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| <a href="#pub-methods">Public Member Functions</a> </div> |
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| <div class="title">GCSoftmaxLayer Class Reference</div> </div> |
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| |
| <p>Basic function to compute a SoftmaxLayer. |
| <a href="classarm__compute_1_1_g_c_softmax_layer.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_g_c_softmax_layer_8h_source.xhtml">GCSoftmaxLayer.h</a>></code></p> |
| <div class="dynheader"> |
| Collaboration diagram for GCSoftmaxLayer:</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:a4c3d471a20099610ef1d617dbaf4b2d6"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_softmax_layer.xhtml#a4c3d471a20099610ef1d617dbaf4b2d6">GCSoftmaxLayer</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:a4c3d471a20099610ef1d617dbaf4b2d6"><td class="mdescLeft"> </td><td class="mdescRight">Constructor. <a href="#a4c3d471a20099610ef1d617dbaf4b2d6">More...</a><br /></td></tr> |
| <tr class="separator:a4c3d471a20099610ef1d617dbaf4b2d6"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a87e0f86361e9b6d237464d91ce76fbfa"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_g_c_softmax_layer.xhtml#a87e0f86361e9b6d237464d91ce76fbfa">configure</a> (const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *input, <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> *output, float beta=1.0f, size_t axis=1)</td></tr> |
| <tr class="memdesc:a87e0f86361e9b6d237464d91ce76fbfa"><td class="mdescLeft"> </td><td class="mdescRight">Set the input and output tensors. <a href="#a87e0f86361e9b6d237464d91ce76fbfa">More...</a><br /></td></tr> |
| <tr class="separator:a87e0f86361e9b6d237464d91ce76fbfa"><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_g_c_softmax_layer.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> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>Basic function to compute a SoftmaxLayer. </p> |
| <p>Softmax is calculated by : </p><p class="formulaDsp"> |
| \[ out = exp(x - max(x)) / sum(exp(x - max(x))) \] |
| </p> |
| <p>This function runs the following kernels:</p><ol type="1"> |
| <li><a class="el" href="classarm__compute_1_1_g_c_logits1_d_max_kernel.xhtml">GCLogits1DMaxKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_g_c_logits1_d_shift_exp_sum_kernel.xhtml">GCLogits1DShiftExpSumKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_g_c_logits1_d_norm_kernel.xhtml">GCLogits1DNormKernel</a> </li> |
| </ol> |
| |
| <p class="definition">Definition at line <a class="el" href="_g_c_softmax_layer_8h_source.xhtml#l00046">46</a> of file <a class="el" href="_g_c_softmax_layer_8h_source.xhtml">GCSoftmaxLayer.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a id="a4c3d471a20099610ef1d617dbaf4b2d6"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a4c3d471a20099610ef1d617dbaf4b2d6">◆ </a></span>GCSoftmaxLayer()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_g_c_softmax_layer.xhtml">GCSoftmaxLayer</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="_g_c_softmax_layer_8cpp_source.xhtml#l00032">32</a> of file <a class="el" href="_g_c_softmax_layer_8cpp_source.xhtml">GCSoftmaxLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  : _memory_group(std::move(memory_manager)), _max_kernel(), _shift_exp_sum_kernel(), _norm_kernel(), _max(), _sum(), _tmp()</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> {</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <h2 class="groupheader">Member Function Documentation</h2> |
| <a id="a87e0f86361e9b6d237464d91ce76fbfa"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a87e0f86361e9b6d237464d91ce76fbfa">◆ </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">const <a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> * </td> |
| <td class="paramname"><em>input</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_g_c_tensor.xhtml">IGCTensor</a> * </td> |
| <td class="paramname"><em>output</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">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]</td><td class="paramname">input</td><td>Source tensor. Data types supported: F16/F32 </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. Only beta = 1 is supported </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">axis</td><td>(Optional) Reduction axis. 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> |
| <dl class="section note"><dt>Note</dt><dd>The value of <code>axis</code> must be always 1 for GLES </dd></dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_g_c_softmax_layer_8cpp_source.xhtml#l00037">37</a> of file <a class="el" href="_g_c_softmax_layer_8cpp_source.xhtml">GCSoftmaxLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(beta, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a>);</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>  <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(beta != 1.0f);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#accc088009d44c521706aa98d6387ee21">axis</a> != 1, <span class="stringliteral">"Axis must be 1 for GLES"</span>);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// Create intermediate tensors shapes</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  _tmp.<a class="code" href="classarm__compute_1_1_g_c_tensor.xhtml#a44d1d7d909047fe63f5f6c11a9849986">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>(), input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">num_channels</a>(), input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>()));</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a> = input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.set(0, 1);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> tensor_info_max_sum(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">num_channels</a>(), input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>());</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  _max.<a class="code" href="classarm__compute_1_1_g_c_tensor.xhtml#a44d1d7d909047fe63f5f6c11a9849986">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(tensor_info_max_sum);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  _sum.<a class="code" href="classarm__compute_1_1_g_c_tensor.xhtml#a44d1d7d909047fe63f5f6c11a9849986">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(tensor_info_max_sum);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_tmp);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_max);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&_sum);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="comment">// Configure Kernels</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  _max_kernel.<a class="code" href="classarm__compute_1_1_g_c_logits1_d_max_kernel.xhtml#aa029e9740bc43eb3301316be76be3b7e">configure</a>(input, &_max);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  _shift_exp_sum_kernel.<a class="code" href="classarm__compute_1_1_g_c_logits1_d_shift_exp_sum_kernel.xhtml#a9b315185b36dd900eb209d005d630310">configure</a>(input, &_max, &_tmp, &_sum);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  _norm_kernel.<a class="code" href="classarm__compute_1_1_g_c_logits1_d_norm_kernel.xhtml#adeaa28cbd0f25f372fca145853a763ad">configure</a>(&_tmp, &_sum, output);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// Allocate intermediate buffers</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  _tmp.<a class="code" href="classarm__compute_1_1_g_c_tensor.xhtml#a44d1d7d909047fe63f5f6c11a9849986">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#aa8a4946cd749d482dd996874d295af85">allocate</a>();</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  _max.<a class="code" href="classarm__compute_1_1_g_c_tensor.xhtml#a44d1d7d909047fe63f5f6c11a9849986">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#aa8a4946cd749d482dd996874d295af85">allocate</a>();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  _sum.<a class="code" href="classarm__compute_1_1_g_c_tensor.xhtml#a44d1d7d909047fe63f5f6c11a9849986">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#aa8a4946cd749d482dd996874d295af85">allocate</a>();</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> }</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_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div> |
| <div class="ttc" id="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_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#l00337">Error.h:337</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_allocator_xhtml_af36143939a43fa124312e395975091ed"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">arm_compute::ITensorAllocator::init</a></div><div class="ttdeci">void init(const TensorInfo &input, size_t alignment=0)</div><div class="ttdoc">Initialize a tensor based on the passed TensorInfo.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator.cpp:38</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</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#l00160">Error.h:160</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_memory_group_base_xhtml_ac1f67376afb7822f262a0174ef4a3104"><div class="ttname"><a href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">arm_compute::MemoryGroupBase::manage</a></div><div class="ttdeci">void manage(TensorType *obj)</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_base_8h_source.xhtml#l00102">MemoryGroupBase.h:102</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape & tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</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_i_tensor_allocator_xhtml_aa8a4946cd749d482dd996874d295af85"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_allocator.xhtml#aa8a4946cd749d482dd996874d295af85">arm_compute::ITensorAllocator::allocate</a></div><div class="ttdeci">virtual void allocate()=0</div><div class="ttdoc">Interface to be implemented by the child class to allocate the tensor.</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#l00789">Validate.h:789</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_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="classarm__compute_1_1_g_c_logits1_d_max_kernel_xhtml_aa029e9740bc43eb3301316be76be3b7e"><div class="ttname"><a href="classarm__compute_1_1_g_c_logits1_d_max_kernel.xhtml#aa029e9740bc43eb3301316be76be3b7e">arm_compute::GCLogits1DMaxKernel::configure</a></div><div class="ttdeci">void configure(const IGCTensor *input, IGCTensor *output)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_softmax_layer_kernel_8cpp_source.xhtml#l00042">GCSoftmaxLayerKernel.cpp:42</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_logits1_d_shift_exp_sum_kernel_xhtml_a9b315185b36dd900eb209d005d630310"><div class="ttname"><a href="classarm__compute_1_1_g_c_logits1_d_shift_exp_sum_kernel.xhtml#a9b315185b36dd900eb209d005d630310">arm_compute::GCLogits1DShiftExpSumKernel::configure</a></div><div class="ttdeci">void configure(const IGCTensor *input, const IGCTensor *max, IGCTensor *output, IGCTensor *sum)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_softmax_layer_kernel_8cpp_source.xhtml#l00107">GCSoftmaxLayerKernel.cpp:107</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_tensor_xhtml_a44d1d7d909047fe63f5f6c11a9849986"><div class="ttname"><a href="classarm__compute_1_1_g_c_tensor.xhtml#a44d1d7d909047fe63f5f6c11a9849986">arm_compute::GCTensor::allocator</a></div><div class="ttdeci">ITensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_tensor_8cpp_source.xhtml#l00034">GCTensor.cpp:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_logits1_d_norm_kernel_xhtml_adeaa28cbd0f25f372fca145853a763ad"><div class="ttname"><a href="classarm__compute_1_1_g_c_logits1_d_norm_kernel.xhtml#adeaa28cbd0f25f372fca145853a763ad">arm_compute::GCLogits1DNormKernel::configure</a></div><div class="ttdeci">void configure(const IGCTensor *input, const IGCTensor *sum, IGCTensor *output)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_softmax_layer_kernel_8cpp_source.xhtml#l00201">GCSoftmaxLayerKernel.cpp:201</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_ad7829ae79223ab87f9da4c0bd7d229ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">arm_compute::ITensorInfo::num_channels</a></div><div class="ttdeci">virtual size_t num_channels() const =0</div><div class="ttdoc">The number of channels for each tensor element.</div></div> |
| <div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00328">Error.h:328</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="classarm__compute_1_1_i_tensor_allocator.xhtml#aa8a4946cd749d482dd996874d295af85">ITensorAllocator::allocate()</a>, <a class="el" href="_g_c_tensor_8cpp_source.xhtml#l00034">GCTensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00337">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00789">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>, <a class="el" href="_error_8h_source.xhtml#l00328">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="_error_8h_source.xhtml#l00160">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="_g_c_softmax_layer_kernel_8cpp_source.xhtml#l00042">GCLogits1DMaxKernel::configure()</a>, <a class="el" href="_g_c_softmax_layer_kernel_8cpp_source.xhtml#l00107">GCLogits1DShiftExpSumKernel::configure()</a>, <a class="el" href="_g_c_softmax_layer_kernel_8cpp_source.xhtml#l00201">GCLogits1DNormKernel::configure()</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#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::F16</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="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator::init()</a>, <a class="el" href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase< TensorType >::manage()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">ITensorInfo::num_channels()</a>, <a class="el" href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00097">arm_compute::test::validation::shape</a>, and <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">ITensorInfo::tensor_shape()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="validation_2_g_l_e_s___c_o_m_p_u_t_e_2_softmax_layer_8cpp_source.xhtml#l00060">arm_compute::test::validation::DATA_TEST_CASE()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="ad1717410afd0be936c6213a63c8005fb"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">◆ </a></span>run()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void run </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Run the kernels contained in the function. </p> |
| <p>For NEON kernels:</p><ul> |
| <li>Multi-threading is used for the kernels which are parallelisable.</li> |
| <li>By default std::thread::hardware_concurrency() threads are used.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl> |
| <p>For OpenCL kernels:</p><ul> |
| <li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li> |
| <li>The queue is then flushed.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd> |
| <dd> |
| Will call <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl> |
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| <p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p> |
| |
| <p class="definition">Definition at line <a class="el" href="_g_c_softmax_layer_8cpp_source.xhtml#l00070">70</a> of file <a class="el" href="_g_c_softmax_layer_8cpp_source.xhtml">GCSoftmaxLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <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="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">dispatch</a>(_max_kernel, <span class="keyword">false</span>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a2dcf87458fcfdfb5e9fdd369e0320d78">memory_barrier</a>();</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">dispatch</a>(_shift_exp_sum_kernel, <span class="keyword">false</span>);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a2dcf87458fcfdfb5e9fdd369e0320d78">memory_barrier</a>();</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">GCScheduler::get</a>().<a class="code" href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">dispatch</a>(_norm_kernel);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> }</div><div class="ttc" id="classarm__compute_1_1_g_c_scheduler_xhtml_a66a29e27a51a13250143981b0ee4ad19"><div class="ttname"><a href="classarm__compute_1_1_g_c_scheduler.xhtml#a66a29e27a51a13250143981b0ee4ad19">arm_compute::GCScheduler::dispatch</a></div><div class="ttdeci">void dispatch(IGCKernel &kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_scheduler_8cpp_source.xhtml#l00069">GCScheduler.cpp:69</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_scheduler_xhtml_a2dcf87458fcfdfb5e9fdd369e0320d78"><div class="ttname"><a href="classarm__compute_1_1_g_c_scheduler.xhtml#a2dcf87458fcfdfb5e9fdd369e0320d78">arm_compute::GCScheduler::memory_barrier</a></div><div class="ttdeci">void memory_barrier()</div><div class="ttdoc">Defines a barrier ordering memory transactions.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_scheduler_8cpp_source.xhtml#l00078">GCScheduler.cpp:78</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_g_c_scheduler_xhtml_a9c5f715748222ab9607cc52134b36b0b"><div class="ttname"><a href="classarm__compute_1_1_g_c_scheduler.xhtml#a9c5f715748222ab9607cc52134b36b0b">arm_compute::GCScheduler::get</a></div><div class="ttdeci">static GCScheduler & get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_g_c_scheduler_8cpp_source.xhtml#l00062">GCScheduler.cpp:62</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#l00046">IMemoryGroup.h:46</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_g_c_scheduler_8cpp_source.xhtml#l00069">GCScheduler::dispatch()</a>, <a class="el" href="_g_c_scheduler_8cpp_source.xhtml#l00062">GCScheduler::get()</a>, and <a class="el" href="_g_c_scheduler_8cpp_source.xhtml#l00078">GCScheduler::memory_barrier()</a>.</p> |
| |
| </div> |
| </div> |
| <hr/>The documentation for this class was generated from the following files:<ul> |
| <li>arm_compute/runtime/GLES_COMPUTE/functions/<a class="el" href="_g_c_softmax_layer_8h_source.xhtml">GCSoftmaxLayer.h</a></li> |
| <li>src/runtime/GLES_COMPUTE/functions/<a class="el" href="_g_c_softmax_layer_8cpp_source.xhtml">GCSoftmaxLayer.cpp</a></li> |
| </ul> |
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| <li class="footer">Generated on Mon Sep 2 2019 11:47:35 for Compute Library by |
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