/external/tensorflow/tensorflow/core/kernels/ |
D | dilation_ops.cc | 68 int64* out_rows, int64* out_cols) { in ParseSizes() argument 111 padding, out_cols, pad_left)); in ParseSizes() 129 int64 out_rows = 0, out_cols = 0; in Compute() local 132 &out_cols); in Compute() 138 const std::vector<int64> out_sizes = {batch, out_rows, out_cols, depth}; in Compute() 228 int64 out_rows = 0, out_cols = 0; in Compute() local 231 &out_cols); in Compute() 240 out_cols == out_backprop.dim_size(2) && in Compute() 348 int64 out_rows = 0, out_cols = 0; in Compute() local 351 &out_cols); in Compute() [all …]
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D | deep_conv2d.h | 80 int out_cols; member 93 out_cols(0), in Conv2DArgs() 102 int out_rows, int out_cols);
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D | depthwise_conv_op.cc | 99 const int64 base_output_index = (out_r * args.out_cols + out_c) * out_depth; in Run() 198 args.out_rows * args.out_cols * args.out_depth; in operator ()() 219 for (int64 out_c = 0; out_c < args.out_cols; ++out_c) { in operator ()() 241 const int64 shard_cost = kCostMultiplier * args.out_cols * args.out_depth; in operator ()() 374 int64 out_rows = 0, out_cols = 0, pad_top = 0, pad_bottom = 0, pad_left = 0, in Compute() local 387 &out_cols, &pad_left, &pad_right)); in Compute() 389 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth); in Compute() 420 << "]; Output: [" << batch << ", " << out_rows << ", " << out_cols in Compute() 463 args.out_cols = out_cols; in Compute()
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D | depthwise_conv_grad_op.cc | 120 int64 out_rows = 0, out_cols = 0, pad_top = 0, pad_bottom = 0, pad_left = 0, \ 133 &out_cols, &pad_left, &pad_right)); \ 140 context, output_cols == out_cols, \ 143 "actual = ", output_cols, ", computed = ", out_cols)); \ 156 args.out_cols = out_cols; \ 163 << ", output: [" << batch << ", " << out_rows << ", " << out_cols \ 205 const int64 out_cols = args.out_cols; in CopyOutputBackpropRegion() local 213 const int64 out_c_end = std::min(out_cols - 1, (in_c + pad_cols) / stride); in CopyOutputBackpropRegion() 236 out_backprop + (out_r * args.out_cols + out_c) * args.out_depth; in CopyOutputBackpropRegion() 424 args.out_rows * args.out_cols * args.out_depth; in operator ()() [all …]
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D | conv_ops.cc | 241 int out_cols, int out_depth, int dilation_rows, in Run() argument 247 in_depth, out_depth, out_rows, out_cols)) { in Run() 261 args.out_cols = out_cols; in Run() 282 int out_cols, int out_depth, int stride_rows, int stride_cols, in Run() argument 296 int out_cols, int out_depth, int dilation_rows, in Run() argument 476 int64 out_rows = 0, out_cols = 0; in ComputeConv2DDimension() local 482 &out_cols, &pad_cols_before, &pad_cols_after)); in ComputeConv2DDimension() 497 dimensions->out_cols = out_cols; in ComputeConv2DDimension() 533 dimensions.out_cols, dimensions.out_depth); in Compute() 564 dimensions.out_cols, dimensions.out_depth, dimensions.dilation_rows, in Compute() [all …]
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D | deep_conv2d.cc | 50 int out_depth, int out_rows, int out_cols) { in GetDeepConvCost() argument 66 const int64 col_tiles = (out_cols + out_tile_cols - 1) / out_tile_cols; in GetDeepConvCost() 75 int out_depth, int out_rows, int out_cols) { in GetDirectConvCost() argument 76 return filter_rows * filter_cols * in_depth * out_depth * out_rows * out_cols; in GetDirectConvCost() 99 int out_rows, int out_cols) { in CanUseDeepConv2D() argument 117 t.output_shape().cols, in_depth, out_depth, out_rows, out_cols); in CanUseDeepConv2D() 119 filter_rows, filter_cols, in_depth, out_depth, out_rows, out_cols); in CanUseDeepConv2D() 800 out_c_start < 0 || out_c_start >= args.out_cols) { in operator ()() 813 if (out_c >= args.out_cols) continue; in operator ()() 823 args.out_depth * (out_r * args.out_cols + out_c) + od; in operator ()() [all …]
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D | fractional_avg_pool_op.cc | 246 const int64 out_cols = out_backprop.dim_size(2); in Compute() local 277 out_cols * out_rows * out_batch); in Compute() 288 for (int64 c = 0; c < out_cols; ++c) { in Compute() 296 const int64 out_index = (b * out_rows + r) * out_cols + c; in Compute()
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D | quantized_conv_ops.cc | 540 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; in Compute() local 546 padding_, &out_cols, &pad_cols)); in Compute() 549 CHECK_GT(out_cols, 0); in Compute() 551 TensorShape out_shape({batch, out_rows, out_cols, out_depth}); in Compute() 564 padding_, output->flat<T3>().data(), out_rows, out_cols, in Compute()
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D | conv_ops_using_gemm.cc | 522 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; in Compute() local 528 padding_, &out_cols, &pad_cols)); in Compute() 530 ShapeFromFormat(data_format_, batch, out_rows, out_cols, out_depth); in Compute() 554 output->flat<T>().data(), out_rows, out_cols); in Compute()
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D | conv_grad_filter_ops_benchmark_test.cc | 65 {batch, conv2d_dims.out_rows, conv2d_dims.out_cols, out_depth}) in Conv2DBackpropFilter() 67 {batch, out_depth, conv2d_dims.out_rows, conv2d_dims.out_cols}); in Conv2DBackpropFilter()
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D | depthwise_conv_op_gpu.h | 58 args.in_cols == args.out_cols && args.pad_rows >= 0 && 71 args.in_cols == args.out_cols && args.pad_rows >= 0 && 104 const int out_width = args.out_cols; 351 const int out_width = args.out_cols; 662 const int num_outputs = args.out_rows * args.out_cols * block_count; 750 args.batch * args.out_rows * args.out_cols * args.out_depth; 824 const int out_width = args.out_cols; 894 const int out_width = args.out_cols; 1047 const int out_width = args.out_cols; 1332 const int out_width = args.out_cols; [all …]
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D | conv_grad_input_ops_benchmark_test.cc | 64 {batch, conv2d_dims.out_rows, conv2d_dims.out_cols, out_depth}) in Conv2DBackpropInput() 66 {batch, out_depth, conv2d_dims.out_rows, conv2d_dims.out_cols}); in Conv2DBackpropInput()
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D | conv_ops.h | 99 int64 out_cols;
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D | depthwise_conv_op.h | 40 int out_cols; member 55 out_cols(0), in DepthwiseArgs()
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D | conv_ops_fused_image_transform.cc | 822 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; in Compute() local 828 padding_, &out_cols, &pad_cols)); in Compute() 830 ShapeFromFormat(FORMAT_NHWC, batch, out_rows, out_cols, out_depth); in Compute() 858 output->flat<T>().data(), out_rows, out_cols, st, top_padding, in Compute()
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/external/tensorflow/tensorflow/core/kernels/neon/ |
D | neon_depthwise_conv_op.cc | 90 int64 out_rows = 0, out_cols = 0, pad_rows = 0, pad_cols = 0; in Compute() local 96 padding_, &out_cols, &pad_cols)); in Compute() 97 TensorShape out_shape({batch, out_rows, out_cols, out_depth}); in Compute() 115 << out_rows << ", " << out_cols << ", " << out_depth << "]"; in Compute()
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/external/tensorflow/tensorflow/core/kernels/image/ |
D | extract_volume_patches_op.cc | 112 int64 out_planes = 0, out_rows = 0, out_cols = 0; in Compute() local 122 padding_, &out_cols, &pad_cols)); in Compute() 125 batch, out_planes, out_rows, out_cols, in Compute()
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D | extract_image_patches_op.cc | 89 int64 out_rows = 0, out_cols = 0; in Compute() local 96 padding_, &out_cols, &pad_cols)); in Compute() 98 const std::vector<int64> out_sizes = {batch, out_rows, out_cols, in Compute()
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/external/tensorflow/tensorflow/core/kernels/mkl/ |
D | mkl_conv_ops.h | 396 int64 out_rows = 0, out_cols = 0, out_planes = 0; variable 418 padding_type, &out_cols, &pad_left, &pad_right)); 431 padding_, &out_cols, &pad_left, &pad_right)); 456 ? ShapeFromFormat(data_format_, out_batch, out_rows, out_cols, 459 {{out_planes, out_rows, out_cols}}, out_depth); 468 mkldnn_sizes[MklDnnDims::Dim_W] = static_cast<int>(out_cols); 476 mkldnn_sizes[MklDnnDims3D::Dim3d_W] = static_cast<int>(out_cols);
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_ExtractVolumePatches.pbtxt | 12 5-D Tensor with shape `[batch, out_planes, out_rows, out_cols, 15 in the "depth" dimension. Note `out_planes`, `out_rows` and `out_cols`
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D | api_def_ExtractImagePatches.pbtxt | 12 4-D Tensor with shape `[batch, out_rows, out_cols, ksize_rows * 15 `out_rows` and `out_cols` are the dimensions of the output patches.
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D | api_def_Conv3DBackpropInput.pbtxt | 19 Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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D | api_def_Conv3DBackpropFilter.pbtxt | 19 Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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D | api_def_Conv3DBackpropFilterV2.pbtxt | 21 Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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/external/tensorflow/tensorflow/core/grappler/costs/ |
D | utils_test.cc | 71 int out_cols = 9; in TEST() local 87 CreateConstOp("output_backprop", {batch, out_rows, out_cols, out_depth}, in TEST()
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