/external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
D | TensorDimensionList.h | 25 template <typename Index, std::size_t Rank> struct DimensionList { 32 template<typename Index, std::size_t Rank> struct array_size<DimensionList<Index, Rank> > { 33 static const size_t value = Rank; 35 template<typename Index, std::size_t Rank> struct array_size<const DimensionList<Index, Rank> > { 36 static const size_t value = Rank; 39 …emplate<DenseIndex n, typename Index, std::size_t Rank> const Index array_get(DimensionList<Index,… 42 …late<DenseIndex n, typename Index, std::size_t Rank> const Index array_get(const DimensionList<Ind… 48 template <typename Index, std::size_t Rank> 49 struct index_known_statically_impl<DimensionList<Index, Rank> > { 54 template <typename Index, std::size_t Rank> [all …]
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/external/llvm-project/flang/lib/Evaluate/ |
D | intrinsics.cpp | 172 ENUM_CLASS(Rank, 199 Rank rank{Rank::elemental}; 209 {IntType, KindCode::kindArg}, Rank::scalar, 215 {IntType, KindCode::kindArg}, Rank::scalar, Optionality::defaultsToSameKind, 222 {IntType, KindCode::kindArg}, Rank::scalar, Optionality::defaultsToSizeKind, 225 {IntType, KindCode::dimArg}, Rank::scalar, Optionality::required, 228 {IntType, KindCode::dimArg}, Rank::scalar, Optionality::optional, 231 Rank::conformable, Optionality::optional, common::Intent::In}; 238 Rank rank{Rank::elemental}; 267 {"achar", {{"i", AnyInt, Rank::elementalOrBOZ}, DefaultingKIND}, KINDChar}, [all …]
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D | variable.cpp | 248 (field != Field::Len && dim >= 0 && dim < last.Rank())); 256 (field != Field::Len && dim >= 0 && dim < last.Rank())); 359 int BaseObject::Rank() const { in Rank() function in Fortran::evaluate::BaseObject 361 [](SymbolRef symbol) { return symbol->Rank(); }, in Rank() 367 int Component::Rank() const { in Rank() function in Fortran::evaluate::Component 368 if (int rank{symbol_->Rank()}; rank > 0) { in Rank() 371 return base().Rank(); in Rank() 374 int NamedEntity::Rank() const { in Rank() function in Fortran::evaluate::NamedEntity 376 [](const SymbolRef s) { return s->Rank(); }, in Rank() 377 [](const Component &c) { return c.Rank(); }, in Rank() [all …]
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D | call.cpp | 31 int ActualArgument::AssumedType::Rank() const { return symbol_->Rank(); } in Rank() function in Fortran::evaluate::ActualArgument::AssumedType 48 int ActualArgument::Rank() const { in Rank() function in Fortran::evaluate::ActualArgument 50 return expr->Rank(); in Rank() 52 return std::get<AssumedType>(u_).Rank(); in Rank() 99 int ProcedureDesignator::Rank() const { in Rank() function in Fortran::evaluate::ProcedureDesignator 102 return symbol->Rank(); in Rank() 109 return typeAndShape->Rank(); in Rank() 198 int ProcedureRef::Rank() const { in Rank() function in Fortran::evaluate::ProcedureRef 202 if (int rank{arg->Rank()}; rank > 0) { in Rank() 209 return proc_.Rank(); in Rank()
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D | shape.cpp | 36 return shape.Rank() == 0 || shape.IsExplicitShape(); // even if scalar in IsExplicitShape() 43 CHECK(arrayConstant.Rank() == 1); in AsShape() 63 if (expr->Rank() == 0) { in AsShape() 221 if (component.base().Rank() == 0) { in operator ()() 251 int rank{base.Rank()}; in GetLowerBounds() 280 } else if (details->IsAssumedSize() && j == symbol.Rank()) { in GetExtent() 346 } else if (details->IsAssumedSize() && dimension + 1 == symbol.Rank()) { in GetUpperBound() 377 CHECK(dim + 1 == base.Rank()); in GetUpperBounds() 385 CHECK(GetRank(result) == symbol.Rank()); in GetUpperBounds() 399 int n{object.shape().Rank()}; in operator ()() [all …]
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/external/tensorflow/tensorflow/core/ops/ |
D | ragged_math_ops.cc | 56 if (c->Rank(starts) == 1) { in RaggedRangeShapeFn() 59 if (c->Rank(limits) == 1) { in RaggedRangeShapeFn() 62 if (c->Rank(deltas) == 1) { in RaggedRangeShapeFn() 70 } else if (c->Rank(starts) == 0 && c->Rank(limits) == 0 && in RaggedRangeShapeFn() 71 c->Rank(deltas) == 0) { in RaggedRangeShapeFn()
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D | sparse_csr_matrix_ops.cc | 72 if (!c->RankKnown(dense_shape) || c->Rank(dense_shape) < 2 || in __anon59a9d6c30102() 73 c->Rank(dense_shape) > 3) { in __anon59a9d6c30102() 75 "Invalid rank: ", c->Rank(dense_shape), in __anon59a9d6c30102() 101 int rank = c->Rank(sparse_matrix); in __anon59a9d6c30202() 118 if (!c->RankKnown(dense_shape) || c->Rank(dense_shape) < 2 || in __anon59a9d6c30302() 119 c->Rank(dense_shape) > 3) { in __anon59a9d6c30302() 121 "Invalid rank of dense: ", c->Rank(dense_shape), in __anon59a9d6c30302() 124 auto rank = c->Rank(dense_shape); in __anon59a9d6c30302() 127 if (!c->RankKnown(indices) || c->Rank(indices) != 2) { in __anon59a9d6c30302() 130 c->Rank(indices)); in __anon59a9d6c30302() [all …]
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_BoostedTreesSparseAggregateStats.pbtxt | 7 int32; Rank 1 Tensor containing node ids for each example, shape [batch_size]. 13 float32; Rank 2 Tensor (shape=[batch_size, logits_dimension]) with gradients for each example. 19 float32; Rank 2 Tensor (shape=[batch_size, hessian_dimension]) with hessians for each example. 25 int32; Rank 2 indices of feature sparse Tensors (shape=[number of sparse entries, 2]). 34 int32; Rank 1 values of feature sparse Tensors (shape=[number of sparse entries]). 42 int32; Rank 1 dense shape of feature sparse Tensors (shape=[2]). 49 int32; Rank 2 indices of summary sparse Tensors (shape=[number of non zero statistics, 4]) 57 output Rank 1 Tensor (shape=[number of non zero statistics]) 63 output Rank 1 Tensor (shape=[4])
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D | api_def_BoostedTreesSparseCalculateBestFeatureSplit.pbtxt | 7 A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within `stats… 13 A Rank 2 int64 tensor of dense shape [N, 4] (N specifies the number of non-zero values) for accumul… 20 A Rank 1 float tensor of dense shape [N] (N specifies the number of non-zero values), which supplie… 26 A Rank 1 float tensor of dense shape [4], which specifies the dense shape of the sparse tensor, whi… 56 A Rank 1 tensor indicating possible node ids that can be split. 62 A Rank 1 tensor indicating the best gains to split each node. 68 A Rank 1 tensor indicating the best feature dimension for each feature to split for each node. 74 A Rank 1 tensor indicating the bucket id to compare with (as a threshold) for split in each node. 80 A Rank 2 tensor indicating the contribution of the left nodes when branching from parent nodes to t… 87 A Rank 2 tensor, with the same shape/conditions as left_node_contribs_list, but just that the value… [all …]
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D | api_def_BoostedTreesAggregateStats.pbtxt | 7 int32; Rank 1 Tensor containing node ids for each example, shape [batch_size]. 13 float32; Rank 2 Tensor (shape=[batch_size, logits_dimension]) with gradients for each example. 19 float32; Rank 2 Tensor (shape=[batch_size, hessian_dimension]) with hessians for each example. 25 int32; Rank 2 feature Tensors (shape=[batch_size, feature_dimension]). 31 output Rank 4 Tensor (shape=[splits, feature_dimension, buckets, logits_dimension + hessian_dimensi…
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D | api_def_BoostedTreesCalculateBestFeatureSplitV2.pbtxt | 7 A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within `stats… 13 A list of Rank 4 tensor (#shape=[max_splits, feature_dims, bucket, stats_dims]) for accumulated sta… 20 A Rank 1 tensor indicating if this Op should perform inequality split or equality split per feature. 26 Rank 1 tensor with ids for each feature. This is the real id of the feature. 56 A Rank 1 tensors indicating possible split node ids for each feature. The length of the list is num… 62 A Rank 1 tensor indicating the best gains for each feature to split for certain nodes. See above fo… 68 A Rank 1 tensors indicating the best feature id for each node. See above for details like shapes an… 74 A Rank 1 tensors indicating the best feature dimension for each feature to split for certain nodes … 80 A Rank 1 tensors indicating the bucket id to compare with (as a threshold) for split in each node. … 86 A Rank 2 tensors indicating the contribution of the left nodes when branching from parent nodes (gi… [all …]
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D | api_def_BoostedTreesMakeStatsSummary.pbtxt | 7 int32 Rank 1 Tensor containing node ids, which each example falls into for the requested layer. 13 float32; Rank 2 Tensor (shape=[#examples, 1]) for gradients. 19 float32; Rank 2 Tensor (shape=[#examples, 1]) for hessians. 25 int32 list of Rank 1 Tensors, each containing the bucketized feature (for each feature column). 31 output Rank 4 Tensor (shape=[#features, #splits, #buckets, 2]) containing accumulated stats put int…
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D | api_def_BoostedTreesTrainingPredict.pbtxt | 7 Rank 1 Tensor containing cached tree ids which is the starting 14 Rank 1 Tensor containing cached node id which is the starting 28 Rank 2 Tensor containing logits update (with respect to cached 35 Rank 1 Tensor containing new tree ids for each example. 41 Rank 1 Tensor containing new node ids in the new tree_ids.
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D | api_def_BoostedTreesCalculateBestFeatureSplit.pbtxt | 7 A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within `stats… 13 A Rank 4 tensor (#shape=[max_splits, feature_dims, bucket, stats_dims]) for accumulated stats summa… 44 A Rank 1 tensors indicating possible split node ids for each feature. The length of the list is num… 50 A Rank 1 tensors indicating the best gains for each feature to split for certain nodes. See above f… 56 A Rank 1 tensors indicating the best feature dimension for each feature to split for certain nodes … 62 A Rank 1 tensors indicating the bucket id to compare with (as a threshold) for split in each node. … 68 A Rank 2 tensors indicating the contribution of the left nodes when branching from parent nodes (gi… 74 A Rank 2 tensors, with the same shape/conditions as left_node_contribs_list, but just that the valu… 80 A Rank 1 tensors indicating the which direction to go if data is missing. See above for details lik…
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D | api_def_BoostedTreesBucketize.pbtxt | 7 float; List of Rank 1 Tensor each containing float values for a single feature. 13 float; List of Rank 1 Tensors each containing the bucket boundaries for a single 20 int; List of Rank 1 Tensors each containing the bucketized values for a single feature.
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D | api_def_BoostedTreesMakeQuantileSummaries.pbtxt | 7 float; List of Rank 1 Tensors each containing values for a single feature. 13 float; Rank 1 Tensor with weights per instance. 25 float; List of Rank 2 Tensors each containing the quantile summary
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D | api_def_BoostedTreesCalculateBestGainsPerFeature.pbtxt | 7 A Rank 1 tensor (shape=[2]) to specify the range [first, last) of node ids to process within `stats… 13 A list of Rank 3 tensor (#shape=[max_splits, bucket, 2]) for accumulated stats summary (gradient/he… 43 An output list of Rank 1 tensors indicating possible split node ids for each feature. The length of… 49 An output list of Rank 1 tensors indicating the best gains for each feature to split for certain no… 55 An output list of Rank 1 tensors indicating the bucket id to compare with (as a threshold) for spli… 61 A list of Rank 2 tensors indicating the contribution of the left nodes when branching from parent n… 67 A list of Rank 2 tensors, with the same shape/conditions as left_node_contribs_list, but just that …
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D | api_def_MatrixSetDiag.pbtxt | 6 Rank `k+1`, where `k >= 1`. 12 Rank `k`, where `k >= 1`. 18 Rank `k+1`, with `output.shape = input.shape`.
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/external/llvm-project/flang/include/flang/Evaluate/ |
D | variable.h | 53 int Rank() const; 83 int Rank() const; 113 int Rank() const; 144 static constexpr int Rank() { return 0; } // always scalar in Rank() function 183 int Rank() const; 215 int Rank() const; 262 int Rank() const; 285 int Rank() const; 322 int Rank() const; 351 int Rank() const; [all …]
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/external/llvm/include/llvm/Transforms/Scalar/ |
D | Reassociate.h | 38 unsigned Rank; member 40 ValueEntry(unsigned R, Value *O) : Rank(R), Op(O) {} in ValueEntry() 43 return LHS.Rank > RHS.Rank; // Sort so that highest rank goes to start.
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/external/swiftshader/third_party/llvm-10.0/llvm/include/llvm/Transforms/Scalar/ |
D | Reassociate.h | 47 unsigned Rank; member 50 ValueEntry(unsigned R, Value *O) : Rank(R), Op(O) {} in ValueEntry() 54 return LHS.Rank > RHS.Rank; // Sort so that highest rank goes to start.
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/external/llvm-project/openmp/libomptarget/deviceRTLs/common/src/ |
D | support.cu | 193 unsigned Rank = __kmpc_impl_popc(Mask & LaneMaskLt); in IncParallelLevel() local 194 if (Rank == 0) { in IncParallelLevel() 205 unsigned Rank = __kmpc_impl_popc(Mask & LaneMaskLt); in DecParallelLevel() local 206 if (Rank == 0) { in DecParallelLevel()
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/external/llvm-project/llvm/include/llvm/Transforms/Scalar/ |
D | Reassociate.h | 47 unsigned Rank; member 50 ValueEntry(unsigned R, Value *O) : Rank(R), Op(O) {} in ValueEntry() 54 return LHS.Rank > RHS.Rank; // Sort so that highest rank goes to start.
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/external/llvm/lib/Transforms/Instrumentation/ |
D | CFGMST.h | 63 if (BB1G->Rank < BB2G->Rank) in unionGroups() 68 if (BB1G->Rank == BB2G->Rank) in unionGroups() 69 BB1G->Rank++; in unionGroups()
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/external/swiftshader/third_party/llvm-10.0/llvm/lib/Transforms/Instrumentation/ |
D | CFGMST.h | 69 if (BB1G->Rank < BB2G->Rank) in unionGroups() 74 if (BB1G->Rank == BB2G->Rank) in unionGroups() 75 BB1G->Rank++; in unionGroups()
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