use unpack graph primitive instead add testcases for all grad interface remove debug log format code remove dumpfuncgraph resolve clang-format resolve reviews resolve cpplint fix reviewpull/62/head
huangdongrun
5 years ago
parent
4b702c4c66
commit
d3f733fa25
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/**
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* Copyright 2020 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 "operator/composite/unpack_call.h"
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#include <algorithm>
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#include <utility>
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#include "./common.h"
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#include "pipeline/static_analysis/abstract_value.h"
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#include "pipeline/static_analysis/dshape.h"
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#include "pipeline/static_analysis/param_validator.h"
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#include "operator/cc_implementations.h"
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#include "ir/anf.h"
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#include "optimizer/opt.h"
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#include "utils/symbolic.h"
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#include "pybind_api/api_register.h"
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namespace mindspore {
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// namespace to support composite operators definition
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namespace prim {
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using mindspore::abstract::AbstractAttribute;
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using mindspore::abstract::AbstractBase;
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using mindspore::abstract::AbstractDictionary;
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using mindspore::abstract::AbstractDictionaryPtr;
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using mindspore::abstract::AbstractFunction;
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using mindspore::abstract::AbstractKeywordArg;
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using mindspore::abstract::AbstractTuple;
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using mindspore::abstract::AbstractTuplePtr;
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FuncGraphPtr UnpackCall::GenerateFuncGraph(const AbstractBasePtrList& args_spec_list) {
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// slice a tensor
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// args: tensor, slice or slice tuple
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const std::string op_name = std::string("UnpackCall");
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size_t arg_length = args_spec_list.size();
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if (arg_length < 2) {
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MS_LOG(EXCEPTION) << op_name << " requires at least two args, but got " << arg_length << ".";
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}
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(void)abstract::CheckArg<AbstractFunction>(op_name, args_spec_list, 0);
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auto ret_graph = std::make_shared<FuncGraph>();
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ret_graph->set_flags(FUNC_GRAPH_FLAG_CORE, true);
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AnfNodePtr fnNode = ret_graph->add_parameter();
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std::vector<AnfNodePtr> elems;
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elems.push_back(fnNode);
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for (size_t index = 1; index < arg_length; index++) {
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MS_EXCEPTION_IF_NULL(args_spec_list[index]);
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if (args_spec_list[index]->isa<AbstractTuple>()) {
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auto arg_tuple = args_spec_list[index]->cast<AbstractTuplePtr>();
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AnfNodePtr para_tuple = ret_graph->add_parameter();
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for (size_t i = 0; i < arg_tuple->size(); ++i) {
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elems.push_back(
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ret_graph->NewCNode({NewValueNode(prim::kPrimTupleGetItem), para_tuple, NewValueNode(SizeToInt(i))}));
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}
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} else if (args_spec_list[index]->isa<AbstractDictionary>()) {
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AbstractDictionaryPtr arg_dict = args_spec_list[index]->cast<AbstractDictionaryPtr>();
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AnfNodePtr para_dict = ret_graph->add_parameter();
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auto dict_elems = arg_dict->elements();
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(void)std::transform(dict_elems.begin(), dict_elems.end(), std::back_inserter(elems),
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[ret_graph, para_dict](const AbstractAttribute& item) {
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auto dict_get_item = ret_graph->NewCNode(
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{NewValueNode(prim::kPrimDictGetItem), para_dict, NewValueNode(item.first)});
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return ret_graph->NewCNode(
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{NewValueNode(prim::kPrimMakeKeywordArg), NewValueNode(item.first), dict_get_item});
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});
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} else {
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MS_LOG(EXCEPTION) << op_name << " require args should be tuple or dict, but got "
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<< args_spec_list[index]->ToString();
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}
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}
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ret_graph->set_output(ret_graph->NewCNode(elems));
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return ret_graph;
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}
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REGISTER_PYBIND_DEFINE(UnpackCall_, ([](const py::module* m) {
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(void)py::class_<UnpackCall, MetaFuncGraph, std::shared_ptr<UnpackCall>>(*m, "UnpackCall_")
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.def(py::init<std::string&>());
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}));
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} // namespace prim
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} // namespace mindspore
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@ -0,0 +1,54 @@
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/**
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* Copyright 2020 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_OPERATOR_COMPOSITE_UNPACK_CALL_H_
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#define MINDSPORE_CCSRC_OPERATOR_COMPOSITE_UNPACK_CALL_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 <utility>
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#include <map>
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#include <set>
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#include <memory>
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#include "pipeline/static_analysis/static_analysis.h"
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#include "utils/misc.h"
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#include "utils/any.h"
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#include "ir/dtype.h"
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#include "ir/meta_func_graph.h"
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#include "common/utils.h"
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namespace mindspore {
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// namespace to support composite operators definition
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namespace prim {
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// Expand the tuple and dict parameters generated when parsing the function call,
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// and generate positional parameters and key-value pairs for function.
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class UnpackCall : public MetaFuncGraph {
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public:
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explicit UnpackCall(const std::string& name) : MetaFuncGraph(name) {}
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~UnpackCall() override = default;
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MS_DECLARE_PARENT(UnpackCall, MetaFuncGraph)
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FuncGraphPtr GenerateFuncGraph(const AbstractBasePtrList& args_spec_list) override;
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friend bool operator==(const UnpackCall& lhs, const UnpackCall& rhs) { return lhs.name_ == rhs.name_; }
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};
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using UnpackCallPtr = std::shared_ptr<UnpackCall>;
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} // namespace prim
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_OPERATOR_COMPOSITE_UNPACK_CALL_H_
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@ -0,0 +1,144 @@
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/**
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* Copyright 2020 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 "optimizer/irpass/grad_var_prepare.h"
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#include <vector>
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#include <algorithm>
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#include <unordered_map>
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#include <memory>
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#include "operator/composite/composite.h"
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#include "operator/ops.h"
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#include "optimizer/irpass.h"
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#include "optimizer/optimizer.h"
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#include "ir/visitor.h"
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#include "ir/func_graph.h"
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#include "ir/func_graph_cloner.h"
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namespace mindspore {
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namespace opt {
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namespace irpass {
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static AnfNodePtr GenerateUnpackGraphNode(std::vector<AnfNodePtr> inputs_y, FuncGraphPtr func_graph,
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AnfNodePtr func_node, bool is_unpack, bool sens_param) {
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MS_EXCEPTION_IF_NULL(func_graph);
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MS_EXCEPTION_IF_NULL(func_node);
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std::vector<AnfNodePtr> nodes;
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AnfNodePtr unpack_graph_node = nullptr;
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if (is_unpack) {
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auto unpack_graph = std::make_shared<prim::UnpackGraphPrimitive>("unpack_graph", sens_param, true);
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nodes.push_back(NewValueNode(unpack_graph));
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nodes.push_back(func_node);
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// {unpackcall, {GradOperation, ...}, args...}
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std::transform(inputs_y.begin() + 2, inputs_y.end(), std::back_inserter(nodes),
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[](const AnfNodePtr& node) { return node; });
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unpack_graph_node = func_graph->NewCNode(nodes);
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} else {
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auto unpack_graph = std::make_shared<prim::UnpackGraphPrimitive>("unpack_graph", sens_param, false);
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nodes.push_back(NewValueNode(unpack_graph));
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nodes.push_back(func_node);
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// {{GradOperation, ...}, args...}
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std::transform(inputs_y.begin() + 1, inputs_y.end(), std::back_inserter(nodes),
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[](const AnfNodePtr& node) { return node; });
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unpack_graph_node = func_graph->NewCNode(nodes);
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}
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return unpack_graph_node;
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}
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// get metagraph of value node
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MetaFuncGraphPtr GetMetaFuncGraphOfValueNode(const AnfNodePtr& node) {
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ValuePtr value;
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if (IsValueNode<prim::DoSignaturePrimitive>(node)) {
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value = GetValueNode(node)->cast<prim::DoSignaturePrimitivePtr>()->function();
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} else {
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value = GetValueNode(node);
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}
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if (value == nullptr) {
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return nullptr;
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}
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return value->cast<MetaFuncGraphPtr>();
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}
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// check if node is a specific metafuncgraph op
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bool IsMetaFuncGraph(const AnfNodePtr& node, const MetaFuncGraphPtr meta_func_graph) {
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if (node != nullptr) {
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auto meta_func_graph_ptr = GetMetaFuncGraphOfValueNode(node);
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if (meta_func_graph_ptr == nullptr) {
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return false;
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}
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if (meta_func_graph_ptr->type_name() == meta_func_graph->type_name()) {
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return true;
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}
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}
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return false;
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}
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// {{GradOperation, g, w}, Ys}
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// {UnPackCall, {GradOperation, g, w}, Ys}
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AnfNodePtr GradVarPrepare::operator()(const OptimizerPtr&, const AnfNodePtr& node) {
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if (!node->isa<CNode>() || node->func_graph() == nullptr) {
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return nullptr;
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}
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// {{...}, Ys}
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auto inputs_y = node->cast<CNodePtr>()->inputs();
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std::vector<AnfNodePtr> inputs_x;
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if (IsCNode(inputs_y[0])) {
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inputs_x = inputs_y[0]->cast<CNodePtr>()->inputs();
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} else if (IsMetaFuncGraph(inputs_y[0], unpack_op_) && IsCNode(inputs_y[1])) {
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inputs_x = inputs_y[1]->cast<CNodePtr>()->inputs();
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} else {
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return nullptr;
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}
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// {{...}, Xs}
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if (inputs_x.size() < 2) {
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return nullptr;
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}
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// {GradOperation, g, w} or {GradOperation, g}
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if (!IsMetaFuncGraph(inputs_x[0], grad_op_)) {
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return nullptr;
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}
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auto meta_func = GetMetaFuncGraphOfValueNode(inputs_x[0]);
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if (meta_func == nullptr) {
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return nullptr;
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}
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auto grad_op_ptr = meta_func->cast<prim::GradOperationPtr>();
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auto func_node = inputs_x[1];
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if (!IsValueNode<FuncGraph>(func_node)) {
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return nullptr;
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}
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AnfNodePtr unpack_graph_node =
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GenerateUnpackGraphNode(inputs_y, node->cast<CNodePtr>()->func_graph(), func_node,
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IsMetaFuncGraph(inputs_y[0], unpack_op_), grad_op_ptr->sens_param());
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// constuct new grad_opration
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inputs_x[1] = unpack_graph_node;
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auto grad_op_cnode = node->func_graph()->NewCNode(inputs_x);
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if (IsMetaFuncGraph(inputs_y[0], unpack_op_)) {
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inputs_y[1] = grad_op_cnode;
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} else {
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inputs_y[0] = grad_op_cnode;
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}
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auto cnode = node->func_graph()->NewCNode(inputs_y);
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return cnode;
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}
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} // namespace irpass
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} // namespace opt
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} // namespace mindspore
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@ -0,0 +1,55 @@
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/**
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* Copyright 2020 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_OPTIMIZER_IRPASS_GRAD_VAR_PREPARE_H_
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#define MINDSPORE_CCSRC_OPTIMIZER_IRPASS_GRAD_VAR_PREPARE_H_
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#include <vector>
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#include <algorithm>
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#include <unordered_map>
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#include <memory>
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#include "operator/composite/composite.h"
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#include "operator/ops.h"
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#include "optimizer/irpass.h"
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#include "optimizer/optimizer.h"
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#include "ir/visitor.h"
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#include "ir/func_graph.h"
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#include "ir/func_graph_cloner.h"
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namespace mindspore {
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namespace opt {
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namespace irpass {
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// {{GradOperation, g, w}, Ys}
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// {UnPackCall, {GradOperation, g, w}, Ys}
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class GradVarPrepare : public AnfVisitor {
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public:
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GradVarPrepare()
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: grad_op_(std::make_shared<prim::GradOperation>("grad")),
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unpack_op_(std::make_shared<prim::UnpackCall>("unpack_call")) {}
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~GradVarPrepare() override = default;
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AnfNodePtr operator()(const OptimizerPtr &, const AnfNodePtr &node) override;
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private:
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MetaFuncGraphPtr grad_op_;
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MetaFuncGraphPtr unpack_op_;
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};
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} // namespace irpass
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} // namespace opt
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_OPTIMIZER_IRPASS_GRAD_VAR_PREPARE_H_
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