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| <div class="title">NESoftmaxLayerGeneric< IS_LOG > Class Template Reference</div> </div> |
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| |
| <p>Basic function to compute a SoftmaxLayer and a Log SoftmaxLayer. |
| <a href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_n_e_softmax_layer_8h_source.xhtml">NESoftmaxLayer.h</a>></code></p> |
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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:a9bec0916cfb2b6eaa1bb206eb3f46137"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#a9bec0916cfb2b6eaa1bb206eb3f46137">NESoftmaxLayerGeneric</a> (std::shared_ptr< <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> > memory_manager=nullptr)</td></tr> |
| <tr class="memdesc:a9bec0916cfb2b6eaa1bb206eb3f46137"><td class="mdescLeft"> </td><td class="mdescRight">Constructor. <a href="#a9bec0916cfb2b6eaa1bb206eb3f46137">More...</a><br /></td></tr> |
| <tr class="separator:a9bec0916cfb2b6eaa1bb206eb3f46137"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ae373da97c14baa05a60780b468a5c627"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#ae373da97c14baa05a60780b468a5c627">NESoftmaxLayerGeneric</a> (const <a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> &)=delete</td></tr> |
| <tr class="memdesc:ae373da97c14baa05a60780b468a5c627"><td class="mdescLeft"> </td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#ae373da97c14baa05a60780b468a5c627">More...</a><br /></td></tr> |
| <tr class="separator:ae373da97c14baa05a60780b468a5c627"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a7c9adf4f66fd46e17547e59f262ad527"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#a7c9adf4f66fd46e17547e59f262ad527">NESoftmaxLayerGeneric</a> (<a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> &&)=default</td></tr> |
| <tr class="memdesc:a7c9adf4f66fd46e17547e59f262ad527"><td class="mdescLeft"> </td><td class="mdescRight">Default move constructor. <a href="#a7c9adf4f66fd46e17547e59f262ad527">More...</a><br /></td></tr> |
| <tr class="separator:a7c9adf4f66fd46e17547e59f262ad527"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a29487ad634792d69e1e9f2ceb93ef9a4"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#a29487ad634792d69e1e9f2ceb93ef9a4">operator=</a> (const <a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> &)=delete</td></tr> |
| <tr class="memdesc:a29487ad634792d69e1e9f2ceb93ef9a4"><td class="mdescLeft"> </td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#a29487ad634792d69e1e9f2ceb93ef9a4">More...</a><br /></td></tr> |
| <tr class="separator:a29487ad634792d69e1e9f2ceb93ef9a4"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a2802bc00e713c79bb276f9357bfc2183"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#a2802bc00e713c79bb276f9357bfc2183">operator=</a> (<a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> &&)=default</td></tr> |
| <tr class="memdesc:a2802bc00e713c79bb276f9357bfc2183"><td class="mdescLeft"> </td><td class="mdescRight">Default move assignment operator. <a href="#a2802bc00e713c79bb276f9357bfc2183">More...</a><br /></td></tr> |
| <tr class="separator:a2802bc00e713c79bb276f9357bfc2183"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aa4aee9a6c9abb0cfbcbf1727de23070c"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#aa4aee9a6c9abb0cfbcbf1727de23070c">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, float beta=1.0f, size_t axis=1)</td></tr> |
| <tr class="memdesc:aa4aee9a6c9abb0cfbcbf1727de23070c"><td class="mdescLeft"> </td><td class="mdescRight">Set the input and output tensors. <a href="#aa4aee9a6c9abb0cfbcbf1727de23070c">More...</a><br /></td></tr> |
| <tr class="separator:aa4aee9a6c9abb0cfbcbf1727de23070c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr> |
| <tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft"> </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"> </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><table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a> |
| Static Public Member Functions</h2></td></tr> |
| <tr class="memitem:a85db282920d24cd0f4dca6a439201a43"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#a85db282920d24cd0f4dca6a439201a43">validate</a> (const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, float beta=1.0f, size_t axis=1)</td></tr> |
| <tr class="memdesc:a85db282920d24cd0f4dca6a439201a43"><td class="mdescLeft"> </td><td class="mdescRight">Static function to check if given info will lead to a valid configuration of <a class="el" href="namespacearm__compute.xhtml#a4df2143ca0a3bdbbbc54b440a52541cd">NESoftmaxLayer</a>. <a href="#a85db282920d24cd0f4dca6a439201a43">More...</a><br /></td></tr> |
| <tr class="separator:a85db282920d24cd0f4dca6a439201a43"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><h3>template<bool IS_LOG = false><br /> |
| class arm_compute::NESoftmaxLayerGeneric< IS_LOG ></h3> |
| |
| <p>Basic function to compute a SoftmaxLayer and a Log SoftmaxLayer. </p> |
| <p>Softmax is calculated by : </p><p class="formulaDsp"> |
| \[ out = \frac{e^{x - max(x)}}{\sum{e^{x - max(x)}}} \] |
| </p> |
| <p>Log Softmax is calculated by : </p><p class="formulaDsp"> |
| \[ out = (x - max(x)) - \sum{e^{x - max(x)}} \] |
| </p> |
| <p>This function runs the following kernels:</p><ol type="1"> |
| <li><a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml">NELogits1DMaxKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_n_e_logits1_d_softmax_kernel.xhtml">NELogits1DSoftmaxKernel</a> </li> |
| </ol> |
| |
| <p class="definition">Definition at line <a class="el" href="_n_e_softmax_layer_8h_source.xhtml#l00053">53</a> of file <a class="el" href="_n_e_softmax_layer_8h_source.xhtml">NESoftmaxLayer.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a id="a9bec0916cfb2b6eaa1bb206eb3f46137"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a9bec0916cfb2b6eaa1bb206eb3f46137">◆ </a></span>NESoftmaxLayerGeneric() <span class="overload">[1/3]</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_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> </td> |
| <td>(</td> |
| <td class="paramtype">std::shared_ptr< <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> > </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 class="definition">Definition at line <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml#l00037">37</a> of file <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml">NESoftmaxLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  : _memory_group(std::move(memory_manager)), _max_kernel(), _softmax_kernel(), _flat_or_reshape_kernel_ptr(<span class="keyword">nullptr</span>), _fill_border_kernel(), _reshape_kernel(), _max(), _tmp(), _input_flattened(),</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  _output_flattened(), _needs_flattening(<span class="keyword">false</span>)</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> {</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a id="ae373da97c14baa05a60780b468a5c627"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ae373da97c14baa05a60780b468a5c627">◆ </a></span>NESoftmaxLayerGeneric() <span class="overload">[2/3]</span></h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a>< IS_LOG > & </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> |
| <a id="a7c9adf4f66fd46e17547e59f262ad527"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a7c9adf4f66fd46e17547e59f262ad527">◆ </a></span>NESoftmaxLayerGeneric() <span class="overload">[3/3]</span></h2> |
| |
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| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a> </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a>< IS_LOG > && </td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">default</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Default move constructor. </p> |
| |
| </div> |
| </div> |
| <h2 class="groupheader">Member Function Documentation</h2> |
| <a id="aa4aee9a6c9abb0cfbcbf1727de23070c"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#aa4aee9a6c9abb0cfbcbf1727de23070c">◆ </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_tensor.xhtml">ITensor</a> * </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> * </td> |
| <td class="paramname"><em>output</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">float </td> |
| <td class="paramname"><em>beta</em> = <code>1.0f</code>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">size_t </td> |
| <td class="paramname"><em>axis</em> = <code>1</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. Data types supported: QASYMM8/F16/F32. If the width is not a multiple of the internal processing block size, <a class="el" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml">NEFillBorderKernel</a> replicates the last value of each row to the nearest multiple. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Data types supported: same as <code>input</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">beta</td><td>(Optional) A scaling factor for the exponent. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">axis</td><td>(Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). It has the purpose of squashing the first <code>axis</code> dimensions together. For instance, given a [4x4x4x4] image, when <code>axis</code> is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml#l00074">74</a> of file <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml">NESoftmaxLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> {</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// Perform validation step</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <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="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(<a class="code" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#a85db282920d24cd0f4dca6a439201a43">NESoftmaxLayerGeneric::validate</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->info(), output->info(), beta, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a>));</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">// We don't need flattening only in the case the input is 2D and axis is 1</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  _needs_flattening = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a> != 1;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="comment">// If we are dealing with a 4D tensor, we will:</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="comment">// - Flatten the input, so that we end up with a [width*height*depth] * batches 2D tensor</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="comment">// - Execute all the pipeline (reduction + normalization) on the flattened tensor</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="comment">// - Reshape the flattened output into the real output</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordflow">if</span>(_needs_flattening)</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  {</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="comment">// Add to the memory manager _input_flattened</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_input_flattened);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="comment">// Configure _flatten_kernel and _input_flattened</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  configure_reshape_input_kernel(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, output, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a>);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  }</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">// We want to deal with a 2D input. Either it is the flattened version of the original input (4D case)</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="comment">// or it is the original input case (2D case)</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  ITensor *input_2D = (_needs_flattening ? &_input_flattened : <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="comment">// Create intermediate tensors shapes</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> TensorInfo <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae008e90eb6906fa3526213bc860f6cc5">input_info</a> = input_2D->info()->clone()->reset_padding().set_is_resizable(<span class="keyword">true</span>);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> tmp_data_type = <a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(input_2D->info()->data_type()) ? <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a> : input_2D->info()->data_type();</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  TensorInfo tensor_info_tmp(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae008e90eb6906fa3526213bc860f6cc5">input_info</a>.clone()->set_data_type(tmp_data_type));</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="comment">// Init intermediate tensors</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  TensorShape max_sum_shape = input_2D->info()->tensor_shape();</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  max_sum_shape.set(0, 1);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  _max.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><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#ae008e90eb6906fa3526213bc860f6cc5">input_info</a>.clone()->set_tensor_shape(max_sum_shape));</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  _tmp.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(tensor_info_tmp);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_max);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_tmp);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="comment">// Configure Kernels</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  _max_kernel.<a class="code" href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml#a83a344e60eb7db895953a942abf16628">configure</a>(input_2D, &_max);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keywordflow">if</span>(_needs_flattening)</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  {</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="comment">// Add to the memory manager _output_flattened</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_output_flattened);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// The normalization kernel stores the result in a flat output tensor</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  _softmax_kernel.configure(input_2D, &_max, &_output_flattened, beta, &_tmp);</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  _input_flattened.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="comment">// Reshape the flat output into the requested (4D) output</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  _reshape_kernel.<a class="code" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml#a83a344e60eb7db895953a942abf16628">configure</a>(&_output_flattened, output);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="comment">// Allocate the intermediate flat tensors</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  _output_flattened.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  }</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  {</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="comment">// Softmax 2D case</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  _fill_border_kernel.<a class="code" href="classarm__compute_1_1_n_e_fill_border_kernel.xhtml#a12f5fc5a4fc18544922aebb0fcbf4eb6">configure</a>(input_2D, _max_kernel.<a class="code" href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</a>(), <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a4ef59320fbe90fe47d40f1f71e4c5daa">BorderMode::REPLICATE</a>);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  _softmax_kernel.configure(input_2D, &_max, output, beta, &_tmp);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="comment">// Allocate intermediate buffers</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  _max.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  _tmp.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> }</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 &allocator, const Coordinates &coords, TensorInfo &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="classarm__compute_1_1_n_e_softmax_layer_generic_xhtml_a85db282920d24cd0f4dca6a439201a43"><div class="ttname"><a href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml#a85db282920d24cd0f4dca6a439201a43">arm_compute::NESoftmaxLayerGeneric::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta=1.0f, size_t axis=1)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NESoftmaxLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_softmax_layer_8cpp_source.xhtml#l00145">NESoftmaxLayer.cpp:145</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</div></div> |
| <div class="ttc" id="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00455">Error.h:455</a></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 &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_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="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_ae008e90eb6906fa3526213bc860f6cc5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ae008e90eb6906fa3526213bc860f6cc5">arm_compute::test::validation::input_info</a></div><div class="ttdeci">input_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00328">Winograd.cpp:328</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_logits1_d_max_kernel_xhtml_a83a344e60eb7db895953a942abf16628"><div class="ttname"><a href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml#a83a344e60eb7db895953a942abf16628">arm_compute::NELogits1DMaxKernel::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_softmax_layer_kernel_8cpp_source.xhtml#l00178">NESoftmaxLayerKernel.cpp:178</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_reshape_layer_kernel_xhtml_a83a344e60eb7db895953a942abf16628"><div class="ttname"><a href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml#a83a344e60eb7db895953a942abf16628">arm_compute::NEReshapeLayerKernel::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output)</div><div class="ttdoc">Set the input and output of the kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reshape_layer_kernel_8cpp_source.xhtml#l00074">NEReshapeLayerKernel.cpp:74</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01139">Utils.h:1139</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_1_1test_1_1validation_xhtml_accc088009d44c521706aa98d6387ee21"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">arm_compute::test::validation::axis</a></div><div class="ttdeci">axis</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_stack_layer_8cpp_source.xhtml#l00226">StackLayer.cpp:226</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_logits1_d_max_kernel_xhtml_a423f9a45a52983b4de5e2b347f4369c7"><div class="ttname"><a href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">arm_compute::NELogits1DMaxKernel::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_softmax_layer_kernel_8cpp_source.xhtml#l00173">NESoftmaxLayerKernel.cpp:173</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327a4ef59320fbe90fe47d40f1f71e4c5daa"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a4ef59320fbe90fe47d40f1f71e4c5daa">arm_compute::BorderMode::REPLICATE</a></div><div class="ttdoc">Pixels outside the image are assumed to have the same value as the closest image pixel.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00075">Types.h:75</a></div></div> |
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| <p class="reference">References <a class="el" href="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00455">ARM_COMPUTE_ERROR_THROW_ON</a>, <a class="el" href="_n_e_o_n_2_stack_layer_8cpp_source.xhtml#l00226">arm_compute::test::validation::axis</a>, <a class="el" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">ICloneable< T >::clone()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">ITensorInfo::data_type()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::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>, <a class="el" href="_c_l_2_winograd_8cpp_source.xhtml#l00328">arm_compute::test::validation::input_info</a>, <a class="el" href="arm__compute_2core_2_utils_8h_source.xhtml#l01139">arm_compute::is_data_type_quantized_asymmetric()</a>, <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a4ef59320fbe90fe47d40f1f71e4c5daa">arm_compute::REPLICATE</a>, <a class="el" href="_tensor_shape_8h_source.xhtml#l00078">TensorShape::set()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">ITensorInfo::tensor_shape()</a>, and <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml#l00145">NESoftmaxLayerGeneric< IS_LOG >::validate()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_n_e_o_n_2_softmax_layer_8cpp_source.xhtml#l00066">arm_compute::test::validation::DATA_TEST_CASE()</a>.</p> |
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| <a id="a29487ad634792d69e1e9f2ceb93ef9a4"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a29487ad634792d69e1e9f2ceb93ef9a4">◆ </a></span>operator=() <span class="overload">[1/2]</span></h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a>& operator= </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a>< IS_LOG > & </td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
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| </td> |
| <td class="mlabels-right"> |
| <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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| </div> |
| <a id="a2802bc00e713c79bb276f9357bfc2183"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a2802bc00e713c79bb276f9357bfc2183">◆ </a></span>operator=() <span class="overload">[2/2]</span></h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a>& operator= </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_n_e_softmax_layer_generic.xhtml">NESoftmaxLayerGeneric</a>< IS_LOG > && </td> |
| <td class="paramname"></td><td>)</td> |
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| <span class="mlabels"><span class="mlabel">default</span></span> </td> |
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| <p>Default move assignment operator. </p> |
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| <a id="ad1717410afd0be936c6213a63c8005fb"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">◆ </a></span>run()</h2> |
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| <td class="memname">void run </td> |
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| <td class="paramname"></td><td>)</td> |
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| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </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> |
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| <p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p> |
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| <p class="definition">Definition at line <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml#l00186">186</a> of file <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml">NESoftmaxLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> {</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  MemoryGroupResourceScope scope_mg(_memory_group);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordflow">if</span>(_needs_flattening)</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  {</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <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>(_flat_or_reshape_kernel_ptr.get(), <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <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>(&_fill_border_kernel, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <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>(&_max_kernel, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <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>(&_softmax_kernel, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keywordflow">if</span>(_needs_flattening)</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  {</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <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>(&_reshape_kernel, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  }</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> }</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_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 &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_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 & 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> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_window_8h_source.xhtml#l00045">Window::DimY</a>, <a class="el" href="_scheduler_8cpp_source.xhtml#l00095">Scheduler::get()</a>, and <a class="el" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">IScheduler::schedule()</a>.</p> |
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| <h2 class="memtitle"><span class="permalink"><a href="#a85db282920d24cd0f4dca6a439201a43">◆ </a></span>validate()</h2> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>input</em>, </td> |
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| <td class="paramkey"></td> |
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| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
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| <td class="paramtype">size_t </td> |
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| <p>Static function to check if given info will lead to a valid configuration of <a class="el" href="namespacearm__compute.xhtml#a4df2143ca0a3bdbbbc54b440a52541cd">NESoftmaxLayer</a>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor info. Data types supported: QASYMM8/F16/F32. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Destination tensor info. Data types supported: same as <code>input</code> </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">beta</td><td>(Optional) A scaling factor for the exponent. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">axis</td><td>(Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). It has the purpose of squashing the first <code>axis</code> dimensions together. For instance, given a [4x4x4x4] image, when <code>axis</code> is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image.</td></tr> |
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| <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl> |
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| <p class="definition">Definition at line <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml#l00145">145</a> of file <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml">NESoftmaxLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// Perform validation step</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_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="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="_error_8h.xhtml#a1c69762a42ab8add645d0a949b6f4b1f">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->num_dimensions() > 4, <span class="stringliteral">"Only up to 4 dimensions are supported"</span>);</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(beta);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(axis < 1 || input->num_dimensions() < <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// Create intermediate tensor info</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> tmp_data_type = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->data_type();</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keyword">const</span> TensorInfo tensor_info_tmp(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->clone()->set_data_type(tmp_data_type).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  TensorShape max_sum_shape = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->tensor_shape();</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  max_sum_shape.set(0, 1);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keyword">const</span> TensorInfo tensor_info_max_sum(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type).set_quantization_info(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->quantization_info()).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keyword">const</span> TensorInfo dont_care;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> needs_flattening = (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a> != 1);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> </div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">if</span>(needs_flattening)</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  {</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keyword">const</span> TensorShape shape_flatten = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#ad16b366db486fec63b6d962937ec4545">misc::shape_calculator::compute_softmax_shape</a>(<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#accc088009d44c521706aa98d6387ee21">axis</a>);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  TensorInfo tensor_info_flat(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>->clone()->set_tensor_shape(shape_flatten).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a> != 3)</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  {</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">NEReshapeLayerKernel::validate</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &tensor_info_flat));</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  }</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  {</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_n_e_flatten_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">NEFlattenLayerKernel::validate</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &tensor_info_flat));</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  }</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  }</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">NELogits1DMaxKernel::validate</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &tensor_info_max_sum));</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_n_e_logits1_d_softmax_kernel.xhtml#ae9a64d99f08581b961e1ac5a5fc46af8">NELogits1DSoftmaxKernel<IS_LOG>::validate</a>(&tensor_info_tmp, &tensor_info_max_sum, output, beta, &dont_care));</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">return</span> Status{};</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> }</div><div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00204">Error.h:204</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_ad16b366db486fec63b6d962937ec4545"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#ad16b366db486fec63b6d962937ec4545">arm_compute::misc::shape_calculator::compute_softmax_shape</a></div><div class="ttdeci">TensorShape compute_softmax_shape(const ITensorInfo *input, size_t axis=1)</div><div class="ttdoc">Calculate the softmax output shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l00605">ShapeCalculator.h:605</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00296">Error.h:296</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_n_e_logits1_d_softmax_kernel_xhtml_ae9a64d99f08581b961e1ac5a5fc46af8"><div class="ttname"><a href="classarm__compute_1_1_n_e_logits1_d_softmax_kernel.xhtml#ae9a64d99f08581b961e1ac5a5fc46af8">arm_compute::NELogits1DSoftmaxKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *max, const ITensorInfo *output, const float beta, const ITensorInfo *tmp)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NELogits1DSoftmaxKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_softmax_layer_kernel_8cpp_source.xhtml#l00648">NESoftmaxLayerKernel.cpp:648</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00152">Error.h:152</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_accc088009d44c521706aa98d6387ee21"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">arm_compute::test::validation::axis</a></div><div class="ttdeci">axis</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_stack_layer_8cpp_source.xhtml#l00226">StackLayer.cpp:226</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_reshape_layer_kernel_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_n_e_reshape_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::NEReshapeLayerKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NEReshapeLayerKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reshape_layer_kernel_8cpp_source.xhtml#l00091">NEReshapeLayerKernel.cpp:91</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a1c69762a42ab8add645d0a949b6f4b1f"><div class="ttname"><a href="_error_8h.xhtml#a1c69762a42ab8add645d0a949b6f4b1f">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MSG(cond, msg)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00244">Error.h:244</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_logits1_d_max_kernel_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_n_e_logits1_d_max_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::NELogits1DMaxKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NELogits1DMaxKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_softmax_layer_kernel_8cpp_source.xhtml#l00220">NESoftmaxLayerKernel.cpp:220</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_flatten_layer_kernel_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_n_e_flatten_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::NEFlattenLayerKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of NEFlattenLayerKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_flatten_layer_kernel_8cpp_source.xhtml#l00095">NEFlattenLayerKernel.cpp:95</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00075">Types.h:75</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00296">ARM_COMPUTE_RETURN_ERROR_ON</a>, <a class="el" href="_error_8h_source.xhtml#l00244">ARM_COMPUTE_RETURN_ERROR_ON_MSG</a>, <a class="el" href="_validate_8h_source.xhtml#l00163">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00204">ARM_COMPUTE_RETURN_ON_ERROR</a>, <a class="el" href="_error_8h_source.xhtml#l00152">ARM_COMPUTE_UNUSED</a>, <a class="el" href="_n_e_o_n_2_stack_layer_8cpp_source.xhtml#l00226">arm_compute::test::validation::axis</a>, <a class="el" href="_shape_calculator_8h_source.xhtml#l00605">arm_compute::misc::shape_calculator::compute_softmax_shape()</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="_n_e_reshape_layer_kernel_8cpp_source.xhtml#l00091">NEReshapeLayerKernel::validate()</a>, <a class="el" href="_n_e_softmax_layer_kernel_8cpp_source.xhtml#l00220">NELogits1DMaxKernel::validate()</a>, and <a class="el" href="_n_e_flatten_layer_kernel_8cpp_source.xhtml#l00095">NEFlattenLayerKernel::validate()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml#l00074">NESoftmaxLayerGeneric< IS_LOG >::configure()</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_softmax_layer_8h_source.xhtml">NESoftmaxLayer.h</a></li> |
| <li>src/runtime/NEON/functions/<a class="el" href="_n_e_softmax_layer_8cpp_source.xhtml">NESoftmaxLayer.cpp</a></li> |
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