!14211 [MSLITE] Support conv1d.
From: @wang_shaocong Reviewed-by: @zhanghaibo5,@zhang_xue_tong Signed-off-by:pull/14211/MERGE
mindspore-ci-bot
4 years ago
committed by
Gitee
commit
5588a398be
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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 "tools/optimizer/fusion/squeeze_fusion.h"
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#include <memory>
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#include "schema/inner/model_generated.h"
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#include "tools/optimizer/common/gllo_utils.h"
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namespace mindspore::opt {
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const BaseRef SqueezeFusion::DefinePattern() const {
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auto squeeze_var = std::make_shared<CondVar>(IsSqueezeNode);
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auto act_var = std::make_shared<CondVar>(IsActivationNode);
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VectorRef act_ref = VectorRef({act_var, squeeze_var});
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auto unsqueeze_var = std::make_shared<CondVar>(IsSqueezeNode);
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return VectorRef({unsqueeze_var, act_ref});
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}
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const AnfNodePtr SqueezeFusion::Process(const FuncGraphPtr &func_graph, const AnfNodePtr &unsqueeze_node,
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const EquivPtr &) const {
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MS_ASSERT(func_graph != nullptr);
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MS_ASSERT(node != nullptr);
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if (CheckIfFuncGraphIsNull(func_graph) != lite::RET_OK || CheckIfAnfNodeIsNull(unsqueeze_node) != lite::RET_OK) {
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lite::ReturnCode::GetSingleReturnCode()->UpdateReturnCode(lite::RET_NULL_PTR);
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return nullptr;
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}
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auto act_node = unsqueeze_node->cast<CNodePtr>()->input(1);
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if (CheckIfCNodeIsNull(act_node->cast<CNodePtr>()) != lite::RET_OK) {
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return nullptr;
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}
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auto squeeze_node = act_node->cast<CNodePtr>()->input(1);
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if (CheckIfCNodeIsNull(squeeze_node->cast<CNodePtr>()) != lite::RET_OK) {
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return nullptr;
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}
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auto pre_node = squeeze_node->cast<CNodePtr>()->input(1);
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if (CheckIfCNodeIsNull(pre_node->cast<CNodePtr>()) != lite::RET_OK) {
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return nullptr;
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}
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if (GetCNodePrimitive(unsqueeze_node)->GetAttr("axis") == GetCNodePrimitive(unsqueeze_node)->GetAttr("axis")) {
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auto manager = func_graph->manager();
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MS_ASSERT(manager != nullptr);
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manager->Replace(unsqueeze_node, act_node);
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manager->Replace(squeeze_node, pre_node);
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return pre_node;
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}
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return nullptr;
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}
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} // namespace mindspore::opt
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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_LITE_SRC_PASS_FUSION_SQUEEZE_FUSION_H_
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#define MINDSPORE_LITE_SRC_PASS_FUSION_SQUEEZE_FUSION_H_
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#include <string>
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#include "backend/optimizer/common/optimizer.h"
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#include "schema/inner/model_generated.h"
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namespace mindspore {
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namespace opt {
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class SqueezeFusion : public PatternProcessPass {
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public:
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explicit SqueezeFusion(bool multigraph = true, const std::string &name = "squeeze_fusion")
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: PatternProcessPass(name, multigraph) {}
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~SqueezeFusion() 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_LITE_SRC_PASS_FUSION_SQUEEZE_FUSION_H_
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@ -0,0 +1,106 @@
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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 "tools/optimizer/graph/conv1d_inout_adjust_pass.h"
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#include <string>
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#include <vector>
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#include <algorithm>
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#include <memory>
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#include "mindspore/lite/include/errorcode.h"
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#include "ops/conv2d.h"
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#include "ops/squeeze.h"
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#include "ops/unsqueeze.h"
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#include "ops/primitive_c.h"
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#include "tools/optimizer/common/gllo_utils.h"
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namespace mindspore::opt {
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CNodePtr Conv1DInOutAdjustPass::NewUnsqueezeOpNode(const FuncGraphPtr &func_graph, const AnfNodePtr input_node,
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const std::vector<int64_t> &axis) {
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auto unsqueeze_prim = std::make_shared<ops::Unsqueeze>();
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if (unsqueeze_prim == nullptr) {
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MS_LOG(ERROR) << "create unsqueeze failed.";
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return nullptr;
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}
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unsqueeze_prim->set_attr("axis", MakeValue(axis));
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ValueNodePtr value_node = NewValueNode(unsqueeze_prim);
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std::vector<AnfNodePtr> op_inputs = {value_node, input_node};
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auto unsqueeze = func_graph->NewCNode(op_inputs);
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unsqueeze->set_fullname_with_scope(input_node->fullname_with_scope() + "_unsqueeze");
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return unsqueeze;
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}
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CNodePtr Conv1DInOutAdjustPass::NewSqueezeOpNode(const FuncGraphPtr &func_graph, const AnfNodePtr input_node,
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const std::vector<int64_t> &axis) {
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auto squeeze_prim = std::make_shared<ops::Squeeze>();
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if (squeeze_prim == nullptr) {
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MS_LOG(ERROR) << "create squeeze failed.";
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return nullptr;
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}
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squeeze_prim->set_attr("axis", MakeValue(axis));
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ValueNodePtr value_node = NewValueNode(squeeze_prim);
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std::vector<AnfNodePtr> op_inputs = {value_node, input_node};
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auto squeeze = func_graph->NewCNode(op_inputs);
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squeeze->set_fullname_with_scope(input_node->fullname_with_scope() + "_squeeze");
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return squeeze;
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}
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bool Conv1DInOutAdjustPass::Run(const FuncGraphPtr &func_graph) {
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MS_ASSERT(func_graph != nullptr);
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auto manager = func_graph->manager();
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MS_ASSERT(manager != nullptr);
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auto cnodes = func_graph->GetOrderedCnodes();
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for (auto &cnode : cnodes) {
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if (!CheckPrimitiveType(cnode, prim::kPrimConv2D) && !CheckPrimitiveType(cnode, prim::kPrimConv2DFusion)) {
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continue;
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}
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auto conv2d_node = GetValueNode<std::shared_ptr<mindspore::ops::Conv2D>>(cnode->input(0));
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if (conv2d_node == nullptr) {
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MS_LOG(ERROR) << "conv2d is nullptr.";
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return false;
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}
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if (conv2d_node->GetAttr(ops::kFormat) == nullptr) {
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MS_LOG(ERROR) << "The format of conv2d is nullptr.";
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return false;
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}
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std::vector<int64_t> axis;
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switch (conv2d_node->get_format()) {
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case mindspore::Format::NWC:
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axis = {1};
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break;
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case mindspore::Format::NCW:
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axis = {2};
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break;
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default:
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continue;
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}
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auto input_node = cnode->input(1);
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auto unsqueeze = NewUnsqueezeOpNode(func_graph, input_node, axis);
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if (unsqueeze == nullptr) {
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MS_LOG(ERROR) << "New unsqueeze node failed.";
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return false;
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}
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manager->Replace(input_node, unsqueeze);
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auto squeeze = NewSqueezeOpNode(func_graph, cnode, axis);
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if (squeeze == nullptr) {
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MS_LOG(ERROR) << "New squeeze node failed.";
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return false;
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}
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manager->Replace(cnode, squeeze);
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}
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return true;
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}
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} // namespace mindspore::opt
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@ -0,0 +1,40 @@
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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_LITE_TOOLS_OPTIMIZER_GRAPH_CONV1D_INOUT_ADJUST_PASS_H_
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#define MINDSPORE_LITE_TOOLS_OPTIMIZER_GRAPH_CONV1D_INOUT_ADJUST_PASS_H_
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#include <string>
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#include <vector>
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#include "backend/optimizer/common/pass.h"
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#include "backend/optimizer/common/optimizer.h"
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#include "tools/converter/converter_flags.h"
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namespace mindspore::opt {
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class Conv1DInOutAdjustPass : public Pass {
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public:
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Conv1DInOutAdjustPass() : Pass("conv1d_inout_adjust_pass") {}
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~Conv1DInOutAdjustPass() override = default;
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bool Run(const FuncGraphPtr &func_graph) override;
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private:
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CNodePtr NewUnsqueezeOpNode(const FuncGraphPtr &func_graph, const AnfNodePtr input_node,
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const std::vector<int64_t> &axis);
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CNodePtr NewSqueezeOpNode(const FuncGraphPtr &func_graph, const AnfNodePtr input_node,
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const std::vector<int64_t> &axis);
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};
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} // namespace mindspore::opt
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#endif // MINDSPORE_LITE_TOOLS_OPTIMIZER_GRAPH_CONV1D_INOUT_ADJUST_PASS_H_
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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 "tools/optimizer/graph/conv1d_weight_expanding_pass.h"
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#include <memory>
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#include <algorithm>
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#include <vector>
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namespace mindspore::opt {
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namespace {
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constexpr size_t kTripleNum = 3;
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constexpr size_t kConvWeightIndex = 2;
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} // namespace
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lite::STATUS Conv1DWeightExpandingPass::ExpandFilterShape(const ParamValueLitePtr &tensor) {
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if (tensor == nullptr) {
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return lite::RET_NULL_PTR;
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}
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auto shape = tensor->tensor_shape();
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std::vector<int> new_shape(shape);
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switch (tensor->format()) {
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case schema::Format_NCHW:
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case schema::Format_KCHW:
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new_shape.insert(new_shape.begin() + 2, 1);
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break;
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case schema::Format_NHWC:
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case schema::Format_KHWC:
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new_shape.insert(new_shape.begin() + 1, 1);
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break;
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default:
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MS_LOG(ERROR) << "Unsupported format.";
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return RET_ERROR;
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}
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tensor->set_tensor_shape(new_shape);
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return RET_OK;
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}
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bool Conv1DWeightExpandingPass::Run(const FuncGraphPtr &func_graph) {
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MS_ASSERT(func_graph != nullptr);
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auto node_list = TopoSort(func_graph->get_return());
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for (auto &node : node_list) {
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if (!utils::isa<CNodePtr>(node)) {
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continue;
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}
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if (!CheckPrimitiveType(node, prim::kPrimConv2D) && !CheckPrimitiveType(node, prim::kPrimConv2DFusion)) {
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continue;
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}
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auto conv_cnode = node->cast<CNodePtr>();
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MS_ASSERT(conv_cnode->inputs().size() > kConvWeightIndex);
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auto weight_node = conv_cnode->input(kConvWeightIndex);
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MS_ASSERT(weight_node != nullptr);
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auto weight_value = GetLiteParamValue(weight_node);
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if (weight_value == nullptr) {
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MS_LOG(ERROR) << "weight node must be param value.";
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return false;
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}
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// expand weight tensor to 4 dimensions.
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if (weight_value->tensor_shape().size() == kTripleNum) {
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auto status = ExpandFilterShape(weight_value);
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if (status != RET_OK) {
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MS_LOG(ERROR) << "Expand filter shape failed.";
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return false;
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}
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}
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}
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return RET_OK;
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}
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} // namespace mindspore::opt
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@ -0,0 +1,37 @@
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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_LITE_SRC_PASS_FUSION_CONV1D_WEIGHT_EXPANDING_PASS_H_
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#define MINDSPORE_LITE_SRC_PASS_FUSION_CONV1D_WEIGHT_EXPANDING_PASS_H_
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#include <string>
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#include "schema/inner/model_generated.h"
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#include "tools/converter/converter_flags.h"
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#include "backend/optimizer/common/pass.h"
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#include "tools/optimizer/common/gllo_utils.h"
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using mindspore::ParamValueLitePtr;
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namespace mindspore::opt {
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class Conv1DWeightExpandingPass : public Pass {
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public:
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Conv1DWeightExpandingPass() : Pass("conv1d_weight_expanding_pass") {}
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~Conv1DWeightExpandingPass() override = default;
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bool Run(const FuncGraphPtr &graph) override;
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private:
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lite::STATUS ExpandFilterShape(const ParamValueLitePtr &tensor);
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};
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} // namespace mindspore::opt
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#endif // MINDSPORE_LITE_SRC_PASS_FUSION_CONV1D_WEIGHT_EXPANDING_PASS_H_
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