/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
D | reduction_ops_common.cc | 48 const TensorShape data_shape = ctx->InputShape(0); in Compile() local 70 VLOG(1) << "data shape: " << data_shape.DebugString(); in Compile() 73 absl::InlinedVector<bool, 4> bitmap(data_shape.dims(), false); in Compile() 78 !(index < -data_shape.dims() || index >= data_shape.dims()), in Compile() 80 " for input with ", data_shape.dims(), in Compile() 82 index = (index + data_shape.dims()) % data_shape.dims(); in Compile() 93 for (int i = 0; i < data_shape.dims(); ++i) { in Compile() 96 int64 dim = data_shape.dim_size(i); in Compile()
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D | resampler_ops.cc | 199 xla::Shape data_shape, XlaOp sample) { in BoundSamples() argument 210 {/*width=*/static_cast<float>(data_shape.dimensions(2)), in BoundSamples() 211 /*height=*/static_cast<float>(data_shape.dimensions(1))}), in BoundSamples() 252 xla::Shape data_shape) { in CalculateGradData() argument 286 last_warp_dim, data_shape, reshaped_weights); in CalculateGradData() 302 ctx->builder(), xla::Literal::CreateFromShape(data_shape)); in CalculateGradData() 321 const int64 batch_size = data_shape.dimensions(0); in CalculateGradData() 322 const int64 width = data_shape.dimensions(1); in CalculateGradData() 323 const int64 height = data_shape.dimensions(2); in CalculateGradData() 362 xla::PrimitiveType data_type, xla::Shape data_shape) { in CalculateGradWarp() argument [all …]
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D | segment_reduction_ops.cc | 54 TensorShape data_shape = ctx->InputShape(0); in Compile() local 62 OP_REQUIRES(ctx, data_shape.dims() >= indices_shape.dims(), in Compile() 69 ctx, (data_shape.dim_size(d) == indices_shape.dim_size(d)), in Compile() 73 d, " differs ", data_shape.dim_size(d), in Compile() 81 TensorShape buffer_shape = data_shape; in Compile() 102 for (int64 i = indices_shape.dims(); i < data_shape.dims(); ++i) { in Compile()
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D | dynamic_stitch_op.cc | 75 const TensorShape& data_shape = data_shapes[input_num]; in Compile() local 77 ctx, TensorShapeUtils::StartsWith(data_shape, indices_shape), in Compile() 79 "].shape = ", data_shape.DebugString(), in Compile() 85 data_shape, indices_shape), in Compile() 90 input_num, "].shape = ", data_shape.DebugString(), in Compile()
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/external/tensorflow/tensorflow/compiler/xla/service/ |
D | rng_bit_generator_expander.cc | 57 const Shape& data_shape, const Shape& state_shape, in GetGeneratorComputation() argument 59 RngGeneratorKey cache_key{data_shape, state_shape, algorithm, module}; in GetGeneratorComputation() 72 data_shape); in GetGeneratorComputation() 76 key_op, GetPhiloxStateOp(state_param, state_shape), data_shape); in GetGeneratorComputation() 110 const Shape& data_shape = rng->shape().tuple_shapes(1); in ExpandInstruction() local 114 GetGeneratorComputation(data_shape, state_shape, algorithm, module)); in ExpandInstruction() 116 ShapeUtil::MakeTupleShape({state_shape, data_shape}), in ExpandInstruction()
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D | rng_bit_generator_expander.h | 42 Shape data_shape; member 49 return H::combine(std::move(h), c.state_shape, c.data_shape, c.algorithm, in AbslHashValue() 54 return data_shape == o.data_shape && state_shape == o.state_shape && 61 StatusOr<HloComputation*> GetGeneratorComputation(const Shape& data_shape,
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D | hlo_dataflow_analysis_test.cc | 2118 Shape data_shape = ShapeUtil::MakeShape(F32, {8}); in TEST_F() local 2120 0, ShapeUtil::MakeTupleShape({data_shape, data_shape}), "tuple")); in TEST_F() 2122 HloInstruction::CreateGetTupleElement(data_shape, tuple, 0)); in TEST_F() 2124 HloInstruction::CreateGetTupleElement(data_shape, tuple, 1)); in TEST_F() 2133 data_shape, gte1, update, in TEST_F() 2154 Shape data_shape = ShapeUtil::MakeShape(F32, {8}); in TEST_F() local 2156 0, ShapeUtil::MakeTupleShape({data_shape, data_shape}), "tuple")); in TEST_F() 2158 HloInstruction::CreateGetTupleElement(data_shape, tuple_param, 0)); in TEST_F() 2160 HloInstruction::CreateGetTupleElement(data_shape, tuple_param, 1)); in TEST_F() 2165 HloInstruction::CreateGetTupleElement(data_shape, tuple, 0)); in TEST_F() [all …]
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D | tuple_points_to_analysis_test.cc | 651 Shape data_shape = ShapeUtil::MakeShape(F32, {}); in TEST_F() local 653 ShapeUtil::MakeTupleShape({data_shape, data_shape}), {constant}, in TEST_F() 659 HloInstruction::CreateGetTupleElement(data_shape, ccall, 0)); in TEST_F() 661 HloInstruction::CreateGetTupleElement(data_shape, ccall, 1)); in TEST_F() 927 Shape data_shape = ShapeUtil::MakeShape(F32, {8}); in TEST_F() local 929 0, ShapeUtil::MakeTupleShape({data_shape, data_shape}), "tuple")); in TEST_F() 931 HloInstruction::CreateGetTupleElement(data_shape, tuple, 0)); in TEST_F() 933 HloInstruction::CreateGetTupleElement(data_shape, tuple, 1)); in TEST_F() 942 data_shape, gte1, update, {starts})); in TEST_F()
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D | hlo_instruction_test.cc | 1353 Shape data_shape = ShapeUtil::MakeShape(F32, {2, 2}); in TEST_F() local 1359 HloInstruction::CreateTranspose(data_shape, b, {1, 0})); in TEST_F() 1364 data_shape, a, b_t, dot_dnums, DefaultPrecisionConfig(2))); in TEST_F() 1368 HloInstruction::CreateBroadcast(data_shape, one, {})); in TEST_F() 1370 data_shape, HloOpcode::kAdd, dot, add_operand)); in TEST_F() 1372 data_shape, HloOpcode::kSubtract, dot, add_operand)); in TEST_F() 1374 HloInstruction::CreateBinary(data_shape, HloOpcode::kMultiply, add, sub)); in TEST_F()
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D | layout_assignment.cc | 413 const Shape& data_shape = in BuildHostChannelConstraints() local 415 TF_RET_CHECK(data_shape.IsArray()); in BuildHostChannelConstraints() 416 TF_RET_CHECK(LayoutUtil::HasLayout(data_shape)); in BuildHostChannelConstraints() 418 *send_recv_instr->channel_id(), data_shape.layout()); in BuildHostChannelConstraints()
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/external/tensorflow/tensorflow/core/tpu/kernels/xla/ |
D | get_item_op.cc | 36 const TensorShape& data_shape = ctx->InputShape(0); in Compile() local 39 ctx, TensorShapeUtils::IsVectorOrHigher(data_shape), in Compile() 50 for (int i = 1; i < data_shape.dims(); i++) { in Compile() 57 for (int i = 1; i < data_shape.dims(); i++) { in Compile() 59 auto size = data_shape.dim_size(i); in Compile()
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D | segment_reduction_ops.cc | 45 TensorShape data_shape = ctx->InputShape(0); in Compile() local 53 OP_REQUIRES(ctx, data_shape.dims() >= indices_shape.dims(), in Compile() 59 OP_REQUIRES(ctx, (data_shape.dim_size(d) == indices_shape.dim_size(d)), in Compile() 63 d, " differs ", data_shape.dim_size(d), " vs. ", in Compile() 71 TensorShape buffer_shape = data_shape; in Compile() 92 for (int64 i = indices_shape.dims(); i < data_shape.dims(); ++i) { in Compile()
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/external/tensorflow/tensorflow/cc/gradients/ |
D | data_flow_grad_test.cc | 50 TensorShape data_shape({2, 3, 2}); in TEST_F() local 51 auto data = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(data_shape)); in TEST_F() 55 RunTest({data}, {data_shape}, y.outputs, in TEST_F()
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D | image_grad_test.cc | 43 Tensor MakeData(const TensorShape& data_shape) { in MakeData() argument 45 Tensor data(data_type, data_shape); in MakeData() 188 Tensor MakeData(const TensorShape& data_shape) { in MakeData() argument 190 Tensor data(data_type, data_shape); in MakeData() 305 Tensor MakeData(const TensorShape& data_shape) { in MakeData() argument 307 Tensor data(data_type, data_shape); in MakeData()
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/external/tensorflow/tensorflow/python/keras/engine/ |
D | base_preprocessing_layer_v1.py | 149 data_shape = data_element.shape 153 data_shape = None 162 self.build(data_shape)
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D | training_integration_test.py | 149 def _run_fit_eval_predict(self, layer_to_test, input_shape, data_shape, argument 155 x = keras.backend.random_uniform(shape=data_shape) 181 return keras.backend.random_uniform(shape=data_shape)
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D | base_preprocessing_layer.py | 256 data_shape = data.shape 260 data_shape = None 268 self.build(data_shape)
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D | training_utils_v1.py | 651 data_shape = tuple(tensorshape.as_list()) 654 data_shape = tuple(tensorshape.as_list()) 656 data_shape = data[i].shape 659 if len(data_shape) != len(shape): 663 'with shape ' + str(data_shape)) 665 data_shape = data_shape[1:] 667 for dim, ref_dim in zip(data_shape, shape): 672 str(data_shape))
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/external/tensorflow/tensorflow/cc/client/ |
D | client_session_test.cc | 209 TensorShape data_shape({1, 1}); in TEST() local 210 auto a = Placeholder(root, DT_INT32, Placeholder::Shape(data_shape)); in TEST() 211 auto b = Placeholder(root, DT_INT32, Placeholder::Shape(data_shape)); in TEST()
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/external/tensorflow/tensorflow/core/ops/ |
D | math_ops.cc | 1123 ShapeHandle data_shape; in SegmentReductionShapeFn() local 1125 TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(0), 1, &data_shape)); in SegmentReductionShapeFn() 1129 TF_RETURN_IF_ERROR(c->Subshape(data_shape, 1, &subshape)); in SegmentReductionShapeFn() 1139 ShapeHandle data_shape; in SparseSegmentReductionShapeFn() local 1140 TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(0), 1, &data_shape)); in SparseSegmentReductionShapeFn() 1153 TF_RETURN_IF_ERROR(c->Subshape(data_shape, 1, &subshape)); in SparseSegmentReductionShapeFn() 1163 ShapeHandle data_shape; in SparseSegmentReductionGradShapeFn() local 1164 TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(0), 1, &data_shape)); in SparseSegmentReductionGradShapeFn() 1177 TF_RETURN_IF_ERROR(c->Subshape(data_shape, 1, &subshape)); in SparseSegmentReductionGradShapeFn() 1201 ShapeHandle data_shape; in SparseSegmentReductionWithNumSegmentsShapeFn() local [all …]
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D | data_flow_ops.cc | 58 ShapeHandle data_shape = c->input(0); in __anonea01102b0202() local 70 c->MergePrefix(data_shape, partitions_shape, &unused, &unused)); in __anonea01102b0202() 77 TF_RETURN_IF_ERROR(c->Subshape(data_shape, rank, &data_suffix_shape)); in __anonea01102b0202() 105 ShapeHandle data_shape = c->input(i + num_partitions); in DynamicStitchShapeFunction() local 114 c->MergePrefix(data_shape, indices_shape, &unused, &unused)); in DynamicStitchShapeFunction() 118 TF_RETURN_IF_ERROR(c->Subshape(data_shape, indices_rank, &rest)); in DynamicStitchShapeFunction()
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/external/tensorflow/tensorflow/compiler/xla/tests/ |
D | tuple_test.cc | 433 Shape data_shape = ShapeUtil::MakeShape(F32, {3}); in XLA_TEST_F() local 434 Shape inner_tuple_shape = ShapeUtil::MakeTupleShape({data_shape, data_shape}); in XLA_TEST_F() 436 ShapeUtil::MakeTupleShape({inner_tuple_shape, data_shape}); in XLA_TEST_F()
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | normalization_test.py | 197 data_shape = (100, 3) 207 model.fit(np.random.random(data_shape), np.random.random(data_shape)) 209 test_data = np.random.random(data_shape) 210 test_targets = np.random.random(data_shape)
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/external/tensorflow/tensorflow/python/ops/ |
D | array_ops.py | 6426 data_shape = shape(data) 6437 data_shape[:axis], [repeats * data_shape[axis]], data_shape[axis + 1:] 6447 repeats = broadcast_to(repeats, [data_shape[axis]]) 6455 [data_shape[:axis + 1 - repeats_ndims], repeats_shape], axis=0) 6483 [data_shape[:axis], [repeated_dim_size], data_shape[axis + 1:]], 6517 data_shape = shape(data) 6519 return reshape(data, concat([[1], data_shape], axis=0)[-data_ndims:])
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/external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
D | ir_emitter.cc | 395 const Shape& data_shape = infeed->infeed_shape(); in HandleInfeed() local 396 DCHECK(ShapeUtil::Equal(data_shape, in HandleInfeed() 403 llvm::Value* data_address = EmitBufferPointer(data_slice, data_shape); in HandleInfeed() 410 if (data_shape.IsTuple()) { in HandleInfeed() 411 TF_RET_CHECK(!ShapeUtil::IsNestedTuple(data_shape)); in HandleInfeed() 418 for (int64 i = 0; i < data_shape.tuple_shapes_size(); ++i) { in HandleInfeed() 423 ShapeUtil::GetTupleElementShape(data_shape, i); in HandleInfeed() 438 llvm_ir::EmitTuple(llvm_ir::IrArray(data_address, data_shape), in HandleInfeed() 442 EmitXfeedTransfer(XfeedKind::kInfeed, data_shape, data_address)); in HandleInfeed() 2195 const Shape& data_shape = ShapeUtil::GetSubshape(hlo->shape(), {0}); in HandlePadToStatic() local [all …]
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