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arm_compute v18.02
[platform/upstream/armcl.git] / documentation / functions_g.xhtml
diff --git a/documentation/functions_g.xhtml b/documentation/functions_g.xhtml
index a62f7c3..522323b 100644 (file)
--- a/documentation/functions_g.xhtml
+++ b/documentation/functions_g.xhtml
@@ -40,7 +40,7 @@
  <tr style="height: 56px;">
   <td style="padding-left: 0.5em;">
    <div id="projectname">Compute Library
-   &#160;<span id="projectnumber">17.12</span>
+   &#160;<span id="projectnumber">18.02</span>
    </div>
   </td>
  </tr>
@@ -173,6 +173,9 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 <li>GCActivationLayerKernel()
 : <a class="el" href="classarm__compute_1_1_g_c_activation_layer_kernel.xhtml#a678f75dfd5cfe14614f8072ebe1cc67d">GCActivationLayerKernel</a>
 </li>
+<li>GCArithmeticAdditionKernel()
+: <a class="el" href="classarm__compute_1_1_g_c_arithmetic_addition_kernel.xhtml#a3e5d5909a0c86adff50e9a527272afa6">GCArithmeticAdditionKernel</a>
+</li>
 <li>GCBatchNormalizationLayer()
 : <a class="el" href="classarm__compute_1_1_g_c_batch_normalization_layer.xhtml#ae46038d0e47ec316681667900c15517c">GCBatchNormalizationLayer</a>
 </li>
@@ -182,12 +185,27 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 <li>GCCol2ImKernel()
 : <a class="el" href="classarm__compute_1_1_g_c_col2_im_kernel.xhtml#a3e3035668c6d03b9bf68dca65222b7d9">GCCol2ImKernel</a>
 </li>
+<li>GCConvolutionLayer()
+: <a class="el" href="classarm__compute_1_1_g_c_convolution_layer.xhtml#ae6185d11854eebe4e07a612a6716a472">GCConvolutionLayer</a>
+</li>
+<li>GCConvolutionLayerReshapeWeights()
+: <a class="el" href="classarm__compute_1_1_g_c_convolution_layer_reshape_weights.xhtml#ab2cb1decf7fb2217d6f7b85c1c6b60a0">GCConvolutionLayerReshapeWeights</a>
+</li>
 <li>GCDepthConcatenateLayer()
 : <a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer.xhtml#a96b1abfc5ee6d10be7e8a525d6846f24">GCDepthConcatenateLayer</a>
 </li>
 <li>GCDepthConcatenateLayerKernel()
 : <a class="el" href="classarm__compute_1_1_g_c_depth_concatenate_layer_kernel.xhtml#a7fc9a4cd38bc7e934e279ed52163fc0e">GCDepthConcatenateLayerKernel</a>
 </li>
+<li>GCDepthwiseConvolutionLayer3x3()
+: <a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3.xhtml#a4bda9e07bd18e83b4ef18d3c7abb0632">GCDepthwiseConvolutionLayer3x3</a>
+</li>
+<li>GCDepthwiseConvolutionLayer3x3Kernel()
+: <a class="el" href="classarm__compute_1_1_g_c_depthwise_convolution_layer3x3_kernel.xhtml#a5b01f75ce20fddeb91acf0bfb9042ba3">GCDepthwiseConvolutionLayer3x3Kernel</a>
+</li>
+<li>GCDirectConvolutionLayer()
+: <a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer.xhtml#a457c6a685b2fe36fd12dd640f6155c31">GCDirectConvolutionLayer</a>
+</li>
 <li>GCDirectConvolutionLayerKernel()
 : <a class="el" href="classarm__compute_1_1_g_c_direct_convolution_layer_kernel.xhtml#ab55e3264789da35ae1297fefa4efed7c">GCDirectConvolutionLayerKernel&lt; kernel_size &gt;</a>
 </li>
@@ -198,7 +216,7 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 : <a class="el" href="classarm__compute_1_1_g_c_dropout_layer_kernel.xhtml#adf240c088ca0ffcbd66a7578bda3d777">GCDropoutLayerKernel</a>
 </li>
 <li>GCFillBorderKernel()
-: <a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml#a60bf5c7efeedbc8ffe5a7d6276db63a2">GCFillBorderKernel</a>
+: <a class="el" href="classarm__compute_1_1_g_c_fill_border_kernel.xhtml#a12fb6b653fe5096135017420a02e79b0">GCFillBorderKernel</a>
 </li>
 <li>GCFullyConnectedLayer()
 : <a class="el" href="classarm__compute_1_1_g_c_fully_connected_layer.xhtml#a72b2bdf0cae7f6e47b0d5f957de6d304">GCFullyConnectedLayer</a>
@@ -237,11 +255,20 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 : <a class="el" href="classarm__compute_1_1_g_c_normalization_layer.xhtml#a87b3f416afc5e40915e193d3f724edd5">GCNormalizationLayer</a>
 </li>
 <li>GCNormalizationLayerKernel()
-: <a class="el" href="classarm__compute_1_1_g_c_normalization_layer_kernel.xhtml#a99dd80fcfac9d5472703e3443deef308">GCNormalizationLayerKernel</a>
+: <a class="el" href="classarm__compute_1_1_g_c_normalization_layer_kernel.xhtml#ae1756c03bc72b902f3becf04a2cb725c">GCNormalizationLayerKernel</a>
+</li>
+<li>GCNormalizePlanarYUVLayer()
+: <a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer.xhtml#a14de8a41191a089a72c071eda4dd501a">GCNormalizePlanarYUVLayer</a>
+</li>
+<li>GCNormalizePlanarYUVLayerKernel()
+: <a class="el" href="classarm__compute_1_1_g_c_normalize_planar_y_u_v_layer_kernel.xhtml#a5767b9b46e4288fce05960d12d7d857c">GCNormalizePlanarYUVLayerKernel</a>
 </li>
 <li>GCPixelWiseMultiplicationKernel()
 : <a class="el" href="classarm__compute_1_1_g_c_pixel_wise_multiplication_kernel.xhtml#adefb2f4872f4d1890ace3aad8d7be409">GCPixelWiseMultiplicationKernel</a>
 </li>
+<li>GCPoolingLayer()
+: <a class="el" href="classarm__compute_1_1_g_c_pooling_layer.xhtml#a4b0897a9e97f3ffd1e202e20cf4404e3">GCPoolingLayer</a>
+</li>
 <li>GCPoolingLayerKernel()
 : <a class="el" href="classarm__compute_1_1_g_c_pooling_layer_kernel.xhtml#aebe262e2f3820f872a1393b751a72a27">GCPoolingLayerKernel</a>
 </li>
@@ -257,11 +284,23 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 <li>GCTensorAllocator()
 : <a class="el" href="classarm__compute_1_1_g_c_tensor_allocator.xhtml#a4c52d0475ea53645c122adac0ebde9ab">GCTensorAllocator</a>
 </li>
+<li>GCTensorShiftKernel()
+: <a class="el" href="classarm__compute_1_1_g_c_tensor_shift_kernel.xhtml#ab622a0c2dba7d8b8059bc5049f48f5ff">GCTensorShiftKernel</a>
+</li>
+<li>GCWeightsReshapeKernel()
+: <a class="el" href="classarm__compute_1_1_g_c_weights_reshape_kernel.xhtml#a29432f2725083d73e198001a805bb862">GCWeightsReshapeKernel</a>
+</li>
 <li>GEMMInfo()
 : <a class="el" href="classarm__compute_1_1_g_e_m_m_info.xhtml#ae70403792b9c2d7bdb0c57b5258b2efd">GEMMInfo</a>
 </li>
-<li>GemmInterleaved()
-: <a class="el" href="class_gemm_interleaved.xhtml#ad4b554ff56ba355e66b70698b1393085">GemmInterleaved&lt; strategy, To, Tr &gt;</a>
+<li>GEMMReshapeInfo()
+: <a class="el" href="classarm__compute_1_1_g_e_m_m_reshape_info.xhtml#aee6f5a043173c4d51c11a54db8e0f519">GEMMReshapeInfo</a>
+</li>
+<li>generate_convolver()
+: <a class="el" href="classarm__compute_1_1_n_e_depthwise_convolution_layer3x3_kernel.xhtml#af77d9d6fcc740068192d3fca9421311f">NEDepthwiseConvolutionLayer3x3Kernel</a>
+</li>
+<li>generate_input_shapes()
+: <a class="el" href="classarm__compute_1_1test_1_1benchmark_1_1_depth_concatenate_layer_fixture.xhtml#ab37a6ce7abc647cab25610539db7f11a">DepthConcatenateLayerFixture&lt; TensorType, ITensorType, Function, AccessorType &gt;</a>
 </li>
 <li>get()
 : <a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml#aebe2d25607545d31f2b1ace6d60a81da">CLKernelLibrary</a>
@@ -274,10 +313,10 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 , <a class="el" href="classarm__compute_1_1graph_1_1_operation_registry.xhtml#a20885c0ad6ee18d2bb0c0177a9b38744">OperationRegistry</a>
 , <a class="el" href="classarm__compute_1_1logging_1_1_logger_registry.xhtml#a56eefda612262945a6f832d1196ee720">LoggerRegistry</a>
 , <a class="el" href="classarm__compute_1_1_o_m_p_scheduler.xhtml#a9571a5288c1b52189b63f9e1074768e3">OMPScheduler</a>
-, <a class="el" href="classarm__compute_1_1_pixel_value.xhtml#ac66bff5206364de49b3159e9cc9d3e58">PixelValue</a>
+, <a class="el" href="classarm__compute_1_1_pixel_value.xhtml#a1541aac2858109c409fcf5eb4ba7799e">PixelValue</a>
 , <a class="el" href="classarm__compute_1_1_scheduler.xhtml#acb4f87f1831680d8d1b70e1bef06bb81">Scheduler</a>
 , <a class="el" href="classarm__compute_1_1_single_thread_scheduler.xhtml#ad2239fa50e4adfc02e94407d0b846077">SingleThreadScheduler</a>
-, <a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml#a11f5f1baaad31d1067564eccf599e90c">AssetsLibrary</a>
+, <a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml#a024fbe836c85d10afefc81cd2e51658e">AssetsLibrary</a>
 , <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_framework.xhtml#af8fbb8b386d3cce307a89002bcdbcfc9">Framework</a>
 </li>
 <li>get_classifications()
@@ -286,26 +325,57 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 , <a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_network.xhtml#a1466ef70729f3c8b5da5ebfec3f53f26">MobileNetNetwork&lt; TensorType, Accessor, ActivationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, DepthwiseConvolutionLayerFunction, ReshapeFunction, PoolingLayerFunction &gt;</a>
 , <a class="el" href="classarm__compute_1_1test_1_1networks_1_1_mobile_net_v1_network.xhtml#a1466ef70729f3c8b5da5ebfec3f53f26">MobileNetV1Network&lt; TensorType, Accessor, ActivationLayerFunction, BatchNormalizationLayerFunction, ConvolutionLayerFunction, DirectConvolutionLayerFunction, DepthwiseConvolutionFunction, ReshapeFunction, PoolingLayerFunction, SoftmaxLayerFunction &gt;</a>
 </li>
+<li>get_convolution_method()
+: <a class="el" href="classarm__compute_1_1_c_l_convolution_layer.xhtml#a5a40ceb849aeb8dc1a3e2cc9d5c49813">CLConvolutionLayer</a>
+, <a class="el" href="classarm__compute_1_1_n_e_convolution_layer.xhtml#a80c35437174d22ead97c59257bf05d3e">NEConvolutionLayer</a>
+</li>
 <li>get_gl_ssbo_name()
 : <a class="el" href="classarm__compute_1_1_g_c_tensor_allocator.xhtml#acb35468f30f12a68bf3c3f227d85a1df">GCTensorAllocator</a>
 </li>
 <li>get_image_shape()
 : <a class="el" href="classarm__compute_1_1test_1_1_assets_library.xhtml#acc474b96886b5fd500460c7b25dc84fa">AssetsLibrary</a>
 </li>
+<li>get_input_storage_size()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_input_kernel.xhtml#a8002726bde2404f3594fd6f1febc5eed">INEWinogradLayerTransformInputKernel&lt; T &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_input_kernel.xhtml#ac500ccdb4a6ced688aa2d8ad4952d215">NEWinogradLayerTransformInputKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+</li>
 <li>get_kernel_path()
 : <a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml#ad7395c158d8e31b9af211b9bc1f65a08">CLKernelLibrary</a>
 </li>
-<li>get_kernel_storage_size()
-: <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_kernel.xhtml#a8e09a3273f0c1e1c3abbf43bb4fa1bda">NEWinogradLayerKernel</a>
-</li>
-<li>get_kernel_transform_working_size()
-: <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_kernel.xhtml#ab1743ad31c8bf4f6e5389aa7970c9e3c">NEWinogradLayerKernel</a>
+<li>get_matrix_stride()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_input_kernel.xhtml#ae25b6ed77179808984b17c39e078ad96">INEWinogradLayerTransformInputKernel&lt; T &gt;</a>
+, <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_output_kernel.xhtml#ae25b6ed77179808984b17c39e078ad96">INEWinogradLayerTransformOutputKernel&lt; T &gt;</a>
+, <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml#a0769fae1b815e5e48086ad25c1528dec">INEWinogradLayerTransformWeightsKernel&lt; T &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_input_kernel.xhtml#ae18e3efe8200578009c1f7a15a4a2fa0">NEWinogradLayerTransformInputKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_output_kernel.xhtml#ae18e3efe8200578009c1f7a15a4a2fa0">NEWinogradLayerTransformOutputKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#a07a976f4d6b4b62e2ffcea8b0dab6d9f">NEWinogradLayerTransformWeightsKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
 </li>
 <li>get_max_workgroup_size()
 : <a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#abca336f832d730e8494049bd714df60a">ICLKernel</a>
 </li>
-<li>get_nhwc_ptrs()
-: <a class="el" href="classarm__compute_1_1_winograd3x3_f32.xhtml#abbf8c87fd8dffe614302613350fd58a6">Winograd3x3F32</a>
+<li>get_number_blocks()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#aa93a680bbd1f25e2e15d85ecebb5a573">INEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#a114bf30301fae775d99637797b17389d">NEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+</li>
+<li>get_number_gemms()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#a48fc5c45b359d608e068703cd61fa916">INEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#a30cc0c6310d217086f60f2c03bea912e">NEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+</li>
+<li>get_output_shape()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_output_kernel.xhtml#a10f4ee28637f13bfbfa0ec1f13972ac1">INEWinogradLayerTransformOutputKernel&lt; T &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_output_kernel.xhtml#acb7b954c56d087e3d2451f92e62eea60">NEWinogradLayerTransformOutputKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+</li>
+<li>get_output_storage_size()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_output_kernel.xhtml#af9c23bac52a4d03b1500cfd081cba624">INEWinogradLayerTransformOutputKernel&lt; T &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_output_kernel.xhtml#acbbdf018ab122fbd13fd655fa678dee3">NEWinogradLayerTransformOutputKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+</li>
+<li>get_output_tile_cols()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#af3fd02b2fb7dbbd5cc2ee0002db6ede6">INEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#a6a6b377891a582d87327706496a0a822">NEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
+</li>
+<li>get_output_tile_rows()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#a1c05f8339d00138dccd2127f0505220c">INEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_batched_g_e_m_m_kernel.xhtml#ae960c2433b8f9a63a5bc1ea61e20f705">NEWinogradLayerBatchedGEMMKernel&lt; TIn, TOut, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
 </li>
 <li>get_profiler()
 : <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_framework.xhtml#a0e42876589150f9ae9ad78d6446ef3b6">Framework</a>
@@ -330,12 +400,9 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 <li>get_value()
 : <a class="el" href="classarm__compute_1_1test_1_1framework_1_1_p_m_u.xhtml#accfba41ff73f99ee744f8619f47bf413">PMU</a>
 </li>
-<li>get_working_size()
-: <a class="el" href="class_gemm_common.xhtml#a190aa5a4547b7d8d8cbf7b7dc46ca32d">GemmCommon&lt; To, Tr &gt;</a>
-, <a class="el" href="class_gemm_interleaved.xhtml#abf5a58f6feffeae31f48b750cba9303d">GemmInterleaved&lt; strategy, To, Tr &gt;</a>
-</li>
-<li>get_working_space_size()
-: <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_kernel.xhtml#aec8ed754d1a231c08c6a61b4d7c69fcc">NEWinogradLayerKernel</a>
+<li>get_weight_storage_size()
+: <a class="el" href="classarm__compute_1_1_i_n_e_winograd_layer_transform_weights_kernel.xhtml#ad670ceec7efb9583d3ab5ae0700bf028">INEWinogradLayerTransformWeightsKernel&lt; T &gt;</a>
+, <a class="el" href="classarm__compute_1_1_n_e_winograd_layer_transform_weights_kernel.xhtml#abfe717774e572988b63fdd5a69364eb9">NEWinogradLayerTransformWeightsKernel&lt; T, OutputTileRows, OutputTileCols, KernelRows, KernelCols &gt;</a>
 </li>
 <li>GlobalPoolingShapes()
 : <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_global_pooling_shapes.xhtml#aa2f05979de5779a1ea507dce1b721566">GlobalPoolingShapes</a>
@@ -368,7 +435,7 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 : <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v1_winograd_layer_dataset.xhtml#af7dbcd903dd2742a455edd24e6b5ed4f">GoogLeNetInceptionV1WinogradLayerDataset</a>
 </li>
 <li>GoogLeNetInceptionV4ActivationLayerDataset()
-: <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_activation_layer_dataset.xhtml#a361dc63be658f74c81c4ca62d555fa4c">GoogLeNetInceptionV4ActivationLayerDataset</a>
+: <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_activation_layer_dataset.xhtml#a12a57f414e425280743da474b259bd31">GoogLeNetInceptionV4ActivationLayerDataset</a>
 </li>
 <li>GoogLeNetInceptionV4BatchNormalizationLayerDataset()
 : <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_batch_normalization_layer_dataset.xhtml#a5c56b0d715939df7ca959944960a7555">GoogLeNetInceptionV4BatchNormalizationLayerDataset</a>
@@ -382,6 +449,9 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 <li>GoogLeNetInceptionV4FullyConnectedLayerDataset()
 : <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_fully_connected_layer_dataset.xhtml#a0e3a7975960a7a9aaf9c17cca2e9a8c0">GoogLeNetInceptionV4FullyConnectedLayerDataset</a>
 </li>
+<li>GoogLeNetInceptionV4NormalizePlanarYUVLayerDataset()
+: <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_normalize_planar_y_u_v_layer_dataset.xhtml#ac9a8eb242d4bffa411886d9293b205f9">GoogLeNetInceptionV4NormalizePlanarYUVLayerDataset</a>
+</li>
 <li>GoogLeNetInceptionV4PoolingLayerDataset()
 : <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_goog_le_net_inception_v4_pooling_layer_dataset.xhtml#a169de687b2e9235db9af906dd7528bb4">GoogLeNetInceptionV4PoolingLayerDataset</a>
 </li>
@@ -403,11 +473,17 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 <li>gpu_speed_mhz
 : <a class="el" href="structmali__userspace_1_1mali__base__gpu__core__props.xhtml#acee64366b6aa7e475082c84ca98e6884">mali_base_gpu_core_props</a>
 </li>
+<li>gpu_target()
+: <a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml#ab0094e1bc5c4a6c433c654786c83993c">Graph</a>
+</li>
 <li>GradientDimensions()
 : <a class="el" href="classarm__compute_1_1test_1_1datasets_1_1_gradient_dimensions.xhtml#a340b012986539040d59dc9cccabf4a61">GradientDimensions</a>
 </li>
 <li>Graph()
-: <a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml#aa2249ab41ba672900ae7703ba6975179">Graph</a>
+: <a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml#afc5ef9d72cc2c509814200791eaef62c">Graph</a>
+</li>
+<li>graph_init()
+: <a class="el" href="classarm__compute_1_1graph_1_1_graph.xhtml#a049136304344524f3d13c052c6fe1f7d">Graph</a>
 </li>
 <li>GraphContext()
 : <a class="el" href="classarm__compute_1_1graph_1_1_graph_context.xhtml#a75608104021b41a6c999e4d076f24905">GraphContext</a>
@@ -427,7 +503,7 @@ $(document).ready(function(){initNavTree('functions_g.xhtml','');});
 <!-- start footer part -->
 <div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
   <ul>
-    <li class="footer">Generated on Thu Dec 14 2017 23:48:39 for Compute Library by
+    <li class="footer">Generated on Thu Feb 22 2018 15:45:28 for Compute Library by
     <a href="http://www.doxygen.org/index.html">
     <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.11 </li>
   </ul>
Domain: Machine Learning / ML Framework;