Merge pull request !3091 from VectorSL/batchnorm_gradtags/v0.6.0-beta
| @@ -0,0 +1,88 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #include "backend/optimizer/gpu/replace_bn_grad_cast2_fusion.h" | |||
| #include <memory> | |||
| #include <vector> | |||
| #include <string> | |||
| #include "backend/session/anf_runtime_algorithm.h" | |||
| #include "ir/primitive.h" | |||
| #include "utils/utils.h" | |||
| #include "backend/optimizer/common/helper.h" | |||
| namespace mindspore { | |||
| namespace opt { | |||
| const BaseRef ReplaceBNGradCast2Fusion::DefinePattern() const { | |||
| VectorRef fbn2g = VectorRef({prim::kPrimFusedBatchNormGrad, dy_, x_, scale_, mean_, var_}); | |||
| VectorRef tupleget = VectorRef({prim::kPrimTupleGetItem, fbn2g, index_}); | |||
| VectorRef out_cast = VectorRef({prim::kPrimCast, tupleget}); | |||
| return out_cast; | |||
| } | |||
| const AnfNodePtr ReplaceBNGradCast2Fusion::Process(const FuncGraphPtr &graph, const AnfNodePtr &node, | |||
| const EquivPtr &equiv) const { | |||
| MS_EXCEPTION_IF_NULL(graph); | |||
| MS_EXCEPTION_IF_NULL(node); | |||
| MS_EXCEPTION_IF_NULL(equiv); | |||
| auto tuple = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(node), 0); | |||
| auto index_node = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 1); | |||
| MS_EXCEPTION_IF_NULL(index_node); | |||
| auto value_node = index_node->cast<ValueNodePtr>(); | |||
| MS_EXCEPTION_IF_NULL(value_node); | |||
| int item_idx = GetValue<int>(value_node->value()); | |||
| if (item_idx != 0) { | |||
| return nullptr; | |||
| } | |||
| auto fbn2g = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 0); | |||
| auto dy_ = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 0); | |||
| auto x_ = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 1); | |||
| auto scale = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 2); | |||
| auto mean = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 3); | |||
| auto var = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 4); | |||
| MS_EXCEPTION_IF_NULL(fbn2g); | |||
| MS_EXCEPTION_IF_NULL(dy_); | |||
| MS_EXCEPTION_IF_NULL(scale); | |||
| MS_EXCEPTION_IF_NULL(x_); | |||
| MS_EXCEPTION_IF_NULL(mean); | |||
| MS_EXCEPTION_IF_NULL(var); | |||
| auto manager = graph->manager(); | |||
| MS_EXCEPTION_IF_NULL(manager); | |||
| manager->Replace(utils::cast<CNodePtr>(node), utils::cast<CNodePtr>(tuple)); | |||
| std::vector<TypeId> outputs_type; | |||
| std::vector<std::vector<size_t>> outputs_shape; | |||
| auto output_num = AnfAlgo::GetOutputTensorNum(fbn2g); | |||
| for (size_t i = 0; i < output_num; i++) { | |||
| outputs_type.push_back(AnfAlgo::GetOutputInferDataType(fbn2g, i)); | |||
| outputs_shape.push_back(AnfAlgo::GetOutputInferShape(fbn2g, i)); | |||
| } | |||
| outputs_type[0] = AnfAlgo::GetPrevNodeOutputInferDataType(fbn2g, 0); | |||
| AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, fbn2g.get()); | |||
| outputs_type.clear(); | |||
| outputs_shape.clear(); | |||
| outputs_type.push_back(AnfAlgo::GetPrevNodeOutputInferDataType(fbn2g, 0)); | |||
| outputs_shape.push_back(AnfAlgo::GetOutputInferShape(tuple, 0)); | |||
| AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, tuple.get()); | |||
| return tuple; | |||
| } | |||
| } // namespace opt | |||
| } // namespace mindspore | |||
| @@ -0,0 +1,54 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #ifndef MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST2_FUSION_H_ | |||
| #define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST2_FUSION_H_ | |||
| #include <memory> | |||
| #include "backend/optimizer/common/optimizer.h" | |||
| namespace mindspore { | |||
| namespace opt { | |||
| class ReplaceBNGradCast2Fusion : public PatternProcessPass { | |||
| public: | |||
| explicit ReplaceBNGradCast2Fusion(bool multigraph = true) : PatternProcessPass("replace_grad_cast2", multigraph) { | |||
| dy_ = std::make_shared<Var>(); | |||
| x_ = std::make_shared<Var>(); | |||
| scale_ = std::make_shared<Var>(); | |||
| mean_ = std::make_shared<Var>(); | |||
| var_ = std::make_shared<Var>(); | |||
| dx_ = std::make_shared<Var>(); | |||
| bn_scale_ = std::make_shared<Var>(); | |||
| bn_bias_ = std::make_shared<Var>(); | |||
| index_ = std::make_shared<Var>(); | |||
| } | |||
| ~ReplaceBNGradCast2Fusion() override = default; | |||
| const BaseRef DefinePattern() const override; | |||
| const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override; | |||
| private: | |||
| VarPtr dy_; | |||
| VarPtr x_; | |||
| VarPtr scale_; | |||
| VarPtr mean_; | |||
| VarPtr var_; | |||
| VarPtr dx_; | |||
| VarPtr bn_scale_; | |||
| VarPtr bn_bias_; | |||
| VarPtr index_; | |||
| }; | |||
| } // namespace opt | |||
| } // namespace mindspore | |||
| #endif // MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST2_FUSION_H_ | |||
| @@ -0,0 +1,91 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #include "backend/optimizer/gpu/replace_bn_grad_cast_fusion.h" | |||
| #include <memory> | |||
| #include <vector> | |||
| #include <string> | |||
| #include "backend/session/anf_runtime_algorithm.h" | |||
| #include "ir/primitive.h" | |||
| #include "utils/utils.h" | |||
| #include "backend/optimizer/common/helper.h" | |||
| namespace mindspore { | |||
| namespace opt { | |||
| const BaseRef ReplaceBNGradCastFusion::DefinePattern() const { | |||
| VectorRef dy_cast = VectorRef({prim::kPrimCast, dy_}); | |||
| VectorRef fbn2g = VectorRef({prim::kPrimFusedBatchNormGrad, dy_cast, x_, scale_, mean_, var_}); | |||
| VectorRef tupleget = VectorRef({prim::kPrimTupleGetItem, fbn2g, index_}); | |||
| VectorRef out_cast = VectorRef({prim::kPrimCast, tupleget}); | |||
| return out_cast; | |||
| } | |||
| const AnfNodePtr ReplaceBNGradCastFusion::Process(const FuncGraphPtr &graph, const AnfNodePtr &node, | |||
| const EquivPtr &equiv) const { | |||
| MS_EXCEPTION_IF_NULL(graph); | |||
| MS_EXCEPTION_IF_NULL(node); | |||
| MS_EXCEPTION_IF_NULL(equiv); | |||
| auto tuple = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(node), 0); | |||
| auto index_node = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 1); | |||
| MS_EXCEPTION_IF_NULL(index_node); | |||
| auto value_node = index_node->cast<ValueNodePtr>(); | |||
| MS_EXCEPTION_IF_NULL(value_node); | |||
| int item_idx = GetValue<int>(value_node->value()); | |||
| if (item_idx != 0) { | |||
| return nullptr; | |||
| } | |||
| auto fbn2g = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 0); | |||
| auto dy_after = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 0); | |||
| auto dy_before = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(dy_after), 0); | |||
| auto x_ = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 1); | |||
| auto scale = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 2); | |||
| auto mean = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 3); | |||
| auto var = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 4); | |||
| MS_EXCEPTION_IF_NULL(fbn2g); | |||
| MS_EXCEPTION_IF_NULL(dy_after); | |||
| MS_EXCEPTION_IF_NULL(dy_before); | |||
| MS_EXCEPTION_IF_NULL(scale); | |||
| MS_EXCEPTION_IF_NULL(x_); | |||
| MS_EXCEPTION_IF_NULL(mean); | |||
| MS_EXCEPTION_IF_NULL(var); | |||
| auto manager = graph->manager(); | |||
| MS_EXCEPTION_IF_NULL(manager); | |||
| manager->Replace(utils::cast<CNodePtr>(dy_after), utils::cast<CNodePtr>(dy_before)); | |||
| manager->Replace(utils::cast<CNodePtr>(node), utils::cast<CNodePtr>(tuple)); | |||
| std::vector<TypeId> outputs_type; | |||
| std::vector<std::vector<size_t>> outputs_shape; | |||
| auto output_num = AnfAlgo::GetOutputTensorNum(fbn2g); | |||
| for (size_t i = 0; i < output_num; i++) { | |||
| outputs_type.push_back(AnfAlgo::GetOutputInferDataType(fbn2g, i)); | |||
| outputs_shape.push_back(AnfAlgo::GetOutputInferShape(fbn2g, i)); | |||
| } | |||
| outputs_type[0] = kNumberTypeFloat16; | |||
| AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, fbn2g.get()); | |||
| outputs_type.clear(); | |||
| outputs_shape.clear(); | |||
| outputs_type.push_back(kNumberTypeFloat16); | |||
| outputs_shape.push_back(AnfAlgo::GetOutputInferShape(tuple, 0)); | |||
| AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, tuple.get()); | |||
| return tuple; | |||
| } | |||
| } // namespace opt | |||
| } // namespace mindspore | |||
| @@ -0,0 +1,54 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #ifndef MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST_FUSION_H_ | |||
| #define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST_FUSION_H_ | |||
| #include <memory> | |||
| #include "backend/optimizer/common/optimizer.h" | |||
| namespace mindspore { | |||
| namespace opt { | |||
| class ReplaceBNGradCastFusion : public PatternProcessPass { | |||
| public: | |||
| explicit ReplaceBNGradCastFusion(bool multigraph = true) : PatternProcessPass("replace_bn_grad_cast", multigraph) { | |||
| dy_ = std::make_shared<Var>(); | |||
| x_ = std::make_shared<Var>(); | |||
| scale_ = std::make_shared<Var>(); | |||
| mean_ = std::make_shared<Var>(); | |||
| var_ = std::make_shared<Var>(); | |||
| dx_ = std::make_shared<Var>(); | |||
| bn_scale_ = std::make_shared<Var>(); | |||
| bn_bias_ = std::make_shared<Var>(); | |||
| index_ = std::make_shared<Var>(); | |||
| } | |||
| ~ReplaceBNGradCastFusion() override = default; | |||
| const BaseRef DefinePattern() const override; | |||
| const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override; | |||
| private: | |||
| VarPtr dy_; | |||
| VarPtr x_; | |||
| VarPtr scale_; | |||
| VarPtr mean_; | |||
| VarPtr var_; | |||
| VarPtr dx_; | |||
| VarPtr bn_scale_; | |||
| VarPtr bn_bias_; | |||
| VarPtr index_; | |||
| }; | |||
| } // namespace opt | |||
| } // namespace mindspore | |||
| #endif // MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST_FUSION_H_ | |||