/external/tensorflow/tensorflow/core/kernels/ |
D | conv_ops_using_gemm.cc | 91 int filter_width, int filter_count, int stride_rows, 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 ()() 156 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in operator ()() 175 filter_data[(filter_y * filter_width * input_depth * in operator ()() 214 int filter_width, int filter_count, int stride_rows, in operator ()() argument 224 if ((filter_width <= 0) || (filter_height <= 0) || (filter_count <= 0)) { in operator ()() 226 << filter_width << ", " << filter_height << ", " in operator ()() 238 if (filter_height == 1 && filter_width == 1 && stride_rows == 1 && in operator ()() 251 } else if (filter_height == input_height && filter_width == input_width && in operator ()() [all …]
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D | eigen_benchmark_cpu_test.cc | 35 int filter_count, int filter_height, int filter_width) { in SpatialConvolution() argument 46 typename Benchmark::Dimensions filter_dims(filter_height, filter_width, in SpatialConvolution() 54 num_computed_elements * (input_depth * filter_height * filter_width); in SpatialConvolution() 64 int filter_width) { in SpatialConvolutionBackwardInput() argument 75 typename Benchmark::Dimensions filter_dims(filter_height, filter_width, in SpatialConvolutionBackwardInput() 82 num_computed_elements * (input_depth * filter_height * filter_width); in SpatialConvolutionBackwardInput() 92 int filter_width) { in SpatialConvolutionBackwardKernel() argument 103 typename Benchmark::Dimensions filter_dims(filter_height, filter_width, in SpatialConvolutionBackwardKernel() 256 int filter_count, int filter_height, int filter_width, in CuboidConvolution() argument 269 filter_height, filter_width, filter_planes, input_depth, filter_count); in CuboidConvolution() [all …]
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D | depthwise_conv_op_gpu.h | 83 const int filter_width = in DepthwiseConv2dGPUKernelNHWC() local 109 const int input_col_end = input_col_start + filter_width; in DepthwiseConv2dGPUKernelNHWC() 119 const int filter_offset_temp = filter_width * filter_row; in DepthwiseConv2dGPUKernelNHWC() 120 UNROLL for (int filter_col = 0; filter_col < filter_width; in DepthwiseConv2dGPUKernelNHWC() 138 const int filter_offset_temp = filter_width * filter_row; in DepthwiseConv2dGPUKernelNHWC() 139 UNROLL for (int filter_col = 0; filter_col < filter_width; in DepthwiseConv2dGPUKernelNHWC() 190 const int filter_width = in DepthwiseConv2dGPUKernelNHWCSmall() local 205 const int filter_pixels = filter_height * filter_width; in DepthwiseConv2dGPUKernelNHWCSmall() 206 const int tile_width = in_width + filter_width - 1; in DepthwiseConv2dGPUKernelNHWCSmall() 284 UNROLL for (int c = 0; c < filter_width; ++c) { in DepthwiseConv2dGPUKernelNHWCSmall() [all …]
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D | quantized_conv_ops.cc | 57 int filter_height, int filter_width, int filter_count, 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 ()() 133 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in operator ()() 156 filter_data[(filter_y * filter_width * input_depth * in operator ()() 203 int filter_height, int filter_width, int filter_count, in operator ()() argument 224 filter_height, filter_width, filter_count, filter_offset, 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 ()() 257 const int filter_value_count = filter_width * filter_height * input_depth; in operator ()() [all …]
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D | conv_ops_fused_image_transform.cc | 262 const T2* filter_data, int filter_height, int filter_width, in operator ()() argument 275 if ((filter_width <= 0) || (filter_height <= 0) || (filter_count <= 0)) { in operator ()() 277 << filter_width << ", " << filter_height << ", " in operator ()() 297 ((output_width - 1) * stride_cols + filter_width - padded_width + 1) / in operator ()() 304 ((output_width - 1) * stride_cols + filter_width - padded_width) / 2; in operator ()() 332 const int filter_value_count = filter_width * filter_height * input_depth; in operator ()() 369 filter_width; in operator ()() 551 (filter_y * filter_width * task_params.input_depth); in operator ()() 568 (filter_width * task_params.input_depth), in operator ()()
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/external/tensorflow/tensorflow/lite/experimental/micro/kernels/portable_optimized/ |
D | depthwise_conv.cc | 55 int height, int filter_width, int filter_height, in CalculateOpData() argument 61 ComputePadding(params->stride_width, 1, width, filter_width, out_width); in CalculateOpData() 124 const int filter_width = filter_shape.Dims(2); in DepthwiseConvOptimizedForFilterWidthEight() local 132 output_depth * filter_width * filter_height * input_depth; in DepthwiseConvOptimizedForFilterWidthEight() 143 {1, output_depth, filter_height, filter_width}); in DepthwiseConvOptimizedForFilterWidthEight() 150 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in DepthwiseConvOptimizedForFilterWidthEight() 192 int filter_x_end = filter_width; in DepthwiseConvOptimizedForFilterWidthEight() 193 if ((in_x_origin + filter_width) >= input_width) { in DepthwiseConvOptimizedForFilterWidthEight() 194 filter_x_end -= (in_x_origin + filter_width) - input_width; in DepthwiseConvOptimizedForFilterWidthEight() 201 if ((filter_width == 8) && !is_out_of_x_bounds) { in DepthwiseConvOptimizedForFilterWidthEight() [all …]
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/external/tensorflow/tensorflow/lite/kernels/ |
D | pooling.cc | 93 compute_out_size(width, params->filter_width, params->stride_width); in GenericPrepare() 100 params->filter_width, out_width); in GenericPrepare() 134 op_params.filter_width = params->filter_width; \ in AverageEvalFloat() 164 op_params.filter_width = params->filter_width; \ in AverageEvalQuantizedUint8() 191 op_params.filter_width = params->filter_width; in AverageEvalQuantizedInt8() 213 op_params.filter_width = params->filter_width; \ in MaxEvalFloat() 241 op_params.filter_width = params->filter_width; \ in MaxEvalQuantizedUInt8() 270 op_params.filter_width = params->filter_width; \ in MaxEvalQuantizedInt8() 294 op_params.filter_width = params->filter_width; \ in L2EvalFloat()
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D | padding.h | 44 int in_width, int filter_height, int filter_width, TfLitePadding padding) { in ComputePaddingHeightWidth() argument 45 int out_width = ComputeOutSize(padding, in_width, filter_width, stride_width); in ComputePaddingHeightWidth() 53 ComputePadding(stride_width, 1, in_width, filter_width, out_width); in ComputePaddingHeightWidth()
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D | transpose_conv.cc | 122 const int filter_width = SizeOfDimension(weights, 2); in ResizeIm2ColTensor() local 124 im2col_shape_array->data[3] = input_depth * filter_height * filter_width; in ResizeIm2ColTensor() 200 const int filter_width = SizeOfDimension(weights, 2); in Eval() local 208 filter_height, filter_width, params->padding); in Eval()
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D | conv.cc | 151 int filter_width = filter->dims->data[2]; in AllocateTemporaryTensorsIfRequired() local 160 params->dilation_height_factor != 1 || filter_width != 1 || in AllocateTemporaryTensorsIfRequired() 274 int filter_width = filter->dims->data[2]; in Prepare() local 290 int out_width = compute_out_size(width, filter_width, params->stride_width, in Prepare() 301 filter_width, out_width); in Prepare() 345 im2col_size->data[3] = input_depth * filter_height * filter_width; in Prepare() 367 hwcn_weights_size->data[0] = (filter_height * filter_width * input_depth); in Prepare()
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/external/tensorflow/tensorflow/lite/kernels/internal/optimized/ |
D | multithreaded_conv.h | 90 int filter_height, int filter_width, int filter_count, in operator() 94 const bool is_1x1_kernel = (filter_height == 1 && filter_width == 1 && in operator() 108 } else if (filter_height == input_height && filter_width == input_width && in operator() 113 filter_width * filter_height * input_depth; in operator() 126 ConstEigenTensor filter(filter_data, filter_height, filter_width, in operator() 159 const int filter_width = filter_shape.Dims(2); in Conv() local 165 filter_width, output_depth, stride_height, stride_width, in Conv()
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D | legacy_optimized_ops.h | 1212 params.filter_width = kwidth; in AveragePool() 1238 int pad_width, int pad_height, int filter_width, in AveragePool() argument 1242 filter_width, filter_height, output_data, output_dims); in AveragePool() 1247 int pad_height, int filter_width, int filter_height, in AveragePool() argument 1255 params.filter_width = filter_width; in AveragePool() 1268 int pad_height, int filter_width, int filter_height, in AveragePool() argument 1281 pad_height, filter_width, filter_height, output_activation_min, in AveragePool() 1288 int pad_width, int pad_height, int filter_width, in AveragePool() argument 1293 filter_width, filter_height, output_activation_min, in AveragePool() 1306 params.filter_width = kwidth; in MaxPool() [all …]
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/external/tensorflow/tensorflow/lite/kernels/internal/ |
D | depthwiseconv_float_test.cc | 75 const int filter_width = ExponentialRandomPositiveInt(0.9f, 4, 10); in TryTestOneDepthwiseConv() local 106 if (!ComputeConvSizes(input_shape_inference, output_depth, filter_width, in TryTestOneDepthwiseConv() 113 {1, filter_height, filter_width, output_depth}); in TryTestOneDepthwiseConv() 123 filter_width * filter_height * input_amplitude * filter_amplitude; in TryTestOneDepthwiseConv()
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D | depthwiseconv_quantized_test.cc | 491 int filter_width, int filter_height, in TryTestDepthwiseConv() argument 524 if (!ComputeConvSizes(input_shape_inference, output_depth, filter_width, in TryTestDepthwiseConv() 531 {1, filter_height, filter_width, output_depth}); in TryTestDepthwiseConv() 565 const int filter_width = ExponentialRandomPositiveInt(0.9f, 4, 10); in TryTestOneDepthwiseConv() local 576 input_height, filter_width, filter_height, depth_multiplier, stride, in TryTestOneDepthwiseConv() 587 const int filter_width = 3; in TryTestOneDepthwiseConv3x3Filter() local 618 input_height, filter_width, filter_height, depth_multiplier, stride, in TryTestOneDepthwiseConv3x3Filter() 639 const int filter_width = 3; in TryTestOneNeonDot3x3() local 654 input_height, filter_width, filter_height, depth_multiplier, stride, in TryTestOneNeonDot3x3()
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D | test_util.cc | 24 int filter_width, int filter_height, int stride, in ComputeConvSizes() argument 32 int dilated_filter_width = dilation_width_factor * (filter_width - 1) + 1; in ComputeConvSizes()
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/external/tensorflow/tensorflow/lite/experimental/micro/kernels/ |
D | depthwise_conv.cc | 52 int height, int filter_width, int filter_height, in CalculateOpData() argument 58 ComputePadding(params->stride_width, 1, width, filter_width, out_width); in CalculateOpData() 169 int filter_width = SizeOfDimension(filter, 2); in Eval() local 171 int out_width = ComputeOutSize(params->padding, width, filter_width, in Eval() 178 filter_width, filter_height, out_width, in Eval()
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/external/tensorflow/tensorflow/tools/graph_transforms/ |
D | flatten_atrous.cc | 70 const int32 filter_width = filter.dim_size(1); in FlattenAtrousConv() local 77 (filter_width - 1) * block_width + 1; in FlattenAtrousConv() 88 for (int w = 0; w < filter_width; ++w) { in FlattenAtrousConv()
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_Conv2D.pbtxt | 14 `[filter_height, filter_width, in_channels, out_channels]` 71 `[filter_height, filter_width, in_channels, out_channels]`, this op 75 `[filter_height * filter_width * in_channels, output_channels]`. 78 filter_height * filter_width * in_channels]`.
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D | api_def_Dilation2DBackpropFilter.pbtxt | 12 3-D with shape `[filter_height, filter_width, depth]`. 24 3-D with shape `[filter_height, filter_width, depth]`.
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D | api_def_Dilation2D.pbtxt | 12 3-D with shape `[filter_height, filter_width, depth]`. 44 `filter` tensor has shape `[filter_height, filter_width, depth]`, i.e., each
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/ |
D | legacy_reference_ops.h | 1408 params.filter_width = kwidth; in AveragePool() 1488 int pad_width, int pad_height, int filter_width, in AveragePool() argument 1492 filter_width, filter_height, output_data, output_dims); in AveragePool() 1497 int pad_height, int filter_width, int filter_height, in AveragePool() argument 1505 params.filter_width = filter_width; in AveragePool() 1518 int pad_height, int filter_width, int filter_height, in AveragePool() argument 1531 pad_height, filter_width, filter_height, output_activation_min, in AveragePool() 1538 int pad_width, int pad_height, int filter_width, in AveragePool() argument 1543 filter_width, filter_height, output_activation_min, in AveragePool() 1556 params.filter_width = kwidth; in MaxPool() [all …]
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D | depthwiseconv_float.h | 50 const int filter_width = filter_shape.Dims(2); in DepthwiseConv() local 66 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in DepthwiseConv()
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/integer_ops/ |
D | conv.h | 61 const int filter_width = filter_shape.Dims(2); in ConvPerChannel() local 72 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in ConvPerChannel()
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D | depthwise_conv.h | 56 const int filter_width = filter_shape.Dims(2); in DepthwiseConvPerChannel() local 72 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in DepthwiseConvPerChannel()
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/external/tensorflow/tensorflow/core/kernels/neon/ |
D | depthwiseconv_float.h | 428 int depth_multiplier, int filter_width, 450 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { 501 int pad_width, int depth_multiplier, int filter_width, 512 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { 570 const int filter_width = ArraySize(filter_dims, 1); 654 pad_width, depth_multiplier, filter_width,
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