/external/tensorflow/tensorflow/compiler/xla/service/ |
D | hlo_sharding_test.cc | 42 HloSharding sharding = HloSharding::Replicate(); in TEST_F() local 43 EXPECT_TRUE(sharding.IsReplicated()); in TEST_F() 44 EXPECT_TRUE(sharding.IsTileMaximal()); in TEST_F() 45 EXPECT_TRUE(sharding.UsesDevice(0)); in TEST_F() 46 EXPECT_TRUE(sharding.UsesDevice(65535)); in TEST_F() 49 EXPECT_EQ(other, sharding); in TEST_F() 51 EXPECT_IS_OK(sharding.Validate(ShapeUtil::MakeShape(U32, {4}), in TEST_F() 53 EXPECT_FALSE(sharding.HasUniqueDevice()); in TEST_F() 57 HloSharding sharding = HloSharding::AssignDevice(5); in TEST_F() local 58 EXPECT_FALSE(sharding.IsReplicated()); in TEST_F() [all …]
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D | hlo_sharding_metadata.cc | 53 const HloSharding& sharding) { in SetSingleSharding() argument 54 VLOG(4) << " " << instruction->name() << " to " << sharding; in SetSingleSharding() 55 instruction->set_single_sharding(sharding); in SetSingleSharding() 120 const HloSharding& sharding) { in FixupPassThroughDomainLinks() argument 127 gte->set_sharding(sharding); in FixupPassThroughDomainLinks() 143 std::shared_ptr<const HloSharding> sharding) { in CloneShardingForDomain() argument 144 auto single_sharding = sharding->ExtractSingleSharding(); in CloneShardingForDomain() 146 return sharding; in CloneShardingForDomain() 152 const HloSharding& sharding) { in ApplyDomainSingleSharding() argument 153 VLOG(4) << "Applying " << sharding << " sharding"; in ApplyDomainSingleSharding() [all …]
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D | hlo_domain_test.cc | 431 new_tuple->sharding(), in TEST_F() 472 EXPECT_EQ(root->sharding(), HloSharding::AssignDevice(1)); in TEST_F() 529 tpl->sharding()); in TEST_F() 540 domain={kind="sharding", entry={maximal device=1}, exit={maximal device=0}} in TEST_F() 543 domain={kind="sharding", entry={maximal device=1}, exit={maximal device=0}} in TEST_F() 546 domain={kind="sharding", entry={maximal device=0}, exit={maximal device=1}} in TEST_F() 550 domain={kind="sharding", entry={maximal device=0}, exit={maximal device=1}} in TEST_F() 555 domain={kind="sharding", entry={maximal device=0}, exit={maximal device=1}} in TEST_F() 668 tuple0->sharding()); in TEST_F() 673 copy0->sharding()); in TEST_F() [all …]
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D | hlo_sharding.cc | 62 for (auto& sharding : shardings) { in Tuple() local 63 CHECK(!sharding.IsTuple()) << sharding.ToString(); in Tuple() 73 const HloSharding& sharding) { in SingleTuple() argument 75 CHECK(!sharding.IsTuple()) << sharding.ToString(); in SingleTuple() 78 flattened_list.resize(leaf_count, sharding); in SingleTuple() 83 const HloSharding& sharding) { in Single() argument 84 return shape.IsTuple() ? SingleTuple(shape, sharding) : sharding; in Single() 366 TF_ASSIGN_OR_RETURN(HloSharding sharding, in FromProto() 368 tuple_shardings.push_back(sharding); in FromProto() 501 std::ostream& operator<<(std::ostream& out, const HloSharding& sharding) { in operator <<() argument [all …]
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D | hlo_sharding_metadata.h | 30 explicit ShardingMetadata(std::shared_ptr<const HloSharding> sharding) in ShardingMetadata() argument 31 : sharding_(std::move(sharding)) {} in ShardingMetadata() 43 const HloSharding* sharding() const { return sharding_.get(); } in sharding() function 77 std::shared_ptr<const HloSharding> sharding; member
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D | hlo_sharding.h | 74 const HloSharding& sharding); 78 static HloSharding Single(const Shape& shape, const HloSharding& sharding); 198 size_t operator()(const HloSharding& sharding) const { in operator() 199 return sharding.Hash(); in operator() 283 std::ostream& operator<<(std::ostream& out, const HloSharding& sharding);
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D | batchnorm_expander.cc | 305 const HloSharding& sharding = batch_norm->sharding(); in HandleBatchNormTraining() local 307 sharding.GetAsShapeTree(batch_norm->shape()).element({0}); in HandleBatchNormTraining() 320 tuple->set_sharding(sharding); in HandleBatchNormTraining() 411 const HloSharding& sharding = batch_norm->sharding(); in HandleBatchNormInference() local 419 inst->set_sharding(sharding); in HandleBatchNormInference() 424 shifted_normalized->set_sharding(sharding); in HandleBatchNormInference() 584 const HloSharding& sharding = batch_norm->sharding(); in HandleBatchNormGrad() local 589 sharding.GetAsShapeTree(batch_norm->shape()).element({0}); in HandleBatchNormGrad() 602 tuple->set_sharding(sharding); in HandleBatchNormGrad()
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D | hlo_matchers.h | 138 explicit HloShardingMatcher(const absl::optional<HloSharding>& sharding) in HloShardingMatcher() argument 139 : sharding_(sharding) {} in HloShardingMatcher() 373 const HloSharding& sharding) { in Sharding() argument 375 new ::xla::testing::HloShardingMatcher(sharding)); in Sharding() 379 absl::string_view sharding) { in Sharding() argument 381 ParseSharding(sharding).ValueOrDie())); in Sharding()
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D | hlo_parser_test.cc | 223 %v1 = f32[4]{0} parameter(0), sharding={maximal device=1} in CreateTestCases() 224 %v2 = f32[4]{0} parameter(1), sharding={maximal device=1} in CreateTestCases() 225 …%greater-than = pred[4]{0} compare(f32[4]{0} %v1, f32[4]{0} %v2), direction=GT, sharding={replicat… in CreateTestCases() 226 …ROOT %select = f32[4]{0} select(pred[4]{0} %greater-than, f32[4]{0} %v1, f32[4]{0} %v2), sharding=… in CreateTestCases() 264 …{0}, f32[2,3]{1,0}) tuple(f32[] %v1, f32[3]{0} %v2, f32[2,3]{1,0} %v3), sharding={{replicated}, {m… in CreateTestCases() 312 %recv = (f32[], u32[], token[]) recv(token[] %token0), channel_id=15, sharding={maximal device=1} in CreateTestCases() 313 …32[], token[]) recv-done((f32[], u32[], token[]) %recv), channel_id=15, sharding={maximal device=1} in CreateTestCases() 314 %constant = f32[] constant(2.1), sharding={maximal device=0} in CreateTestCases() 315 …%send = (f32[], u32[], token[]) send(f32[] %constant, token[] %token0), channel_id=16, sharding={m… in CreateTestCases() 316 …%send-done = token[] send-done((f32[], u32[], token[]) %send), channel_id=16, sharding={maximal de… in CreateTestCases() [all …]
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D | hlo_cse_test.cc | 718 domain={kind="sharding", entry={maximal device=0}, exit={maximal device=1}} in TEST_F() 720 domain={kind="sharding", entry={maximal device=0}, exit={maximal device=1}} in TEST_F() 722 domain={kind="sharding", entry={maximal device=0}, exit={maximal device=2}} in TEST_F() 727 domain={kind="sharding", entry={maximal device=1}, exit={maximal device=0}} in TEST_F() 729 domain={kind="sharding", entry={maximal device=1}, exit={maximal device=0}} in TEST_F() 731 domain={kind="sharding", entry={maximal device=2}, exit={maximal device=0}} in TEST_F()
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D | hlo_instruction.h | 1139 const HloSharding& sharding() const { in sharding() function 1158 void set_sharding(const HloSharding& sharding) { in set_sharding() argument 1159 sharding_ = std::make_shared<const HloSharding>(sharding); in set_sharding() 1161 void set_sharding(std::shared_ptr<const HloSharding> sharding) { in set_sharding() argument 1162 sharding_ = std::move(sharding); in set_sharding() 1164 void set_single_sharding(const HloSharding& sharding); 1179 return other->has_sharding() ? sharding() == other->sharding() : false; in has_compatible_sharding()
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D | hlo_parser.cc | 268 bool ParseSharding(OpSharding* sharding); 269 bool ParseSingleSharding(OpSharding* sharding, bool lbrace_pre_lexed); 668 optional<OpSharding> sharding; in ParseInstructionRhs() local 669 attrs["sharding"] = {/*required=*/false, AttrTy::kSharding, &sharding}; in ParseInstructionRhs() 1721 if (sharding) { in ParseInstructionRhs() 1723 HloSharding::FromProto(sharding.value()).ValueOrDie()); in ParseInstructionRhs() 1758 bool HloParser::ParseSharding(OpSharding* sharding) { in ParseSharding() argument 1769 return ParseSingleSharding(sharding, /*lbrace_pre_lexed=*/true); in ParseSharding() 1776 if (!ParseSingleSharding(sharding->add_tuple_shardings(), in ParseSharding() 1782 sharding->set_type(OpSharding::Type::OpSharding_Type_TUPLE); in ParseSharding() [all …]
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D | hlo_instruction.cc | 571 HloSharding sharding, in CreateFromProto() 573 entry_hlo_sharding = std::make_shared<const HloSharding>(sharding); in CreateFromProto() 577 HloSharding sharding, in CreateFromProto() 579 exit_hlo_sharding = std::make_shared<const HloSharding>(sharding); in CreateFromProto() 629 TF_ASSIGN_OR_RETURN(const auto& sharding, in CreateFromProto() 630 HloSharding::FromProto(proto.sharding())); in CreateFromProto() 631 instruction->set_sharding(sharding); in CreateFromProto() 1130 broadcast->set_sharding(operand->sharding()); in CreateBroadcastSequence() 1155 reshaped_operand->set_sharding(operand->sharding()); in CreateBroadcastSequence() 1162 broadcast->set_sharding(operand->sharding()); in CreateBroadcastSequence() [all …]
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D | hlo_matchers_test.cc | 159 auto sharding = HloSharding::Tuple( in TEST() local 162 p2->set_sharding(sharding); in TEST()
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D | hlo_matchers.cc | 193 if (instruction->sharding() == sharding_.value()) { in MatchAndExplain()
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D | layout_assignment.cc | 861 HloSharding sharding = in SetupCopiedInstruction() local 862 !index.empty() && instruction.sharding().IsTuple() in SetupCopiedInstruction() 863 ? instruction.sharding().GetSubSharding(instruction.shape(), index) in SetupCopiedInstruction() 864 : instruction.sharding(); in SetupCopiedInstruction() 869 auto device = sharding.UniqueDevice(); in SetupCopiedInstruction() 871 copy->set_sharding(sharding); in SetupCopiedInstruction()
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/external/tensorflow/tensorflow/compiler/tf2xla/ |
D | sharding_util.cc | 35 xla::OpSharding sharding; in GetShardingFromNodeDef() local 37 if (!sharding.ParseFromString(value)) { in GetShardingFromNodeDef() 42 return absl::optional<xla::OpSharding>(sharding); in GetShardingFromNodeDef() 83 TF_ASSIGN_OR_RETURN(absl::optional<xla::OpSharding> sharding, in ParseShardingFromDevice() 85 return ParseShardingFromDevice(device_name, num_cores_per_replica, sharding); in ParseShardingFromDevice() 94 TF_ASSIGN_OR_RETURN(absl::optional<xla::OpSharding> sharding, in ParseShardingFromDevice() 96 return ParseShardingFromDevice(device_name, num_cores_per_replica, sharding); in ParseShardingFromDevice()
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D | sharding_util_test.cc | 26 [](absl::optional<xla::OpSharding> sharding) -> int64 { in TEST() argument 27 if (sharding.has_value() && in TEST() 28 sharding.value().type() == in TEST() 30 return sharding.value().tile_assignment_devices(0); in TEST()
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D | tf2xla_util.cc | 507 absl::optional<xla::OpSharding> sharding, in SetNodeShardingFromNeighbors() 511 if (sharding.has_value()) { in SetNodeShardingFromNeighbors() 512 TF_RET_CHECK(sharding.value().type() == in SetNodeShardingFromNeighbors() 514 const int core_annotation = sharding.value().tile_assignment_devices(0); in SetNodeShardingFromNeighbors()
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D | xla_compiler.cc | 82 auto sharding, in ComputeArgAndRetvalCores() 84 if (sharding.has_value()) { in ComputeArgAndRetvalCores() 85 TF_RET_CHECK(sharding.value().type() == in ComputeArgAndRetvalCores() 87 return sharding.value().tile_assignment_devices(0); in ComputeArgAndRetvalCores()
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/external/junit-params/ |
D | README.google | 20 38419944 - Fix sharding on CTS.
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/external/tensorflow/tensorflow/compiler/xla/client/ |
D | xla_builder.h | 159 void SetSharding(const OpSharding& sharding) { sharding_ = sharding; } in SetSharding() argument 166 const absl::optional<OpSharding>& sharding() const { return sharding_; } in sharding() function 1014 absl::optional<OpSharding> sharding) in XlaScopedShardingAssignment() argument 1015 : builder_(builder), prev_sharding_(builder->sharding()) { in XlaScopedShardingAssignment() 1016 SetSharding(sharding); in XlaScopedShardingAssignment() 1026 void SetSharding(const absl::optional<OpSharding>& sharding) { in SetSharding() argument 1027 if (sharding.has_value()) { in SetSharding() 1028 builder_->SetSharding(sharding.value()); in SetSharding()
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D | xla_builder.cc | 1292 if (shape.IsArray() && sharding() && in Infeed() 1293 sharding()->type() == OpSharding::Type::OpSharding_Type_OTHER) { in Infeed() 1299 if (sharding() && in Infeed() 1300 sharding()->type() == OpSharding::Type::OpSharding_Type_REPLICATED) { in Infeed() 1313 if (sharding()) { in Infeed() 1315 OpSharding sharding = sharding_builder::AssignDevice(0); in Infeed() local 1316 XlaScopedShardingAssignment scoped_sharding(this, sharding); in Infeed() 1327 if (sharding() && in Infeed() 1328 sharding()->type() == OpSharding::Type::OpSharding_Type_TUPLE) { in Infeed() 1331 OpSharding infeed_instruction_sharding = *sharding(); in Infeed() [all …]
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/external/tensorflow/tensorflow/compiler/xla/ |
D | xla_data.proto | 577 // This sharding is replicated across all devices (implies maximal, 580 // This sharding is maximal - one device runs the entire operation. 582 // This sharding is a tuple - only the tuple_shardings field is valid. 601 // applied, this is inferred from the instruction this sharding gets attached
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/external/autotest/ |
D | global_config.ini | 42 # This is for sharding: Even when sharding, the results (tko tables) should
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