forked from mindspore-Ecosystem/mindspore
add node output and shape pass
This commit is contained in:
zhujingxuan
parent
55c71a6034
commit
beeb36d075
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@ -59,6 +59,9 @@ file(GLOB_RECURSE CONVERTER_SRC RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
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../optimizer/fusion/tf_gelu_fusion.cc
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../optimizer/fusion/onnx_gelu_fusion.cc
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../optimizer/fusion/squeeze_fusion.cc
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../optimizer/fisson/fisson_util.cc
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../optimizer/fisson/iter_node_outputs.cc
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../optimizer/fisson/node_out_shapes.cc
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../optimizer/graph/conv1d_inout_adjust_pass.cc
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../optimizer/graph/weight_format_transform_pass.cc
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../optimizer/graph/weight_format_hardcode_pass.cc
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@ -0,0 +1,129 @@
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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 <unordered_set>
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#include <unordered_map>
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#include <memory>
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#include "tools/optimizer/fisson/fisson_util.h"
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#include "mindspore/core/base/core_ops.h"
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#include "src/common/utils.h"
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#include "tools/common/node_util.h"
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namespace mindspore {
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using lite::converter::FmkType;
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namespace opt {
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std::unordered_map<std::string, std::vector<AnfNodePtr>> g_graph_nodes_output = {};
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std::unordered_map<std::string, std::vector<std::vector<ShapeVector>>> g_graph_nodes_out_shapes = {};
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AnfNodePtr CreateOutputsOfConcat(const FuncGraphPtr &func_graph, const CNodePtr &conv_cnode,
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const std::vector<AnfNodePtr> &conv_outputs, const SplitInfo &split_info,
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const std::string &node_name) {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(conv_cnode);
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int32_t nodes_num = conv_outputs.size();
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if (nodes_num != split_info.out_num) {
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MS_LOG(ERROR) << "Conv outputs has wrong input size";
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return nullptr;
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}
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// the inputs of concate are from the outputs of conv
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std::vector<AnfNodePtr> concate_inputs = {NewValueNode(std::make_shared<Primitive>(prim::kPrimConcat->name()))};
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for (int32_t i = 0; i < nodes_num; i++) {
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concate_inputs.push_back(conv_outputs[i]);
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}
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auto concate_cnode = func_graph->NewCNode(concate_inputs);
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MS_EXCEPTION_IF_NULL(concate_cnode);
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concate_cnode->set_fullname_with_scope(node_name + "_Concat");
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concate_cnode->set_scope(conv_cnode->scope());
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return concate_cnode;
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}
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int32_t GetCOutAxis(int32_t format) {
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switch (format) {
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case schema::Format_KHWC:
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return 0;
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case schema::Format_CHWK:
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return 3;
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case schema::Format_NCHW:
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return 0;
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default:
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MS_LOG(ERROR) << "Do not support format: " << format << " now.";
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return -1;
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}
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}
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int32_t GetCInAxis(int32_t format) {
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switch (format) {
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case schema::Format_KHWC:
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return 3;
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case schema::Format_CHWK:
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return 0;
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default:
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MS_LOG(ERROR) << "Do not support format: " << format << " now.";
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return -1;
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}
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}
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int32_t GetAxis(int32_t axis, int32_t format, const SplitInfo &split_info) {
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switch (split_info.primitive_type) {
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case mindspore::schema::PrimitiveType_Conv2DFusion:
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if (axis == CuttingStragedy::CUT_C_OUT) {
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return GetCOutAxis(format);
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} else if (axis == CuttingStragedy::CUT_C_IN) {
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return GetCInAxis(format);
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} else {
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MS_LOG(ERROR) << "Only channel_in and channel_out need to transform.";
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}
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break;
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default:
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MS_LOG(ERROR) << "Now, do not support the type : " << split_info.primitive_type;
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}
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return -1;
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}
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AnfNodePtr CreateOutputsOfAddN(const FuncGraphPtr &func_graph, const CNodePtr &conv_cnode,
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const std::vector<AnfNodePtr> &conv_outputs, const SplitInfo &split_info,
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const std::string &node_name) {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(conv_cnode);
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int32_t nodes_num = conv_outputs.size();
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if (nodes_num != split_info.out_num) {
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MS_LOG(ERROR) << "Conv outputs has wrong input size";
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return nullptr;
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}
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// the inputs of addn are from the outputs of conv
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std::vector<AnfNodePtr> addn_inputs = {NewValueNode(std::make_shared<Primitive>(prim::kPrimAddN->name()))};
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for (int32_t i = 0; i < nodes_num; i++) {
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addn_inputs.push_back(conv_outputs[i]);
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}
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auto addn_cnode = func_graph->NewCNode(addn_inputs);
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MS_EXCEPTION_IF_NULL(addn_cnode);
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addn_cnode->set_fullname_with_scope(node_name + "_AddN");
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addn_cnode->set_scope(conv_cnode->scope());
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return addn_cnode;
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,68 @@
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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_FISSON_FISSON_UTIL_H_
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#define MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_FISSON_UTIL_H_
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#include <vector>
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#include <string>
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#include <unordered_map>
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#include "schema/inner/model_generated.h"
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#include "mindspore/ccsrc/utils/utils.h"
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#include "tools/optimizer/common/gllo_utils.h"
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#include "tools/converter/converter_flags.h"
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#include "mindspore/lite/include/context.h"
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#include "mindspore/lite/include/lite_types.h"
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namespace mindspore {
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using mindspore::schema::PrimitiveType;
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namespace opt {
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extern std::unordered_map<std::string, std::vector<AnfNodePtr>> g_graph_nodes_output;
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extern std::unordered_map<std::string, std::vector<std::vector<ShapeVector>>> g_graph_nodes_out_shapes;
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struct SplitInfo {
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int32_t axis;
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int32_t out_num;
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std::vector<int32_t> size_splits;
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std::vector<int32_t> extend_top;
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std::vector<int32_t> extend_bottom;
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std::vector<mindspore::lite::DeviceType> dev_types;
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int32_t in_num_conv;
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int32_t fmk_type;
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std::vector<int32_t> weight_channel;
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PrimitiveType primitive_type;
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};
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typedef enum { CUT_N, CUT_H, CUT_W, CUT_C_IN, CUT_C_OUT, CUT_NONE } CuttingStragedy;
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void GetMultipleOutputsOfAnfNode(const FuncGraphPtr &func_graph, const AnfNodePtr &node, size_t output_num,
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std::vector<AnfNodePtr> *outputs);
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AnfNodePtr CreateOutputsOfConcat(const FuncGraphPtr &func_graph, const CNodePtr &conv_cnode,
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const std::vector<AnfNodePtr> &conv_outputs, const SplitInfo &split_info,
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const std::string &node_name);
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void CreateOutputsOfSplitWithOverlap(const FuncGraphPtr &func_graph, const CNodePtr &conv_cnode,
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std::vector<AnfNodePtr> *split_outputs, const SplitInfo &split_info,
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const std::string &node_name);
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void GetCNodeShapeInfo(const FuncGraphPtr &func_graph, int32_t fmk_type);
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AnfNodePtr CreateOutputsOfAddN(const FuncGraphPtr &func_graph, const CNodePtr &conv_cnode,
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const std::vector<AnfNodePtr> &conv_outputs, const SplitInfo &split_info,
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const std::string &node_name);
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_FISSON_UTIL_H_
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@ -0,0 +1,53 @@
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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/fisson/iter_node_outputs.h"
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#include <vector>
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#include "tools/optimizer/fisson/fisson_util.h"
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namespace mindspore {
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namespace opt {
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AnfNodePtr IterNodeOutputs::Run(const FuncGraphPtr &func_graph, const AnfNodePtr &node) {
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if (CheckIfFuncGraphIsNull(func_graph) != lite::RET_OK || CheckIfAnfNodeIsNull(node) != lite::RET_OK) {
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return nullptr;
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}
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if (!utils::isa<CNodePtr>(node)) {
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return nullptr;
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}
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auto cnode = node->cast<CNodePtr>();
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auto inputs = cnode->inputs();
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for (auto input_node : inputs) {
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if (!utils::isa<CNodePtr>(input_node)) {
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continue;
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}
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auto input_cnode = input_node->cast<CNodePtr>();
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auto name = input_cnode->fullname_with_scope();
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if (g_graph_nodes_output.find(name) != g_graph_nodes_output.end()) {
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std::vector<AnfNodePtr>::iterator it;
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it = find(g_graph_nodes_output[name].begin(), g_graph_nodes_output[name].end(), node);
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if (it != g_graph_nodes_output[name].end()) {
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continue;
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}
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}
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g_graph_nodes_output[name].push_back(node);
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}
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return nullptr;
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,35 @@
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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 "ir/anf.h"
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#include "mindspore/ccsrc/backend/optimizer/common/node_pass.h"
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#ifndef MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_ITER_NODE_OUTPUTS_H_
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#define MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_ITER_NODE_OUTPUTS_H_
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namespace mindspore {
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namespace opt {
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class IterNodeOutputs : public opt::NodePass {
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public:
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IterNodeOutputs() : NodePass("iter_node_outputs") {}
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~IterNodeOutputs() override = default;
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AnfNodePtr Run(const FuncGraphPtr &func_graph, const AnfNodePtr &node) override;
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};
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_ITER_NODE_OUTPUTS_H_
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@ -0,0 +1,81 @@
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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/fisson/node_out_shapes.h"
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#include <vector>
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#include <string>
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#include "tools/optimizer/fisson/fisson_util.h"
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namespace mindspore {
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namespace opt {
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AnfNodePtr NodeOutShapes::Run(const FuncGraphPtr &func_graph, const AnfNodePtr &node) {
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if (CheckIfFuncGraphIsNull(func_graph) != lite::RET_OK || CheckIfAnfNodeIsNull(node) != lite::RET_OK) {
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return nullptr;
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}
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std::vector<ShapeVector> input_shapes;
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std::vector<ShapeVector> output_shapes;
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if (!utils::isa<CNodePtr>(node)) {
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return nullptr;
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}
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auto cnode = node->cast<CNodePtr>();
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// input
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for (auto input_node : cnode->inputs()) {
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if (utils::isa<CNodePtr>(input_node) || utils::isa<ParameterPtr>(input_node)) {
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auto in_shape = input_node->Shape();
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if (in_shape == nullptr) {
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MS_LOG(ERROR) << "The shape is null.";
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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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if (utils::isa<abstract::ShapePtr>(in_shape)) {
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const auto &shape = in_shape->cast<abstract::ShapePtr>()->shape();
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input_shapes.push_back(shape);
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} else {
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MS_LOG(ERROR) << "currently not support tuple";
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}
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}
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}
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// output
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auto out_shape = cnode->Shape();
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if (out_shape == nullptr) {
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MS_LOG(ERROR) << "The shape is null.";
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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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if (utils::isa<abstract::TupleShapePtr>(out_shape)) {
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auto shape = out_shape->cast<abstract::TupleShapePtr>();
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for (size_t i = 0; i < shape->size(); ++i) {
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const auto &shape_ptr = (*shape)[i];
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if (!utils::isa<abstract::ShapePtr>(shape_ptr)) {
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MS_LOG(ERROR) << "shape_ptr is not ShapePtr.";
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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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output_shapes.push_back(shape_ptr->cast<abstract::ShapePtr>()->shape());
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}
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} else if (utils::isa<abstract::ShapePtr>(out_shape)) {
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const auto &shape = out_shape->cast<abstract::ShapePtr>()->shape();
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output_shapes.push_back(shape);
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}
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std::string name = cnode->fullname_with_scope();
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g_graph_nodes_out_shapes[name].push_back(input_shapes);
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g_graph_nodes_out_shapes[name].push_back(output_shapes);
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return nullptr;
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}
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,35 @@
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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 "ir/anf.h"
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#include "mindspore/ccsrc/backend/optimizer/common/node_pass.h"
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#ifndef MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_NODE_OUT_SHAPES_H_
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#define MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_NODE_OUT_SHAPES_H_
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namespace mindspore {
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namespace opt {
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class NodeOutShapes : public opt::NodePass {
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public:
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NodeOutShapes() : NodePass("node_out_shapes") {}
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~NodeOutShapes() override = default;
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AnfNodePtr Run(const FuncGraphPtr &func_graph, const AnfNodePtr &node);
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};
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_LITE_TOOLS_OPTIMIZER_FISSON_NODE_OUT_SHAPES_H_
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