient</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique&lt;NEGradientKernel&gt;();</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; k-&gt;configure(&amp;_gx, &amp;_gy, &amp;_magnitude, &amp;_phase, norm_type);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; _gradient = std::move(k);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; _gx.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; _gy.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_nonmax);</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; <span class="comment">// Configure non-maxima suppression</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; _non_max_suppr.<a class="code" href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml#a57a36344e261edfdfa97b19ac40b7c30">configure</a>(&amp;_magnitude, &amp;_phase, &amp;_nonmax, upper_thr, lower_thr, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a> == <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">BorderMode::UNDEFINED</a>);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="comment">// Fill border around magnitude image as non-maxima suppression will access</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="comment">// it. If border mode is undefined filling the border is a nop.</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; _border_mag_gradient.<a class="code" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml#a12f5fc5a4fc18544922aebb0fcbf4eb6">configure</a>(&amp;_magnitude, _non_max_suppr.<a class="code" href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; _phase.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; _magnitude.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</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="comment">// Configure edge tracing</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; _edge_trace.<a class="code" href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml#a9daf8026e68559806afe7d0aa12693d6">configure</a>(&amp;_nonmax, output);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="comment">// Fill border with &quot;No edge&quot; to stop recursion in edge trace</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; _border_edge_trace.<a class="code" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml#a12f5fc5a4fc18544922aebb0fcbf4eb6">configure</a>(&amp;_nonmax, _edge_trace.<a class="code" href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>(), <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">BorderMode::CONSTANT</a>, static_cast&lt;float&gt;(0.f));</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="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; _nonmax.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160;}</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_absolute_difference_8cpp_source.xhtml#l00097">AbsoluteDifference.cpp:97</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#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a3fc6adad84b23f10d54d5a7b6928f872"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">arm_compute::TensorAllocator::init</a></div><div class="ttdeci">void init(const TensorAllocator &amp;allocator, const Coordinates &amp;coords, TensorInfo &amp;sub_info)</div><div class="ttdoc">Shares the same backing memory with another tensor allocator, while the tensor info might be differen...</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00108">TensorAllocator.cpp:108</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">1 channel, 1 U8 per channel</div></div>
<div class="ttc" id="_error_8h_xhtml_abd040a16dc0dbc75733e07aff93048a8"><div class="ttname"><a href="_error_8h.xhtml#abd040a16dc0dbc75733e07aff93048a8">ARM_COMPUTE_ERROR_VAR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_VAR(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#l00346">Error.h:346</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00466">Error.h:466</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 U16 per channel</div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_fill_border_kernel_xhtml_a12f5fc5a4fc18544922aebb0fcbf4eb6"><div class="ttname"><a href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml#a12f5fc5a4fc18544922aebb0fcbf4eb6">arm_compute::NEFillBorderKernel::configure</a></div><div class="ttdeci">void configure(ITensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &amp;constant_border_value=PixelValue())</div><div class="ttdoc">Initialise the function.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_fill_border_kernel_8cpp_source.xhtml#l00098">NEFillBorderKernel.cpp:98</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel_xhtml_a423f9a45a52983b4de5e2b347f4369c7"><div class="ttname"><a href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">arm_compute::NEEdgeNonMaxSuppressionKernel::border_size</a></div><div class="ttdeci">BorderSize border_size() const override</div><div class="ttdoc">The size of the border for that kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l00965">NECannyEdgeKernel.cpp:965</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_xhtml_adbd0cf83a8e1b335a9bf405a8e5019fa"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">arm_compute::Tensor::allocator</a></div><div class="ttdeci">TensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8cpp_source.xhtml#l00048">Tensor.cpp:48</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="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 S32 per channel</div></div>
<div class="ttc" id="classarm__compute_1_1_memory_group_xhtml_a6fc0a49304c152c20a0f6df0634fb3cd"><div class="ttname"><a href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">arm_compute::MemoryGroup::manage</a></div><div class="ttdeci">void manage(IMemoryManageable *obj) override</div><div class="ttdoc">Sets a object to be managed by the given memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_8h_source.xhtml#l00079">MemoryGroup.h:79</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5471e46933e7a9c4709972d91fc4ea65"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">arm_compute::test::validation::border_mode</a></div><div class="ttdeci">border_mode</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00118">Convolution.cpp:118</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 U32 per channel</div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_edge_trace_kernel_xhtml_a423f9a45a52983b4de5e2b347f4369c7"><div class="ttname"><a href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">arm_compute::NEEdgeTraceKernel::border_size</a></div><div class="ttdeci">BorderSize border_size() const override</div><div class="ttdoc">The size of the border for that kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l01049">NECannyEdgeKernel.cpp:1049</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::TensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of CPU memory.</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00133">TensorAllocator.cpp:133</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel_xhtml_a57a36344e261edfdfa97b19ac40b7c30"><div class="ttname"><a href="classarm__compute_1_1_n_e_edge_non_max_suppression_kernel.xhtml#a57a36344e261edfdfa97b19ac40b7c30">arm_compute::NEEdgeNonMaxSuppressionKernel::configure</a></div><div class="ttdeci">void configure(const ITensor *magnitude, const ITensor *phase, ITensor *output, int32_t upper_thr, int32_t lower_thr, bool border_undefined)</div><div class="ttdoc">Initialise the kernel's sources, destination and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l00970">NECannyEdgeKernel.cpp:970</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 S16 per channel</div></div>
<div class="ttc" id="_validate_8h_xhtml_aadf5c9cff86327b96d88d04649d9715e"><div class="ttname"><a href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00790">Validate.h:790</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_ad6b64f33be1e66dcf7612483ffb8fd63"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">arm_compute::TensorInfo::init</a></div><div class="ttdeci">void init(Format format)</div><div class="ttdoc">Initialize the tensor info with just a format.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_tensor_info_8cpp_source.xhtml#l00107">TensorInfo.cpp:107</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</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="classarm__compute_1_1_n_e_edge_trace_kernel_xhtml_a9daf8026e68559806afe7d0aa12693d6"><div class="ttname"><a href="classarm__compute_1_1_n_e_edge_trace_kernel.xhtml#a9daf8026e68559806afe7d0aa12693d6">arm_compute::NEEdgeTraceKernel::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output)</div><div class="ttdoc">Initialise the kernel's source, destination and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l01059">NECannyEdgeKernel.cpp:1059</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">arm_compute::BorderMode::UNDEFINED</a></div><div class="ttdoc">Borders are left undefined.</div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div>
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<p class="reference">References <a class="el" href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00133">TensorAllocator::allocate()</a>, <a class="el" href="runtime_2_tensor_8cpp_source.xhtml#l00048">Tensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00466">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00790">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>, <a class="el" href="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00346">ARM_COMPUTE_ERROR_VAR</a>, <a class="el" href="_c_l_2_convolution_8cpp_source.xhtml#l00118">arm_compute::test::validation::border_mode</a>, <a class="el" href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l00965">NEEdgeNonMaxSuppressionKernel::border_size()</a>, <a class="el" href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l01049">NEEdgeTraceKernel::border_size()</a>, <a class="el" href="_n_e_fill_border_kernel_8cpp_source.xhtml#l00098">NEFillBorderKernel::configure()</a>, <a class="el" href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l00970">NEEdgeNonMaxSuppressionKernel::configure()</a>, <a class="el" href="_n_e_canny_edge_kernel_8cpp_source.xhtml#l01059">NEEdgeTraceKernel::configure()</a>, <a class="el" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">arm_compute::CONSTANT</a>, <a class="el" href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">arm_compute::test::validation::info</a>, <a class="el" href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00108">TensorAllocator::init()</a>, <a class="el" href="src_2core_2_tensor_info_8cpp_source.xhtml#l00107">TensorInfo::init()</a>, <a class="el" href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">arm_compute::test::validation::input</a>, <a class="el" href="_memory_group_8h_source.xhtml#l00079">MemoryGroup::manage()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, <a class="el" href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00097">arm_compute::test::validation::shape</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::U16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::U32</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>, and <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">arm_compute::UNDEFINED</a>.</p>
<p class="reference">Referenced by <a class="el" href="_n_e_o_n_2_canny_edge_8cpp_source.xhtml#l00058">arm_compute::test::validation::DATA_TEST_CASE()</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#a325fac2836aecb2da2f86b7699e2b359">&#9670;&nbsp;</a></span>operator=()</h2>
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<td class="memname"><a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a>&amp; operator= </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_n_e_canny_edge.xhtml">NECannyEdge</a> &amp;&#160;</td>
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<span class="mlabels"><span class="mlabel">delete</span></span> </td>
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<p>Prevent instances of this class from being copied (As this class contains pointers) </p>
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<h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">&#9670;&nbsp;</a></span>run()</h2>
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<td class="memname">void run </td>
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<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="_n_e_canny_edge_8cpp_source.xhtml#l00162">162</a> of file <a class="el" href="_n_e_canny_edge_8cpp_source.xhtml">NECannyEdge.cpp</a>.</p>
<div class="fragment"><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; <a class="code" href="_error_8h.xhtml#a0b0eb3235749a2909dc5a101afe59a1b">ARM_COMPUTE_ERROR_ON_MSG</a>(_sobel == <span class="keyword">nullptr</span>, <span class="stringliteral">&quot;Unconfigured function&quot;</span>);</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; <a class="code" href="classarm__compute_1_1_memory_group_resource_scope.xhtml">MemoryGroupResourceScope</a> scope_mg(_memory_group);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <span class="comment">// Run sobelNxN</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; _sobel-&gt;run();</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; <span class="comment">// Run gradient</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(_gradient.get(), <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <span class="comment">// Fill border before non-maxima suppression. Nop for border mode undefined.</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_border_mag_gradient, <a class="code" href="classarm__compute_1_1_window.xhtml#a893d17b56b9abc4423ce26e9a24ac5dc">Window::DimZ</a>);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="comment">// Run non-maxima suppression</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_non_max_suppr, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160;</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(_output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>() == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; std::fill_n(_output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>(), _output-&gt;<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>(), 0);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; <span class="comment">// Fill border before edge trace</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_border_edge_trace, <a class="code" href="classarm__compute_1_1_window.xhtml#a893d17b56b9abc4423ce26e9a24ac5dc">Window::DimZ</a>);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; <span class="comment">// Run edge tracing</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_edge_trace, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160;}</div><div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00466">Error.h:466</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a0b0eb3235749a2909dc5a101afe59a1b"><div class="ttname"><a href="_error_8h.xhtml#a0b0eb3235749a2909dc5a101afe59a1b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond, msg)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00456">Error.h:456</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's metadata.</div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_ad2d402364fa822b0b7775081291eeca9"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">arm_compute::Window::DimY</a></div><div class="ttdeci">static constexpr size_t DimY</div><div class="ttdoc">Alias for dimension 1 also known as Y dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00045">Window.h:45</a></div></div>
<div class="ttc" id="classarm__compute_1_1_memory_group_resource_scope_xhtml"><div class="ttname"><a href="classarm__compute_1_1_memory_group_resource_scope.xhtml">arm_compute::MemoryGroupResourceScope</a></div><div class="ttdoc">Memory group resources scope handling class.</div><div class="ttdef"><b>Definition:</b> <a href="_i_memory_group_8h_source.xhtml#l00082">IMemoryGroup.h:82</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_i_scheduler_xhtml_a4e58f95544bd5ac6559a421671bd9842"><div class="ttname"><a href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">arm_compute::IScheduler::schedule</a></div><div class="ttdeci">virtual void schedule(ICPPKernel *kernel, const Hints &amp;hints)=0</div><div class="ttdoc">Runs the kernel in the same thread as the caller synchronously.</div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_a893d17b56b9abc4423ce26e9a24ac5dc"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a893d17b56b9abc4423ce26e9a24ac5dc">arm_compute::Window::DimZ</a></div><div class="ttdeci">static constexpr size_t DimZ</div><div class="ttdoc">Alias for dimension 2 also known as Z dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00047">Window.h:47</a></div></div>
<div class="ttc" id="classarm__compute_1_1_scheduler_xhtml_a0d63ca713bab377aabcfb63c192b8429"><div class="ttname"><a href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">arm_compute::Scheduler::get</a></div><div class="ttdeci">static IScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_scheduler_8cpp_source.xhtml#l00095">Scheduler.cpp:95</a></div></div>
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<p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00466">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_error_8h_source.xhtml#l00456">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">ITensor::buffer()</a>, <a class="el" href="_window_8h_source.xhtml#l00045">Window::DimY</a>, <a class="el" href="_window_8h_source.xhtml#l00047">Window::DimZ</a>, <a class="el" href="_scheduler_8cpp_source.xhtml#l00095">Scheduler::get()</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">IScheduler::schedule()</a>, and <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">ITensorInfo::total_size()</a>.</p>
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<hr/>The documentation for this class was generated from the following files:<ul>
<li>arm_compute/runtime/NEON/functions/<a class="el" href="_n_e_canny_edge_8h_source.xhtml">NECannyEdge.h</a></li>
<li>src/runtime/NEON/functions/<a class="el" href="_n_e_canny_edge_8cpp_source.xhtml">NECannyEdge.cpp</a></li>
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