/external/tensorflow/tensorflow/compiler/xla/tests/ |
H A D | bitcast_convert_test.cc | 127 // input -> reshape -> convert 129 // input -> convert -> reshape 134 auto reshape = builder.Reshape(input, /*dimensions=*/{0}, /*new_sizes=*/{}); local 135 builder.BitcastConvertType(reshape, F32);
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H A D | convert_test.cc | 198 // input -> reshape -> convert 200 // input -> convert -> reshape 205 auto reshape = builder.Reshape(input, /*dimensions=*/{0}, /*new_sizes=*/{}); local 206 builder.ConvertElementType(reshape, F32);
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H A D | reshape_test.cc | 104 auto reshape = builder.Reshape(/*operand=*/parameter, /*dimensions=*/{0, 1}, local 106 auto new_shape = builder.GetShape(reshape).ConsumeValueOrDie(); 121 auto reshape = local 540 // As above, but uses reshape directly. 691 // Tests R2->R4 reshape with the reshape dimensions {1, 0}. 762 // Tests R4->R2 reshape with the reshape dimensions {0, 2, 1, 3}. 818 // Since the reshape is a no-op, verify that it does not change the underlying 893 // Specify the requested output shape explicitly to ensure that this reshape [all...] |
H A D | select_and_scatter_test.cc | 259 const auto reshape = local 263 builder_.SelectAndScatter(reshape, ge_s32_, /*window_dimensions=*/{2, 3},
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H A D | multioutput_fusion_test.cc | 137 HloInstruction* reshape = local 144 ShapeUtil::MakeShape(F32, {1}), sub, reshape, dot_dnums)); 156 TF_CHECK_OK(reshape->ReplaceOperandWith(0, gte1));
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H A D | reduce_test.cc | 526 auto reshape = builder.Reshape(log_, {rows, cols}); local 527 builder.Reduce(reshape, zero, add_f32, /*dimensions_to_reduce=*/{0}); 843 // These should be simplified into a reshape.
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H A D | fusion_test.cc | 323 auto reshape = builder.AddInstruction(HloInstruction::CreateReshape( local 326 ->CreateFusionInstruction(/*instructions_to_fuse=*/{reshape},
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/external/tensorflow/tensorflow/contrib/lite/kernels/ |
H A D | reshape.cc | 25 namespace reshape { namespace in namespace:tflite::ops::builtin 81 } // namespace reshape 84 static TfLiteRegistration r = {nullptr, nullptr, reshape::Prepare, 85 reshape::Eval};
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/external/clang/test/Analysis/ |
H A D | malloc-interprocedural.c | 77 static char *reshape(char *in) { function 83 v = reshape(v); 84 v = reshape(v);// expected-warning {{Potential leak of memory pointed to by 'v'}}
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/external/tensorflow/tensorflow/compiler/xla/service/ |
H A D | reshape_mover_test.cc | 74 // Verifies that the reshape is not moved, since rng0 is trivially reshapable 294 // where there is only 1 non-trivial reshape (reshape0), we sink the reshape 339 // There is 1 non-trivial reshape (reshape0). It's not clear whether reshape1 465 // reshape [128,1] constant [128,1024] 469 // The reshape mover would like to sink the reshape below the multiply. 471 // Previously we would attempt to insert a reshape of the constant to [1,128,1] 473 // preparation for sinking the reshape. 475 // To eliminate the unsoundness, we outlaw reshape sinkin 492 auto reshape = builder.AddInstruction(HloInstruction::CreateReshape( local [all...] |
H A D | user_computation_test.cc | 256 // reshape | 270 const HloInstruction* reshape = broadcast->operand(0); local 271 EXPECT_TRUE(reshape->has_sharding()); 322 // reshape and a broadcast. 326 // broadcast reshape
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H A D | layout_assignment_test.cc | 321 // param -> log -> reshape -> tanh 329 auto reshape = local 332 HloInstruction::CreateUnary(bshape, HloOpcode::kTanh, reshape)); 355 AsInt64Slice(reshape->shape().layout().minor_to_major()); 517 // param0 -> concatenate -> reshape 529 auto reshape = builder.AddInstruction( local 533 module->AddEntryComputation(builder.Build(reshape));
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H A D | hlo_instruction_test.cc | 1094 HloInstruction* reshape = local 1100 HloInstruction::CreateDot(sout, x, reshape, dot_dnums)); 1105 {dot, reshape}, HloInstruction::FusionKind::kTransposeDot); 1233 HloInstruction* reshape = local 1239 HloInstruction::CreateDot(sout, x, reshape, dot_dnums)); 1250 {dot, reshape}, HloInstruction::FusionKind::kTransposeDot);
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H A D | hlo_verifier.cc | 188 Status ShapeVerifier::HandleReshape(HloInstruction* reshape) { argument 190 TF_RETURN_IF_ERROR(CheckShape(reshape, reshape->shape())); 191 TF_RET_CHECK(ShapeUtil::ElementsIn(reshape->shape()) == 192 ShapeUtil::ElementsIn(reshape->operand(0)->shape()));
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H A D | algebraic_simplifier.cc | 74 // Returns true if the given reshape produces a result which is bit-wise 78 // reshape may still be a bitcast. For example, a reshape from [28x28] to [784]. 80 const HloInstruction* reshape, 82 CHECK_EQ(HloOpcode::kReshape, reshape->opcode()); 84 const HloInstruction* operand = reshape->operand(0); 87 return ShapeUtil::ReshapeIsBitcast(operand->shape(), reshape->shape()) && 88 valid_bitcast_callback(operand->shape(), reshape->shape()); 157 Status HandleReshape(HloInstruction* reshape) override; 710 // reshape(resul 79 ReshapeIsBitcast( const HloInstruction* reshape, const AlgebraicSimplifier::ValidBitcastCallback& valid_bitcast_callback) argument 1495 HandleReshape(HloInstruction* reshape) argument 1685 auto reshape = computation_->AddInstruction( local [all...] |
H A D | algebraic_simplifier_test.cc | 1211 // Test that a reshape which could be replaced with a bitcast is not if 1218 HloInstruction* reshape = local 1223 *reshape->mutable_shape()->mutable_layout() = 1281 // Verify that only the first reshape is replaced. 1313 // Regression test for a bug in the reshape sinking transformation, where 1314 // moving a reshape to a scalar led to a crash. 1320 HloInstruction* reshape = builder.AddInstruction( local 1325 ShapeUtil::MakeShape(F32, {3}), HloOpcode::kMaximum, reshape, zero)); local 1340 // Regression test for a bug where if we failed to sink a reshape, we'd set the 1363 // Regression test for a bug where if we failed to sink a reshape, w 2209 HloInstruction* reshape = builder.AddInstruction( local [all...] |
/external/tensorflow/tensorflow/contrib/metrics/python/kernel_tests/ |
H A D | histogram_ops_test.py | 237 def reshape(scores): function in function:synthetic_data 240 false_scores = reshape(false_scores) 241 true_scores = reshape(true_scores)
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/external/tensorflow/tensorflow/contrib/labeled_tensor/python/ops/ |
H A D | ops.py | 300 def reshape(labeled_tensor, existing_axes, new_axes, name=None): function 368 reshaped_tensor = array_ops.reshape( 398 return reshape(labeled_tensor, [existing_name], [new_axis], name=scope) 817 'Use transpose and reshape to create a single shared axis to sum ' 851 a_tensor = array_ops.reshape(a.tensor, (1, -1)) 859 b_tensor = array_ops.reshape(b.tensor, (-1, 1))
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/external/tensorflow/tensorflow/contrib/labeled_tensor/ |
H A D | __init__.py | 107 reshape = _ops.reshape variable
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/external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
H A D | TensorBase.h | 738 reshape(const NewDimensions& newDimensions) const { function in class:Eigen::TensorBase 907 reshape(const NewDimensions& newDimensions) const { function in class:Eigen::TensorBase 912 reshape(const NewDimensions& newDimensions) { function in class:Eigen::TensorBase
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/external/tensorflow/tensorflow/compiler/xla/ |
H A D | literal_util_test.cc | 546 auto reshape = original->Reshape(/*dimensions=*/{}).ConsumeValueOrDie(); local 547 EXPECT_EQ(*original, *reshape); 565 auto reshape = original->Reshape({3, 4, 2}).ConsumeValueOrDie(); local 567 EXPECT_EQ(*expected, *reshape); 585 auto reshape = original->Reshape({3, 4, 2}).ConsumeValueOrDie(); local 587 EXPECT_EQ(*expected, *reshape); 592 auto reshape = original->Transpose(/*permutation=*/{}); local 593 EXPECT_EQ(*original, *reshape); 605 auto reshape = original->Transpose(/*permutation=*/{2, 3, 0, 1}); local 607 reshape [all...] |
/external/tensorflow/tensorflow/contrib/keras/api/keras/backend/ |
H A D | __init__.py | 117 from tensorflow.python.keras._impl.keras.backend import reshape namespace
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/external/tensorflow/tensorflow/core/grappler/optimizers/ |
H A D | arithmetic_optimizer_test.cc | 613 // The target shape of the reshape is the concatenation of `batch_size` and 620 Output reshape = ops::Reshape(s, inputs, target_shape); local 621 Output outputs = ops::Identity(s.WithOpName("outputs"), reshape); 644 Output reshape = ops::Reshape(s, inputs, ops::Const(s, {8, -1, 28, 28}, {4})); local 645 Output outputs = ops::Identity(s.WithOpName("outputs"), reshape); 666 Output reshape = ops::Reshape(s, inputs, ops::Const(s, {-1, -1}, {2})); local 667 Output outputs = ops::Identity(s.WithOpName("outputs"), reshape);
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H A D | constant_folding_test.cc | 1214 // Build a simple graph with a reshape that can be reduced to the identity. 1217 // A reshape than can be optimized 1227 // A multi dimensional reshape than can be optimized 1235 // A multi dimensional partially defined reshape than can be optimized 1243 // A reshape that can't be optimized 1391 Output reshape = ops::Reshape(s.WithOpName("reshape"), sum, size); local 1395 item.fetch.push_back("reshape");
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/external/tensorflow/tensorflow/python/keras/backend/ |
H A D | __init__.py | 117 from tensorflow.python.keras._impl.keras.backend import reshape namespace
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