| /external/tensorflow/tensorflow/compiler/xla/client/ |
| D | xla_builder.h | 334 const absl::Span<const int64> broadcast_dimensions);
603 absl::Span<const int64> broadcast_dimensions,
614 absl::Span<const int64> broadcast_dimensions);
720 const absl::Span<const int64> broadcast_dimensions);
762 absl::Span<const int64> broadcast_dimensions);
764 absl::Span<const int64> broadcast_dimensions);
766 absl::Span<const int64> broadcast_dimensions);
768 absl::Span<const int64> broadcast_dimensions);
770 absl::Span<const int64> broadcast_dimensions);
772 absl::Span<const int64> broadcast_dimensions);
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| D | xla_builder.cc | 420 absl::Span<const int64> broadcast_dimensions) { in InDimBroadcast() argument
425 for (int64 dim : broadcast_dimensions) { in InDimBroadcast()
448 std::vector<int64> broadcast_dimensions; in AddBroadcastSequence() local
452 broadcast_dimensions.push_back(i); in AddBroadcastSequence()
468 broadcast_dimensions); in AddBroadcastSequence()
483 absl::Span<const int64> broadcast_dimensions, in BinaryOp() argument
491 binop, lhs_shape, rhs_shape, broadcast_dimensions)); in BinaryOp()
511 if (!broadcast_dimensions.empty() && lhs_rank != rhs_rank) { in BinaryOp()
523 int64 to_dim = broadcast_dimensions[from_dim]; in BinaryOp()
532 InDimBroadcast(broadcasted_shape, from, broadcast_dimensions)); in BinaryOp()
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| /external/tensorflow/tensorflow/compiler/xla/service/ |
| D | shape_inference.cc | 745 absl::Span<const int64> broadcast_dimensions) { in InferInDimBroadcastShape() argument
746 if (broadcast_dimensions.empty() && !ShapeUtil::IsScalar(smaller_shape)) { in InferInDimBroadcastShape()
753 } else if (broadcast_dimensions.size() != smaller_shape.rank()) { in InferInDimBroadcastShape()
759 smaller_shape.rank(), broadcast_dimensions.size()); in InferInDimBroadcastShape()
805 int64 dimension_to_match = broadcast_dimensions.at(i); in InferInDimBroadcastShape()
847 if (i > 0 && broadcast_dimensions.at(i - 1) >= dimension_to_match) { in InferInDimBroadcastShape()
850 dimension_to_match, broadcast_dimensions.at(i - 1)); in InferInDimBroadcastShape()
862 absl::Span<const int64> broadcast_dimensions) { in InferElementwiseBinaryOpShape() argument
876 if (!broadcast_dimensions.empty() && in InferElementwiseBinaryOpShape()
877 broadcast_dimensions != identity_dims) { in InferElementwiseBinaryOpShape()
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| D | shape_inference.h | 58 absl::Span<const int64> broadcast_dimensions);
225 absl::Span<const int64> broadcast_dimensions);
306 absl::Span<const int64> broadcast_dimensions);
334 absl::Span<const int64> broadcast_dimensions);
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| D | hlo_creation_utils.h | 92 absl::Span<const int64> broadcast_dimensions,
218 absl::Span<const int64> broadcast_dimensions);
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| D | hlo_creation_utils.cc | 177 absl::Span<const int64> broadcast_dimensions, in MakeBroadcastHlo() argument
184 broadcast_shape, operand, broadcast_dimensions)); in MakeBroadcastHlo()
439 absl::Span<const int64> broadcast_dimensions) { in BroadcastZeros() argument
443 /*result_shape_bounds=*/broadcast_dimensions); in BroadcastZeros()
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| D | hlo_instruction.cc | 1102 absl::Span<const int64> broadcast_dimensions) { in CreateBroadcast() argument
1104 broadcast_dimensions); in CreateBroadcast()
1135 std::vector<int64> broadcast_dimensions; in CreateBroadcastSequence() local
1139 broadcast_dimensions.push_back(i); in CreateBroadcastSequence()
1159 broadcast_shape, reshaped_operand, broadcast_dimensions); in CreateBroadcastSequence()
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| D | hlo_instruction.h | 663 absl::Span<const int64> broadcast_dimensions);
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| D | hlo_parser.cc | 1156 optional<std::vector<int64>> broadcast_dimensions; in ParseInstructionRhs() local
1158 &broadcast_dimensions}; in ParseInstructionRhs()
1164 shape, operands[0], *broadcast_dimensions)); in ParseInstructionRhs()
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| /external/tensorflow/tensorflow/compiler/xla/python/ |
| D | local_computation_builder.cc | 477 absl::Span<const int64> broadcast_dimensions) { in BroadcastInDim() argument
478 return xla::BroadcastInDim(operand.op(), out_dim_sizes, broadcast_dimensions); in BroadcastInDim()
788 absl::Span<const int64> broadcast_dimensions), \
789 (lhs.op(), rhs.op(), broadcast_dimensions))
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| D | local_computation_builder.h | 245 absl::Span<const int64> broadcast_dimensions);
392 absl::Span<const int64> broadcast_dimensions))
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| D | xla_client_test.py | 260 broadcast_dimensions=(0,))
271 broadcast_dimensions=(0,))
282 broadcast_dimensions=(1,))
293 broadcast_dimensions=(1,))
948 broadcast_dimensions=(0,))
956 broadcast_dimensions=(1,))
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| D | xla_client.py | 1104 def BroadcastInDim(self, operand, shape, broadcast_dimensions): argument
1116 return self._client.BroadcastInDim(operand, shape, broadcast_dimensions)
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| /external/tensorflow/tensorflow/compiler/xla/g3doc/ |
| D | broadcasting.md | 101 `broadcast_dimensions` argument is given. For example, see
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| D | operation_semantics.md | 1162 <b> `Op(lhs, rhs, broadcast_dimensions)` </b>
1168 The additional `broadcast_dimensions` operand is a slice of integers used to
1170 operand. `broadcast_dimensions` maps the dimensions of the lower-rank shape to
1207 <b> `Op(lhs, rhs, broadcast_dimensions)` </b>
1213 The additional `broadcast_dimensions` operand is a slice of integers specifying
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