/external/tensorflow/tensorflow/core/kernels/ |
D | depthtospace_op_gpu.cu.cc | 37 const int input_height, const int input_width, in D2S_NHWC() argument 57 in_d + input_depth * (in_w + input_width * (in_h + input_height * b)); in D2S_NHWC() 67 const int block_size, const int input_width, in D2S_NCHW() argument 78 const int n_bY_bX_oC_iY = input_idx / input_width; in D2S_NCHW() 79 const int iX = input_idx - n_bY_bX_oC_iY * input_width; in D2S_NCHW() 93 (iX + input_width * in D2S_NCHW() 104 const int input_width, const int output_width, in D2S_NCHW_LOOP() argument 120 const int n_oC_iY = thread_idx / input_width; in D2S_NCHW_LOOP() 121 const int iX = thread_idx - n_oC_iY * input_width; in D2S_NCHW_LOOP() 153 const int input_width = input.dimension(2); in operator ()() local [all …]
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D | spacetodepth_op_gpu.cu.cc | 35 const int input_height, const int input_width, in S2D_NHWC() argument 43 const int w = inp_idx2 % input_width; in S2D_NHWC() 44 const int inp_idx3 = inp_idx2 / input_width; in S2D_NHWC() 104 const int output_width, const int input_width, in S2D_NCHW_LOOP() argument 126 auto input_ptr = input + (n_iC_oY * input_width + oX) * block_size; in S2D_NCHW_LOOP() 135 ldg(input_ptr + bY * input_width + bX); in S2D_NCHW_LOOP() 149 const int input_width = input.dimension(2); in operator ()() local 156 batch_size * input_height * input_width * input_depth; in operator ()() 164 input_height, input_width, input_depth, output_height, output_width, in operator ()() 188 const int input_width = input.dimension(3); in operator ()() local [all …]
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D | conv_ops_using_gemm.cc | 89 int input_batches, int input_height, int input_width, in operator ()() argument 112 ((output_width - 1) * stride_cols + filter_width - input_width + 1) / in operator ()() 119 ((output_width - 1) * stride_cols + filter_width - input_width) / 2; in operator ()() 164 if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in operator ()() 167 input_data[(batch * input_height * input_width * in operator ()() 169 (in_y * input_width * input_depth) + in operator ()() 212 int input_batches, int input_height, int input_width, in operator ()() argument 217 if ((input_batches <= 0) || (input_width <= 0) || (input_height <= 0) || in operator ()() 221 << input_width << ", " << input_depth; in operator ()() 241 const int m = input_batches * input_height * input_width; in operator ()() [all …]
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D | quantized_activation_ops_test.cc | 47 const int input_width = 2; in TEST_F() local 49 Tensor input_float(DT_FLOAT, {input_height, input_width}); in TEST_F() 53 Tensor expected_float(DT_FLOAT, {input_height, input_width}); in TEST_F() 78 const int input_width = 2; in TEST_F() local 80 Tensor input_float(DT_FLOAT, {input_height, input_width}); in TEST_F() 84 Tensor expected_float(DT_FLOAT, {input_height, input_width}); in TEST_F()
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D | quantized_pooling_ops_test.cc | 54 const int input_width = 4; in TEST_F() local 56 Tensor input_float(DT_FLOAT, {1, input_height, input_width, input_channels}); in TEST_F() 64 const int expected_width = input_width / stride; in TEST_F() 99 const int input_width = 4; in TEST_F() local 101 Tensor input_float(DT_FLOAT, {1, input_height, input_width, input_channels}); in TEST_F() 109 const int expected_width = input_width / stride; in TEST_F()
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D | quantized_bias_add_op_test.cc | 54 const int input_width = 3; in TEST_F() local 55 Tensor input_float(DT_FLOAT, {input_height, input_width}); in TEST_F() 69 Tensor expected_float(DT_FLOAT, {input_height, input_width}); in TEST_F() 104 const int input_width = 64; in TEST_F() local 105 Tensor input_float(DT_FLOAT, {input_height, input_width}); in TEST_F() 141 Tensor expected_float(DT_FLOAT, {input_height, input_width}); in TEST_F()
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D | mkl_requantize_ops_test.cc | 118 const int input_width = 4; in TEST_F() local 123 {1, input_height, input_width, input_channels}); in TEST_F() 179 const int input_width = 4; in TEST_F() local 184 {1, input_height, input_width, input_channels}); in TEST_F() 237 const int input_width = 4; in TEST_F() local 242 {1, input_height, input_width, input_channels}); in TEST_F()
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D | eigen_benchmark_cpu_test.cc | 32 int input_batches, int input_height, int input_width, in SpatialConvolution() argument 45 input_width, input_depth); in SpatialConvolution() 61 int input_width, int input_depth, in SpatialConvolutionBackwardInput() argument 74 input_width, input_depth); in SpatialConvolutionBackwardInput() 89 int input_width, int input_depth, in SpatialConvolutionBackwardKernel() argument 102 input_width, input_depth); in SpatialConvolutionBackwardKernel() 110 num_computed_elements * (input_batches * input_height * input_width); in SpatialConvolutionBackwardKernel() 253 int input_batches, int input_height, int input_width, in CuboidConvolution() argument 267 input_batches, input_height, input_width, input_planes, input_depth); in CuboidConvolution() 283 int input_width, int input_planes, in CuboidConvolutionBackwardInput() argument [all …]
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D | quantized_conv_ops.cc | 55 int input_batches, int input_height, int input_width, in operator ()() argument 91 ((output_width - 1) * stride + filter_width - input_width + 1) / 2; in operator ()() 96 ((output_width - 1) * stride + filter_width - input_width) / 2; in operator ()() 141 if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) && in operator ()() 144 input_data[(batch * input_height * input_width * in operator ()() 146 (in_y * input_width * input_depth) + in operator ()() 201 int input_batches, int input_height, int input_width, in operator ()() argument 223 input_width, input_depth, input_offset, filter_data, in operator ()() 236 ((output_width - 1) * stride + filter_width - input_width + 1) / 2; in operator ()() 241 ((output_width - 1) * stride + filter_width - input_width) / 2; in operator ()() [all …]
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D | mkl_quantized_pooling_ops_test.cc | 84 const int input_width = 4; in TEST_F() local 86 Tensor input_float(DT_FLOAT, {1, input_height, input_width, input_channels}); in TEST_F() 94 const int expected_width = input_width / stride; in TEST_F() 153 const int input_width = 4; in TEST_F() local 155 Tensor input_float(DT_FLOAT, {1, input_height, input_width, input_channels}); in TEST_F() 162 const int expected_width = input_width / stride; in TEST_F()
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D | eigen_attention.h | 93 const Index input_width = in.dimension(1); in eval() local 96 eigen_assert(input_width > 0); in eval() 106 x *= input_width; in eval() 113 x += input_width / 2.0f; in eval() 135 } else if (offset_x + width_ >= input_width) { in eval() 136 glimpse_width = (std::max<Index>)(0, input_width - offset_x); in eval() 151 slice_extent[1] = std::min<Index>(input_width, slice_extent[1]); in eval() 184 DSizes<Index, 2> input_size(input_width, input_height); in eval()
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D | scale_and_translate_op.cc | 305 const int64 input_width = input.dim_size(2); in Compute() local 340 ComputeSpans(context, kernel_type_, output_width, input_width, in Compute() 351 input_width, channels}), in Compute() 485 const int64 input_width, const int64 output_height, in GatherColumns() argument 488 const int64 in_row_size = input_width * channels; in GatherColumns() 498 std::min(starts[x] + span_size, static_cast<int>(input_width)) - in GatherColumns() 528 const int64 input_width, const int64 output_height, in GatherRows() argument 530 const int64 in_row_size = input_width * channels; in GatherRows() 567 const int64 input_width = images.dimension(2); in operator ()() local 573 const int64 input_pix_per_batch = input_width * input_height * channels; in operator ()() [all …]
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D | quantized_batch_norm_op_test.cc | 65 const int input_width = 6; in TEST_F() local 68 {input_batch, input_height, input_width, input_depth}); in TEST_F() 122 TensorShape({input_batch, input_height, input_width, input_depth})); in TEST_F() 162 const int input_width = 6; in TEST_F() local 165 {input_batch, input_height, input_width, input_depth}); in TEST_F() 219 TensorShape({input_batch, input_height, input_width, input_depth})); in TEST_F()
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/external/tensorflow/tensorflow/lite/kernels/internal/ |
D | resize_bilinear_test.cc | 28 void TestOneResizeBilinear(int batch, int depth, int input_width, in TestOneResizeBilinear() argument 31 RuntimeShape input_dims_inference({batch, input_height, input_width, depth}); in TestOneResizeBilinear() 84 const int input_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST() local 89 TestOneResizeBilinear<uint8>(batch, depth, input_width, input_height, in TEST() 100 const int input_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST() local 102 const int output_width = input_width * 2; in TEST() 105 TestOneResizeBilinear<uint8>(batch, depth, input_width, input_height, in TEST() 116 const int input_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST() local 121 TestOneResizeBilinear<float>(batch, depth, input_width, input_height, in TEST() 132 const int input_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST() local [all …]
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D | resize_nearest_neighbor_test.cc | 152 void TestOptimizedResizeNearestNeighbor(int batch, int depth, int input_width, in TestOptimizedResizeNearestNeighbor() argument 158 RuntimeShape input_shape({batch, input_height, input_width, depth}); in TestOptimizedResizeNearestNeighbor() 184 bool is_valid_scale(int input_width, int input_height, int output_width, in is_valid_scale() argument 189 static_cast<float>(input_width) / output_width; in is_valid_scale() 192 int32 width_scale_int = (input_width << 16) / output_width + 1; in is_valid_scale() 205 input_width - 1); in is_valid_scale() 206 int32 in_x_int = std::min((x * width_scale_int) >> 16, input_width - 1); in is_valid_scale() 221 const int input_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TEST() local 226 if (is_valid_scale(input_width, input_height, output_width, in TEST() 229 batch, depth, input_width, input_height, output_width, output_height); in TEST()
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D | test_util.cc | 28 const int input_width = input_shape.Dims(2); in ComputeConvSizes() local 44 output_width = (input_width + stride - dilated_filter_width) / stride; in ComputeConvSizes() 47 output_width = (input_width + stride - 1) / stride; in ComputeConvSizes() 61 ((output_width - 1) * stride + dilated_filter_width - input_width) / 2); in ComputeConvSizes()
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D | depthwiseconv_quantized_test.cc | 490 int input_depth, int input_width, int input_height, in TryTestDepthwiseConv() argument 521 {batch, input_height, input_width, input_depth}); in TryTestDepthwiseConv() 563 const int input_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TryTestOneDepthwiseConv() local 575 test_param, params_specialization, batch, input_depth, input_width, in TryTestOneDepthwiseConv() 585 int input_width = ExponentialRandomPositiveInt(0.9f, 20, 200); in TryTestOneDepthwiseConv3x3Filter() local 604 input_width = 2 * (input_width / 2) + 1; in TryTestOneDepthwiseConv3x3Filter() 611 (input_width > 1) != (input_height > 1)) { in TryTestOneDepthwiseConv3x3Filter() 617 test_param, params_specialization, batch, input_depth, input_width, in TryTestOneDepthwiseConv3x3Filter() 632 const int input_width = coverage_extension == CoverageExtension::kLargeWidths in TryTestOneNeonDot3x3() local 653 test_param, params_specialization, batch, input_depth, input_width, in TryTestOneNeonDot3x3()
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D | softmax_quantized_test.cc | 155 const int input_width = ExponentialRandomPositiveInt(0.8f, 20, 200); in TryOneUniformSoftmax() local 163 RuntimeShape({batch, input_height, input_width, input_depth}); in TryOneUniformSoftmax() 188 const int input_width = ExponentialRandomPositiveInt(0.7f, 20, 200); in TryOneSkyscraperSoftmax() local 201 RuntimeShape({batch, input_height, input_width, input_depth}); in TryOneSkyscraperSoftmax()
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/external/tensorflow/tensorflow/examples/label_image/ |
D | label_image.py | 40 input_width=299, argument 59 resized = tf.image.resize_bilinear(dims_expander, [input_height, input_width]) 81 input_width = 299 variable 107 if args.input_width: 108 input_width = args.input_width variable 122 input_width=input_width,
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/external/mesa3d/src/gallium/state_trackers/xvmc/tests/ |
D | xvmc_bench.c | 55 unsigned int input_width; member 71 config->input_width = DEFAULT_INPUT_WIDTH; in ParseArgs() 83 if (sscanf(argv[++i], "%u", &config->input_width) != 1) in ParseArgs() 170 config->output_width = config->input_width; in ParseArgs() 201 mbw = align(config.input_width, MACROBLOCK_WIDTH) / MACROBLOCK_WIDTH; in main() 209 config.input_width, in main() 238 …assert(XvMCCreateContext(display, port_num, surface_type_id, config.input_width, config.input_heig… in main() 278 …assert(XvMCPutSurface(display, &surface, window, 0, 0, config.input_width, config.input_height, 0,… in main() 287 …printf("Input: %u,%u\nOutput: %u,%u\n", config.input_width, config.input_height, config.output_wid… in main()
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/external/tensorflow/tensorflow/lite/kernels/internal/optimized/ |
D | multithreaded_conv.h | 89 int input_width, int input_depth, const T* filter_data, in operator() 108 } else if (filter_height == input_height && filter_width == input_width && in operator() 125 input_width, input_depth); in operator() 157 const int input_width = input_shape.Dims(2); in Conv() local 164 input_width, input_depth, filter_data, filter_height, in Conv()
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/external/webrtc/webrtc/modules/video_coding/utility/ |
D | quality_scaler_unittest.cc | 106 void DownscaleEndsAt(int input_width, 367 void QualityScalerTest::DownscaleEndsAt(int input_width, in DownscaleEndsAt() argument 373 input_frame_.CreateEmptyFrame(input_width, input_height, input_width, in DownscaleEndsAt() 374 (input_width + 1) / 2, (input_width + 1) / 2); in DownscaleEndsAt() 376 int last_width = input_width; in DownscaleEndsAt()
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/integer_ops/ |
D | mean.h | 41 const int input_width = input_shape.Dims(2); in Mean() local 42 const int num_elements_in_axis = input_width * input_height; in Mean() 57 for (int in_w = 0; in_w < input_width; ++in_w) { in Mean()
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D | pooling.h | 34 const int input_width = input_shape.Dims(2); in AveragePool() local 51 std::min(params.filter_width, input_width - in_x_origin); in AveragePool() 95 const int input_width = input_shape.Dims(2); in MaxPool() local 112 std::min(params.filter_width, input_width - in_x_origin); in MaxPool()
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/external/libxcam/tests/ |
D | test-video-stabilization.cpp | 75 uint32_t input_width = 1920; in main() local 115 input_width = atoi(optarg); in main() 116 output_width = input_width; in main() 153 printf ("input width:%d\n", input_width); in main() 202 input_buf_info.init (input_format, input_width, input_height); in main()
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