/external/tensorflow/tensorflow/python/keras/_impl/keras/utils/ |
H A D | vis_utils.py | 59 show_layer_names: whether to display layer names. 84 for layer in layers: 85 layer_id = str(id(layer)) 87 # Append a wrapped layer's label to node's label, if it exists. 88 layer_name = layer.name 89 class_name = layer.__class__.__name__ 90 if isinstance(layer, Wrapper): 91 layer_name = '{}({})'.format(layer_name, layer.layer.name) 92 child_class_name = layer [all...] |
/external/skia/tools/sk_app/ |
H A D | Window.cpp | 41 this->visitLayers([](Layer* layer) { layer->onBackendCreated(); }); 45 return this->signalLayers([=](Layer* layer) { return layer->onChar(c, modifiers); }); 49 return this->signalLayers([=](Layer* layer) { return layer->onKey(key, state, modifiers); }); 53 return this->signalLayers([=](Layer* layer) { return layer->onMouse(x, y, state, modifiers); }); 57 return this->signalLayers([=](Layer* layer) { return layer [all...] |
/external/skqp/tools/sk_app/ |
H A D | Window.cpp | 41 this->visitLayers([](Layer* layer) { layer->onBackendCreated(); }); 45 return this->signalLayers([=](Layer* layer) { return layer->onChar(c, modifiers); }); 49 return this->signalLayers([=](Layer* layer) { return layer->onKey(key, state, modifiers); }); 53 return this->signalLayers([=](Layer* layer) { return layer->onMouse(x, y, state, modifiers); }); 57 return this->signalLayers([=](Layer* layer) { return layer [all...] |
/external/webrtc/webrtc/modules/video_coding/codecs/vp9/ |
H A D | screenshare_layers_unittest.cc | 48 EXPECT_EQ(expected_.layer[layer_id].upd_buf, 49 actual.layer[layer_id].upd_buf); 50 EXPECT_EQ(expected_.layer[layer_id].ref_buf1, 51 actual.layer[layer_id].ref_buf1); 52 EXPECT_EQ(expected_.layer[layer_id].ref_buf2, 53 actual.layer[layer_id].ref_buf2); 54 EXPECT_EQ(expected_.layer[layer_id].ref_buf3, 55 actual.layer[layer_id].ref_buf3); 94 expected_.layer[l].upd_buf = l; 100 expected_.layer[ [all...] |
/external/opencv/ml/src/ |
H A D | mlcnn.cpp | 70 static void icvCNNetworkAddLayer( CvCNNetwork* network, CvCNNLayer* layer ); 73 /* In all layer functions we denote input by X and output by Y, where 78 /*------------------------ functions for convolutional layer ---------------------------*/ 81 static void icvCNNConvolutionForward( CvCNNLayer* layer, const CvMat* X, CvMat* Y ); 83 static void icvCNNConvolutionBackward( CvCNNLayer* layer, int t, 86 /*------------------------ functions for sub-sampling layer ----------------------------*/ 89 static void icvCNNSubSamplingForward( CvCNNLayer* layer, const CvMat* X, CvMat* Y ); 91 static void icvCNNSubSamplingBackward( CvCNNLayer* layer, int t, 94 /*------------------------ functions for full connected layer --------------------------*/ 97 static void icvCNNFullConnectForward( CvCNNLayer* layer, cons [all...] |
/external/mesa3d/src/mesa/drivers/dri/i965/ |
H A D | intel_resolve_map.h | 121 uint32_t layer; member in struct:intel_resolve_map 132 uint32_t layer, 143 uint32_t layer) 145 return intel_resolve_map_find_any(resolve_map, level, 1, layer, 1); 151 uint32_t layer) 154 resolve_map, level, 1, layer, 1); 141 intel_resolve_map_const_get(const struct exec_list *resolve_map, uint32_t level, uint32_t layer) argument 149 intel_resolve_map_get(struct exec_list *resolve_map, uint32_t level, uint32_t layer) argument
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H A D | intel_resolve_map.c | 29 * \brief Set that the miptree slice at (level, layer) needs a resolve. 37 uint32_t layer, 41 if (map->level == level && map->layer == layer) { 50 m->layer = layer; 68 map->layer >= start_layer && 69 map->layer < (start_layer + num_layers)) 35 intel_resolve_map_set(struct exec_list *resolve_map, uint32_t level, uint32_t layer, unsigned need) argument
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/external/wpa_supplicant_8/hostapd/logwatch/ |
H A D | hostapd | 29 if (my ($iface,$mac,$layer,$details) = ($line =~ /(.*?): STA (.*?) (.*?): (.*?)$/i)) { 34 $hostapd{$iface}->{$mac}->{$layer}->{$details}++; 45 foreach my $layer (sort keys %{$hostapd{$iface}->{$mac}}) { 46 print " $layer:\n"; 47 foreach my $details (sort keys %{$hostapd{$iface}->{$mac}->{$layer}}) { 49 my $count = $hostapd{$iface}->{$mac}->{$layer}->{$details};
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/external/tensorflow/tensorflow/python/layers/ |
H A D | base_test.py | 43 layer = base_layers.Layer(name='my_layer') 44 self.assertEqual(layer.variables, []) 45 self.assertEqual(layer.trainable_variables, []) 46 self.assertEqual(layer.non_trainable_variables, []) 49 self.assertEqual(layer.updates, []) 50 self.assertEqual(layer.losses, []) 51 self.assertEqual(layer.built, False) 52 layer = base_layers.Layer(name='my_layer', trainable=False) 53 self.assertEqual(layer.trainable, False) 57 layer 284 layer = CustomerLayer() variable in class:BaseLayerTest.testInputSpecNdimCheck.CustomerLayer 311 layer = CustomerLayer() variable in class:BaseLayerTest.testInputSpecMinNdimCheck.CustomerLayer 339 layer = CustomerLayer() variable in class:BaseLayerTest.testInputSpecMaxNdimCheck.CustomerLayer [all...] |
H A D | convolutional_test.py | 67 layer = conv_layers.Conv2D(32, [3, 3], activation=nn_ops.relu) 68 output = layer.apply(images) 72 self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 4, 32]) 73 self.assertListEqual(layer.bias.get_shape().as_list(), [32]) 85 layer = conv_layers.Conv2D(32, 3) 86 output = layer.apply(images) 89 self.assertListEqual(layer.kernel.get_shape().as_list(), [3, 3, 4, 32]) 90 self.assertListEqual(layer.bias.get_shape().as_list(), [32]) 95 layer = conv_layers.Conv2D(32, [3, 3], data_format='channels_first') 96 output = layer [all...] |
H A D | pooling_test.py | 56 layer = pooling_layers.MaxPooling2D([2, 2], strides=2) 57 output = layer.apply(images) 63 layer = pooling_layers.AveragePooling2D([2, 2], strides=2) 64 output = layer.apply(images) 70 layer = pooling_layers.MaxPooling2D([2, 2], 73 output = layer.apply(images) 79 layer = pooling_layers.AveragePooling2D((2, 2), 83 output = layer.apply(images) 90 layer = pooling_layers.AveragePooling2D((2, 2), 94 output = layer [all...] |
/external/skia/tests/ |
H A D | GpuLayerCacheTest.cpp | 8 // Disabling this test since it is for the layer hoister which is current disabled. 40 static int Uses(GrCachedLayer* layer) { argument 41 return layer->uses(); 59 GrCachedLayer* layer = cache->findLayerOrCreate(picture.uniqueID(), local 66 REPORTER_ASSERT(reporter, layer); 69 REPORTER_ASSERT(reporter, temp == layer); 73 REPORTER_ASSERT(reporter, picture.uniqueID() == layer->pictureID()); 74 REPORTER_ASSERT(reporter, layer->start() == idOffset + i + 1); 75 REPORTER_ASSERT(reporter, layer->stop() == idOffset + i + 2); 76 REPORTER_ASSERT(reporter, !layer 82 lock_layer(skiatest::Reporter* reporter, GrLayerCache* cache, GrCachedLayer* layer) argument [all...] |
/external/skqp/tests/ |
H A D | GpuLayerCacheTest.cpp | 8 // Disabling this test since it is for the layer hoister which is current disabled. 40 static int Uses(GrCachedLayer* layer) { argument 41 return layer->uses(); 59 GrCachedLayer* layer = cache->findLayerOrCreate(picture.uniqueID(), local 66 REPORTER_ASSERT(reporter, layer); 69 REPORTER_ASSERT(reporter, temp == layer); 73 REPORTER_ASSERT(reporter, picture.uniqueID() == layer->pictureID()); 74 REPORTER_ASSERT(reporter, layer->start() == idOffset + i + 1); 75 REPORTER_ASSERT(reporter, layer->stop() == idOffset + i + 2); 76 REPORTER_ASSERT(reporter, !layer 82 lock_layer(skiatest::Reporter* reporter, GrLayerCache* cache, GrCachedLayer* layer) argument [all...] |
/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
H A D | local_test.py | 68 layer = keras.layers.LocallyConnected1D(**kwargs) 69 layer.build((num_samples, num_steps, input_dim)) 70 self.assertEqual(len(layer.losses), 2) 71 layer( 73 self.assertEqual(len(layer.losses), 3) 84 layer = keras.layers.LocallyConnected1D(**kwargs) 85 layer.build((num_samples, num_steps, input_dim)) 86 self.assertEqual(layer.kernel.constraint, k_constraint) 87 self.assertEqual(layer.bias.constraint, b_constraint) 147 layer [all...] |
H A D | convolutional_test.py | 75 layer = keras.layers.Conv1D(**kwargs) 76 layer.build((None, 5, 2)) 77 self.assertEqual(len(layer.losses), 2) 78 layer(keras.backend.variable(np.ones((1, 5, 2)))) 79 self.assertEqual(len(layer.losses), 3) 94 layer = keras.layers.Conv1D(**kwargs) 95 layer.build((None, 5, 2)) 96 self.assertEqual(layer.kernel.constraint, k_constraint) 97 self.assertEqual(layer.bias.constraint, b_constraint) 149 layer [all...] |
H A D | recurrent_test.py | 51 layer = keras.layers.RNN(cell) variable in class:RNNTest.test_minimal_rnn_cell_non_layer.MinimalRNNCell 52 y = layer(x) 61 layer = keras.layers.RNN(cells) variable in class:RNNTest.test_minimal_rnn_cell_non_layer.MinimalRNNCell 62 y = layer(x) 89 layer = keras.layers.RNN(cell) variable in class:RNNTest.test_minimal_rnn_cell_non_layer_multiple_states.MinimalRNNCell 90 y = layer(x) 99 layer = keras.layers.RNN(cells) variable in class:RNNTest.test_minimal_rnn_cell_non_layer_multiple_states.MinimalRNNCell 100 assert layer.cell.state_size == (32, 32, 16, 16, 8, 8) 101 y = layer(x) 140 layer variable in class:RNNTest.test_minimal_rnn_cell_layer.MinimalRNNCell 163 layer = keras.layers.RNN(cells) variable in class:RNNTest.test_minimal_rnn_cell_layer.MinimalRNNCell 230 layer = keras.layers.RNN(cell) variable in class:RNNTest.test_rnn_cell_with_constants_layer.RNNCellWithConstants 270 layer = keras.layers.recurrent.RNN(cells) variable in class:RNNTest.test_rnn_cell_with_constants_layer.RNNCellWithConstants 343 layer = keras.layers.RNN(cell) variable in class:RNNTest.test_rnn_cell_with_constants_layer_passing_initial_state.RNNCellWithConstants [all...] |
H A D | convolutional_recurrent_test.py | 60 layer = keras.layers.ConvLSTM2D(**kwargs) 61 layer.build(inputs.shape) 62 outputs = layer(x) 68 keras.backend.eval(layer.states[0]), state, atol=1e-4) 103 layer = keras.layers.ConvLSTM2D(**kwargs) 105 model.add(layer) 119 layer.reset_states() 162 layer = keras.layers.ConvLSTM2D(**kwargs) 163 layer.build(inputs.shape) 164 self.assertEqual(len(layer [all...] |
/external/iproute2/include/uapi/linux/tc_ematch/ |
H A D | tc_em_nbyte.h | 11 __u8 layer:4; member in struct:tcf_em_nbyte
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/external/kernel-headers/original/uapi/linux/tc_ematch/ |
H A D | tc_em_nbyte.h | 11 __u8 layer:4; member in struct:tcf_em_nbyte
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/external/mesa3d/src/gallium/auxiliary/vl/ |
H A D | vl_compositor.c | 610 default_rect(struct vl_compositor_layer *layer) argument 612 struct pipe_resource *res = layer->sampler_views[0]->texture; 632 calc_src_and_dst(struct vl_compositor_layer *layer, unsigned width, unsigned height, argument 637 layer->src.tl = calc_topleft(size, src); 638 layer->src.br = calc_bottomright(size, src); 639 layer->dst.tl = calc_topleft(size, dst); 640 layer->dst.br = calc_bottomright(size, dst); 641 layer->zw.x = 0.0f; 642 layer->zw.y = size.y; 646 gen_rect_verts(struct vertex2f *vb, struct vl_compositor_layer *layer) argument 730 calc_drawn_area(struct vl_compositor_state *s, struct vl_compositor_layer *layer) argument 793 struct vl_compositor_layer *layer = &s->layers[i]; local 832 struct vl_compositor_layer *layer = &s->layers[i]; local 964 vl_compositor_set_layer_blend(struct vl_compositor_state *s, unsigned layer, void *blend, bool is_clearing) argument 977 vl_compositor_set_layer_dst_area(struct vl_compositor_state *s, unsigned layer, struct u_rect *dst_area) argument 994 vl_compositor_set_buffer_layer(struct vl_compositor_state *s, struct vl_compositor *c, unsigned layer, struct pipe_video_buffer *buffer, struct u_rect *src_rect, struct u_rect *dst_rect, enum vl_compositor_deinterlace deinterlace) argument 1047 vl_compositor_set_palette_layer(struct vl_compositor_state *s, struct vl_compositor *c, unsigned layer, struct pipe_sampler_view *indexes, struct pipe_sampler_view *palette, struct u_rect *src_rect, struct u_rect *dst_rect, bool include_color_conversion) argument 1077 vl_compositor_set_rgba_layer(struct vl_compositor_state *s, struct vl_compositor *c, unsigned layer, struct pipe_sampler_view *rgba, struct u_rect *src_rect, struct u_rect *dst_rect, struct vertex4f *colors) argument 1109 vl_compositor_set_layer_rotation(struct vl_compositor_state *s, unsigned layer, enum vl_compositor_rotation rotate) argument 1119 vl_compositor_set_yuv_layer(struct vl_compositor_state *s, struct vl_compositor *c, unsigned layer, struct pipe_video_buffer *buffer, struct u_rect *src_rect, struct u_rect *dst_rect, bool y) argument [all...] |
/external/tensorflow/tensorflow/python/keras/_impl/keras/engine/ |
H A D | topology.py | 16 """Base layer code and base model (Network) code. 67 """Abstract base layer class. 75 A layer with `n` input tensors must have 77 trainable: Boolean, whether the layer weights 80 of the layer uses `K.in_training_phase()` 84 attribute is ill-defined (e.g. a shared layer 87 Prefer using `layer.get_input_shape_for(input_shape)`, 88 or `layer.get_input_shape_at(node_index)`. 92 input, output: Input/output tensor(s). Note that if the layer is used 93 more than once (shared layer), thi [all...] |
/external/iproute2/tc/ |
H A D | em_nbyte.c | 31 "Usage: nbyte(NEEDLE at OFFSET [layer LAYER])\n" \ 36 "Example: nbyte(\"ababa\" at 12 layer 1)\n", 45 unsigned long offset = 0, layer = TCF_LAYER_NETWORK; local 70 } else if (!bstrcmp(a, "layer")) { 75 layer = parse_layer(a); 76 if (layer == INT_MAX) { 77 layer = bstrtoul(a); 78 if (layer == ULONG_MAX) 80 "layer"); 83 if (layer > TCF_LAYER_MA [all...] |
/external/mp4parser/isoparser/src/main/java/com/googlecode/mp4parser/authoring/ |
H A D | TrackMetaData.java | 41 int layer; field in class:TrackMetaData 108 return layer; 111 public void setLayer(int layer) { argument 112 this.layer = layer;
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/external/tensorflow/tensorflow/contrib/eager/python/ |
H A D | network.py | 85 `tf.layers.Dense` layer: 306 def track_layer(self, layer): 313 layer: A `tf.layers.Layer` object. 316 The passed in `layer`. 320 TypeError: If `layer` is the wrong type. 325 if not isinstance(layer, base.Layer): 328 (type(layer),)) 329 if isinstance(layer, Network): 330 layer._finalize_name(parent_network=self) 332 # `layer` i [all...] |
/external/libxcam/modules/ocl/ |
H A D | cl_newwavelet_denoise_handler.cpp | 67 uint32_t layer) 72 , _current_layer (layer) 292 uint32_t layer) 296 , _current_layer (layer) 378 uint32_t layer, 384 , _current_layer (layer) 497 CLWaveletTransformKernel::get_decomp_buffer (uint32_t channel, int layer) argument 501 buffer = _handler->get_decomp_buffer (channel, layer); 505 XCAM_LOG_ERROR ("get channel(%d) layer(%d) decomposition buffer failed!", channel, layer); 61 CLWaveletNoiseEstimateKernel( const SmartPtr<CLContext> &context, const char *name, SmartPtr<CLNewWaveletDenoiseImageHandler> &handler, uint32_t channel, uint32_t subband, uint32_t layer) argument 287 CLWaveletThresholdingKernel( const SmartPtr<CLContext> &context, const char *name, SmartPtr<CLNewWaveletDenoiseImageHandler> &handler, uint32_t channel, uint32_t layer) argument 372 CLWaveletTransformKernel( const SmartPtr<CLContext> &context, const char *name, SmartPtr<CLNewWaveletDenoiseImageHandler> &handler, CLWaveletFilterBank fb, uint32_t channel, uint32_t layer, bool bayes_shrink) argument 669 get_decomp_buffer(uint32_t channel, int layer) argument 706 dump_coeff(SmartPtr<CLImage> image, uint32_t channel, uint32_t layer, uint32_t subband) argument 765 create_kernel_haar_decomposition( const SmartPtr<CLContext> &context, SmartPtr<CLNewWaveletDenoiseImageHandler> handler, uint32_t channel, uint32_t layer, bool bayes_shrink) argument 798 create_kernel_haar_reconstruction( const SmartPtr<CLContext> &context, SmartPtr<CLNewWaveletDenoiseImageHandler> handler, uint32_t channel, uint32_t layer, bool bayes_shrink) argument 832 create_kernel_noise_estimation( const SmartPtr<CLContext> &context, SmartPtr<CLNewWaveletDenoiseImageHandler> handler, uint32_t channel, uint32_t subband, uint32_t layer) argument 862 create_kernel_thresholding( const SmartPtr<CLContext> &context, SmartPtr<CLNewWaveletDenoiseImageHandler> handler, uint32_t channel, uint32_t layer) argument [all...] |