baihuawei
4 years ago
parent
b59168bfec
commit
a1c20e568a
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/**
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* Copyright 2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "backend/optimizer/cpu/insert_cast_cpu.h"
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#include <memory>
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#include <string>
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#include <vector>
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#include <utility>
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#include "backend/kernel_compiler/kernel_build_info.h"
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#include "backend/session/anf_runtime_algorithm.h"
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#include "backend/session/kernel_graph.h"
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#include "utils/utils.h"
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#include "backend/kernel_compiler/common_utils.h"
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namespace mindspore {
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namespace opt {
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namespace {
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AnfNodePtr AddCastOpNodeToGraph(const FuncGraphPtr &func_graph, const AnfNodePtr &input, const std::string &format,
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const TypeId &input_type, const TypeId &output_type,
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const std::vector<size_t> &origin_shape, const TypeId &origin_type) {
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MS_EXCEPTION_IF_NULL(func_graph);
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std::string input_format = format;
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std::string output_format = format;
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CNodePtr cast = func_graph->NewCNode({NewValueNode(std::make_shared<Primitive>(prim::kPrimCast->name())), input});
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MS_EXCEPTION_IF_NULL(cast);
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// set kernel build info
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kernel::KernelBuildInfo::KernelBuildInfoBuilder builder;
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builder.SetInputsFormat({input_format});
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builder.SetOutputsFormat({output_format});
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builder.SetInputsDeviceType({input_type});
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builder.SetOutputsDeviceType({output_type});
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// if kernel info is null , it remarks this function is running ut
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if (cast->kernel_info() == nullptr) {
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auto kernel_info = std::make_shared<device::KernelInfo>();
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cast->set_kernel_info(kernel_info);
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}
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AnfAlgo::SetSelectKernelBuildInfo(builder.Build(), cast.get());
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AnfAlgo::SetOutputInferTypeAndShape({origin_type}, {origin_shape}, cast.get());
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AnfAlgo::SetNodeAttr(kIsBackendCast, MakeValue(true), cast);
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return cast;
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}
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AnfNodePtr InsertCastForMultipleOutput(const FuncGraphPtr &func_graph, const CNodePtr &cnode,
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const std::vector<bool> &need_insert_cast) {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(cnode);
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auto kernel_graph = func_graph->cast<KernelGraphPtr>();
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size_t out_num = AnfAlgo::GetOutputTensorNum(cnode);
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for (size_t output_idx = 0; output_idx < out_num; ++output_idx) {
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AnfNodePtr replace_node = nullptr;
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const auto origin_shape = AnfAlgo::GetOutputInferShape(cnode, output_idx);
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const auto infer_type = AnfAlgo::GetOutputInferDataType(cnode, output_idx);
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auto idx = NewValueNode(SizeToLong(output_idx));
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MS_EXCEPTION_IF_NULL(idx);
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auto imm = std::make_shared<Int64Imm>(output_idx);
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idx->set_abstract(std::make_shared<abstract::AbstractScalar>(imm));
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auto getitem = func_graph->NewCNode({NewValueNode(prim::kPrimTupleGetItem), cnode, idx});
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AnfAlgo::SetOutputInferTypeAndShape({infer_type}, {origin_shape}, getitem.get());
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if (need_insert_cast[output_idx]) {
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const auto dev_fmt = AnfAlgo::GetOutputFormat(cnode, output_idx);
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const auto device_type = AnfAlgo::GetOutputDeviceDataType(cnode, output_idx);
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if (infer_type != device_type) {
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replace_node =
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AddCastOpNodeToGraph(func_graph, getitem, dev_fmt, device_type, infer_type, origin_shape, infer_type);
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MS_EXCEPTION_IF_NULL(replace_node);
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replace_node->set_scope(cnode->scope());
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AnfAlgo::SetNodeAttr(kAttrVisited, MakeValue(true), replace_node);
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if (kernel_graph != nullptr && kernel_graph->IsInternalOutput(cnode, output_idx)) {
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kernel_graph->ReplaceInternalOutput(cnode, replace_node, output_idx, 0);
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}
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}
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}
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}
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return cnode;
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}
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void InsertCastForInput(const FuncGraphPtr &func_graph, const CNodePtr &cnode) {
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MS_EXCEPTION_IF_NULL(cnode);
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size_t in_num = AnfAlgo::GetInputTensorNum(cnode);
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auto kernel_graph = func_graph->cast<KernelGraphPtr>();
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auto mng = kernel_graph->manager();
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for (size_t input_index = 0; input_index < in_num; ++input_index) {
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auto prev_node = AnfAlgo::GetPrevNodeOutput(cnode, input_index);
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const auto infer_type = AnfAlgo::GetOutputInferDataType(prev_node.first, prev_node.second);
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auto cur_input = AnfAlgo::GetInputNode(cnode, input_index);
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const std::string dev_fmt = AnfAlgo::GetInputFormat(cnode, input_index);
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const std::vector<size_t> origin_shape = AnfAlgo::GetOutputInferShape(prev_node.first, prev_node.second);
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if (TypeId device_type = AnfAlgo::GetInputDeviceDataType(cnode, input_index); infer_type != device_type) {
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auto cast =
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AddCastOpNodeToGraph(func_graph, cur_input, dev_fmt, infer_type, device_type, origin_shape, device_type);
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MS_EXCEPTION_IF_NULL(cast);
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cast->set_scope(cnode->scope());
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AnfAlgo::SetNodeAttr(kAttrVisited, MakeValue(true), cast);
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mng->Replace(cur_input, cast);
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}
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}
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}
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AnfNodePtr InsertCastForOutput(const FuncGraphPtr &func_graph, const CNodePtr &cnode,
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const std::vector<bool> &need_insert_cast) {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(cnode);
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if (AnfAlgo::GetOutputTensorNum(cnode) == 0) {
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return cnode;
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}
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MS_EXCEPTION_IF_NULL(cnode->Type());
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auto kernel_graph = func_graph->cast<KernelGraphPtr>();
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// Single output
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if (!cnode->Type()->isa<Tuple>()) {
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if (!need_insert_cast[0]) {
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return cnode;
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}
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const std::string dev_fmt = AnfAlgo::GetOutputFormat(cnode, 0);
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std::vector<size_t> origin_shape = AnfAlgo::GetOutputInferShape(cnode, 0);
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const auto infer_type = AnfAlgo::GetOutputInferDataType(cnode, 0);
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const TypeId device_type = AnfAlgo::GetOutputDeviceDataType(cnode, 0);
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AnfNodePtr replace_node = cnode;
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if (infer_type != device_type) {
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replace_node =
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AddCastOpNodeToGraph(func_graph, cnode, dev_fmt, device_type, infer_type, origin_shape, infer_type);
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MS_EXCEPTION_IF_NULL(replace_node);
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replace_node->set_scope(cnode->scope());
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AnfAlgo::SetNodeAttr(kAttrVisited, MakeValue(true), replace_node);
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if (kernel_graph != nullptr && kernel_graph->IsInternalOutput(cnode, 0)) {
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kernel_graph->ReplaceInternalOutput(cnode, replace_node);
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}
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}
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return replace_node;
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}
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// Multiple output
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return InsertCastForMultipleOutput(func_graph, cnode, need_insert_cast);
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}
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} // namespace
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const BaseRef InsertCastCPU::DefinePattern() const {
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VarPtr V = std::make_shared<CondVar>(UnVisited);
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VarPtr Xs = std::make_shared<SeqVar>();
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return VectorRef({V, Xs});
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}
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const AnfNodePtr InsertCastCPU::Process(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
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const EquivPtr &) const {
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MS_EXCEPTION_IF_NULL(node);
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if (!AnfAlgo::IsRealCNodeKernel(node) || func_graph == nullptr) {
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return nullptr;
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}
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AnfAlgo::SetNodeAttr(kAttrVisited, MakeValue(true), node);
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// process input
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CNodePtr cnode = node->cast<CNodePtr>();
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MS_EXCEPTION_IF_NULL(cnode);
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InsertCastForInput(func_graph, cnode);
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// process output
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return InsertCastForOutput(func_graph, cnode, std::vector<bool>(AnfAlgo::GetOutputTensorNum(cnode), true));
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,36 @@
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/**
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* Copyright 2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_CCSRC_BACKEND_OPTIMIZER_CPU_INSERT_CAST_CPU_H
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#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_CPU_INSERT_CAST_CPU_H
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#include <string>
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#include "backend/optimizer/common/optimizer.h"
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#include "ir/anf.h"
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namespace mindspore {
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namespace opt {
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class InsertCastCPU : public PatternProcessPass {
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public:
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explicit InsertCastCPU(bool multigraph = true) : PatternProcessPass("insert_cast_cpu", multigraph) {}
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~InsertCastCPU() override = default;
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const BaseRef DefinePattern() const override;
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const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
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};
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_BACKEND_OPTIMIZER_CPU_INSERT_CAST_CPU_H
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