| /external/tensorflow/tensorflow/core/kernels/ |
| D | conv_grad_filter_ops.cc | 146 dims.spatial_dims[0].input_size, dims.spatial_dims[0].filter_size, in operator ()()
149 DCHECK_EQ(dims.spatial_dims[0].output_size, expected_out_rows); in operator ()()
151 dims.spatial_dims[1].input_size, dims.spatial_dims[1].filter_size, in operator ()()
154 DCHECK_EQ(dims.spatial_dims[1].output_size, expected_out_cols); in operator ()()
473 dims.spatial_dims[0].input_size, dims.spatial_dims[0].filter_size, in Compute()
474 dims.spatial_dims[0].stride, padding_, in Compute()
475 &dims.spatial_dims[0].output_size, &pad_top, &pad_bottom)); in Compute()
479 dims.spatial_dims[1].input_size, dims.spatial_dims[1].filter_size, in Compute()
480 dims.spatial_dims[1].stride, padding_, in Compute()
481 &dims.spatial_dims[1].output_size, &pad_left, &pad_right)); in Compute()
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| D | conv_grad_input_ops.cc | 113 dims.spatial_dims[0].input_size, dims.spatial_dims[0].filter_size, in operator ()()
116 DCHECK_EQ(dims.spatial_dims[0].output_size, expected_out_rows); in operator ()()
118 dims.spatial_dims[1].input_size, dims.spatial_dims[1].filter_size, in operator ()()
121 DCHECK_EQ(dims.spatial_dims[1].output_size, expected_out_cols); in operator ()()
138 if (dims.spatial_dims[0].filter_size == 1 && in operator ()()
139 dims.spatial_dims[1].filter_size == 1 && !is_grouped_convolution && in operator ()()
140 dims.spatial_dims[0].stride == 1 && dims.spatial_dims[1].stride == 1 && in operator ()()
143 const uint64 m = dims.batch_size * dims.spatial_dims[0].input_size * in operator ()()
144 dims.spatial_dims[1].input_size; in operator ()()
162 } else if (dims.spatial_dims[0].filter_size == in operator ()()
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| D | conv_grad_input_ops.h | 151 dims.spatial_dims[0].input_size, dims.spatial_dims[0].filter_size, in operator()
154 DCHECK_EQ(dims.spatial_dims[0].output_size, expected_out_rows); in operator()
157 dims.spatial_dims[1].input_size, dims.spatial_dims[1].filter_size, in operator()
160 DCHECK_EQ(dims.spatial_dims[1].output_size, expected_out_cols); in operator()
594 dims.spatial_dims[0].input_size, dims.spatial_dims[0].filter_size,
595 dims.spatial_dims[0].stride, padding_,
596 &dims.spatial_dims[0].output_size, &pad_top, &pad_bottom));
600 dims.spatial_dims[1].input_size, dims.spatial_dims[1].filter_size,
601 dims.spatial_dims[1].stride, padding_,
602 &dims.spatial_dims[1].output_size, &pad_left, &pad_right));
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| D | conv_grad_ops_3d.cc | 283 static_cast<int>(dims.spatial_dims[0].stride), // stride_planes in Compute()
284 static_cast<int>(dims.spatial_dims[1].stride), // stride_rows in Compute()
285 static_cast<int>(dims.spatial_dims[2].stride)); // stride_cols in Compute()
412 dims.spatial_dims[0].input_size, in Compute()
413 dims.spatial_dims[0].filter_size, in Compute()
414 dims.spatial_dims[0].stride, padding_, in Compute()
415 &dims.spatial_dims[0].output_size, in Compute()
418 dims.spatial_dims[1].input_size, in Compute()
419 dims.spatial_dims[1].filter_size, in Compute()
420 dims.spatial_dims[1].stride, padding_, in Compute()
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| D | conv_grad_shape_utils.h | 47 gtl::InlinedVector<ConvBackpropSpatialDimension, 3> spatial_dims; member
56 int64_t input_size(int dim) const { return spatial_dims[dim].input_size; } in input_size()
57 int64_t filter_size(int dim) const { return spatial_dims[dim].filter_size; } in filter_size()
58 int64_t output_size(int dim) const { return spatial_dims[dim].output_size; } in output_size()
59 int64_t stride(int dim) const { return spatial_dims[dim].stride; } in stride()
60 int64_t dilation(int dim) const { return spatial_dims[dim].dilation; } in dilation()
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| D | conv_2d.h | 304 Eigen::DSizes<IndexType, NDIMS - 2> spatial_dims;
305 for (int i = 0; i < spatial_dims.rank(); ++i) {
306 spatial_dims[i] = in.dimension(i);
311 merged_dims[0] = spatial_dims.TotalSize(); // product of spatial dims [H*W]
325 for (int i = 0; i < spatial_dims.rank(); ++i) {
326 expanded_dims[2 + i] = spatial_dims[i];
334 for (int i = 0; i < spatial_dims.rank(); ++i) {
335 expanded_dims[1 + i] = spatial_dims[i];
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| D | conv_grad_shape_utils.cc | 144 dims->spatial_dims.resize(num_spatial_dims); in ConvBackpropComputeDimensionsV2()
155 &dims->spatial_dims[i])); in ConvBackpropComputeDimensionsV2()
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | batch_to_space_nd_test.cc | 74 int spatial_dims = static_cast<int>(block_shape.size()); in BatchToSpaceNDOpConstModel() local
76 block_shape_ = AddConstInput(TensorType_INT32, block_shape, {spatial_dims}); in BatchToSpaceNDOpConstModel()
77 crops_ = AddConstInput(TensorType_INT32, crops, {spatial_dims, 2}); in BatchToSpaceNDOpConstModel()
104 int spatial_dims = static_cast<int>(input_shape.size()) - 2; in BatchToSpaceNDOpDynamicModel() local
108 BuildInterpreter({input_shape, {spatial_dims}, {spatial_dims, 2}}); in BatchToSpaceNDOpDynamicModel()
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_ops.py | 575 spatial_dims=None, argument
722 spatial_dims=spatial_dims,
752 spatial_dims=None, argument
776 if spatial_dims is None:
777 spatial_dims = range(starting_spatial_dim,
779 orig_spatial_dims = list(spatial_dims)
780 spatial_dims = sorted(set(int(x) for x in orig_spatial_dims))
781 if spatial_dims != orig_spatial_dims or any(x < 1 for x in spatial_dims):
787 expected_input_rank = spatial_dims[-1]
789 expected_input_rank = spatial_dims[-1] + 1
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | conv_op_helpers.cc | 361 padding[i] = {dims.spatial_dims[i].pad_before, in MakeXlaBackpropInputConvOp()
362 dims.spatial_dims[i].pad_after}; in MakeXlaBackpropInputConvOp()
363 lhs_dilation[i] = dims.spatial_dims[i].stride; in MakeXlaBackpropInputConvOp()
474 rhs_dilation[i] = dims.spatial_dims[i].stride; in MakeXlaBackpropFilterConvOp()
483 dims.spatial_dims[i].expanded_output_size + in MakeXlaBackpropFilterConvOp()
484 (dims.spatial_dims[i].filter_size - 1) * attrs.dilations[dim]; in MakeXlaBackpropFilterConvOp()
500 const int64_t pad_total = padded_in_size - dims.spatial_dims[i].input_size; in MakeXlaBackpropFilterConvOp()
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| /external/tensorflow/tensorflow/core/util/ |
| D | tensor_format.h | 603 std::vector<int64_t> spatial_dims(num_src_spatial_dims); in ShapeFromFormat()
605 spatial_dims[spatial_dim] = gtl::ArraySlice<int64_t>( in ShapeFromFormat()
610 spatial_dims[num_src_spatial_dims - 1] *= 4; in ShapeFromFormat()
612 return ShapeFromFormat(dst_format, batch, {spatial_dims}, channels); in ShapeFromFormat()
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| /external/tensorflow/tensorflow/compiler/mlir/xla/experimental/conv_emitter/ |
| D | conv_emitter.cc | 70 absl::Span<const tensorflow::protobuf_int64> spatial_dims, in GetShapeInfo() argument
82 for (int64_t dim : spatial_dims) { in GetShapeInfo()
102 /*dimCount=*/2 + spatial_dims.size(), /*symbolCount=*/0, affine_exprs, in GetShapeInfo()
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| /external/tensorflow/tensorflow/core/framework/ |
| D | common_shape_fns.cc | 524 gtl::MutableArraySlice<DimensionHandle> spatial_dims, in DimensionsFromShape() argument
528 GetTensorDimsFromSpatialDims(spatial_dims.size(), format); in DimensionsFromShape()
532 for (int spatial_dim_index = 0, end = spatial_dims.size(); in DimensionsFromShape()
534 spatial_dims[spatial_dim_index] = context->Dim( in DimensionsFromShape()
550 gtl::ArraySlice<DimensionHandle> spatial_dims, in ShapeFromDimensions() argument
555 GetTensorDimsFromSpatialDims(spatial_dims.size(), format); in ShapeFromDimensions()
561 for (int spatial_dim_index = 0, end = spatial_dims.size(); in ShapeFromDimensions()
564 rank, format, spatial_dim_index)] = spatial_dims[spatial_dim_index]; in ShapeFromDimensions()
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| /external/tensorflow/tensorflow/compiler/xla/service/ |
| D | dynamic_padder.cc | 242 const auto& spatial_dims = in ShouldSkipPadOnOperand() local
244 for (int64_t spatial_dim = 0; spatial_dim < spatial_dims.size(); in ShouldSkipPadOnOperand()
248 if (spatial_dims[spatial_dim] == dimension && in ShouldSkipPadOnOperand()
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| /external/tensorflow/tensorflow/compiler/mlir/xla/transforms/ |
| D | legalize_tf.cc | 984 NamedAttribute GetConvDimensionNumbersAttr(ArrayRef<int64_t> spatial_dims, in GetConvDimensionNumbersAttr() argument
987 int64_t num_spatial_dims = spatial_dims.size(); in GetConvDimensionNumbersAttr()
1005 builder->getContext(), batch_dim, feature_dim, spatial_dims, in GetConvDimensionNumbersAttr()
1007 kernel_spatial_dimensions, batch_dim, feature_dim, spatial_dims)); in GetConvDimensionNumbersAttr()
4944 SmallVector<int64_t, num_spatial_dims> spatial_dims; in matchAndRewrite() local
4952 spatial_dims.push_back(spatial_dim); in matchAndRewrite()
5056 /*input_spatial_dimensions=*/spatial_dims, in matchAndRewrite()
5067 /*output_spatial_dimensions=*/spatial_dims), in matchAndRewrite()
5168 SmallVector<int64_t, num_spatial_dims> spatial_dims; in matchAndRewrite() local
5190 const auto &spatial_dim_i = dims.spatial_dims[i]; in matchAndRewrite()
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.nn.pbtxt | 357 …'input\', \'dilation_rate\', \'padding\', \'op\', \'filter_shape\', \'spatial_dims\', \'data_forma…
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| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/transforms/ |
| D | legalize_hlo.cc | 754 auto spatial_dims = dnums.getInputSpatialDimensions(); in matchAndRewrite() local
756 std::accumulate(spatial_dims.begin(), spatial_dims.end(), 1LL, in matchAndRewrite()
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.nn.pbtxt | 445 …'input\', \'dilation_rate\', \'padding\', \'op\', \'filter_shape\', \'spatial_dims\', \'data_forma…
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | randomized_tests.cc | 465 const std::vector<int64_t>& spatial_dims);
1298 const std::vector<int64_t>& spatial_dims) { in ImageDims() argument
1303 for (int dim : spatial_dims) { in ImageDims()
1311 for (int dim : spatial_dims) { in ImageDims()
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| /external/tensorflow/tensorflow/compiler/xla/stream_executor/cuda/ |
| D | cuda_dnn.cc | 704 absl::Span<const int64_t> spatial_dims = in CudnnFilterDescriptor() local
706 std::copy(spatial_dims.begin(), spatial_dims.end(), dims.begin() + 2); in CudnnFilterDescriptor()
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| /external/tensorflow/tensorflow/compiler/xla/g3doc/ |
| D | operation_semantics.md | 790 * `spatial_dims`: Describes the `n` spatial dimensions that define the base
799 * `spatial_dims`: Describes the `n` spatial dimensions that define the n-d
861 * `spatial_dims`: One value for each valid placement of the convolutional
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