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1330 lines
54 KiB
1330 lines
54 KiB
/**
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* This is the C++ adaptation and derivative work of Myia (https://github.com/mila-iqia/myia/).
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*
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* Copyright 2019-2020 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 "pipeline/static_analysis/prim.h"
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#include <algorithm>
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#include <limits>
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#include <mutex>
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#include <set>
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#include <string>
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#include <utility>
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#include "operator/cc_implementations.h"
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#include "operator/ops.h"
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#include "operator/composite/do_signature.h"
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#include "operator/prim_to_function.h"
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#include "pipeline/static_analysis/utils.h"
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#include "utils/symbolic.h"
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#include "./common.h"
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#include "pipeline/resource.h"
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#include "pipeline/parse/resolve.h"
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#include "ir/tensor.h"
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#include "utils/convert_utils.h"
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#include "pipeline/parse/data_converter.h"
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#include "pipeline/static_analysis/param_validator.h"
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#include "common/utils.h"
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namespace mindspore {
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namespace abstract {
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PrimitiveEvalImplMap &GetPrimitiveToEvalImplMap() {
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static PrimitiveEvalImplMap prim_eval_implement_map = {
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// Statements
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{prim::kPrimReturn, {InferImplReturn, true}},
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{prim::kPrimTypeOf, {InferImplTypeof, false}},
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{prim::kPrimHasType, {InferImplHasType, false}},
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{prim::kPrimDot, {InferImplDot, true}},
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{prim::kPrimSwitch, {InferImplSwitch, true}},
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{prim::kPrimSwitchLayer, {InferImplSwitchLayer, true}},
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{prim::kPrimIs_, {InferImplIs_, true}},
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{prim::kPrimIsNot, {InferImplIsNot, true}},
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{prim::kPrimInDict, {InferImplInDict, true}},
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{prim::kPrimNotInDict, {InferImplNotInDict, true}},
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{prim::kPrimIsConsant, {InferImplIsConstant, true}},
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// Maths
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{prim::kPrimMaximumGrad, {InferImplMinOrMaxGrad, true}},
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{prim::kPrimMinimumGrad, {InferImplMinOrMaxGrad, true}},
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// Array
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{prim::kPrimScalarToArray, {InferImplScalarToArray, true}},
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{prim::kPrimArrayToScalar, {InferImplArrayToScalar, true}},
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{prim::kPrimBroadcastShape, {InferImplBroadCastShape, true}},
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{prim::kPrimShape, {InferImplShape, true}},
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{prim::kPrimPack, {InferImplPack, true}},
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// Structure
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{prim::kPrimMakeTuple, {InferImplMakeTuple, true}},
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{prim::kPrimMakeList, {InferImplMakeList, true}},
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{prim::kPrimMakeDict, {InferImplMakeDict, true}},
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{prim::kPrimMakeSlice, {InferImplMakeSlice, true}},
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{prim::kPrimMakeKeywordArg, {InferImplMakeKwarg, true}},
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{prim::kPrimExtractKeywordArg, {InferImplExtractKwarg, true}},
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{prim::kPrimMakeRecord, {InferImplMakeRecord, false}},
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{prim::kPrimTupleGetItem, {InferImplTupleGetItem, true}},
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{prim::kPrimListGetItem, {InferImplListGetItem, true}},
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{prim::kPrimTupleSetItem, {InferImplTupleSetItem, true}},
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{prim::kPrimListSetItem, {InferImplListSetItem, true}},
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{prim::kPrimDictGetItem, {InferImplDictGetItem, true}},
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{prim::kPrimDictSetItem, {InferImplDictSetItem, true}},
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{prim::kPrimListAppend, {InferImplListAppend, true}},
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{prim::kPrimTupleLen, {InferImplTupleLen, true}},
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{prim::kPrimListLen, {InferImplListLen, true}},
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{prim::kPrimArrayLen, {InferImplArrayLen, true}},
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{prim::kPrimListMap, {InferImplListMap, false}},
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{prim::kPrimListReduce, {InferImplListReduce, false}},
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{prim::kPrimTupleReversed, {InferImplTupleReversed, false}},
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{prim::kPrimReducedShape, {InferImplReduceShape, false}},
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{prim::kPrimTupleDiv, {InferImplTupleDiv, false}},
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{prim::kPrimTupleToArray, {InferImplTuple2Array, false}},
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{prim::kPrimShapeMul, {InferImplShapeMul, false}},
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{prim::kPrimTupleEqual, {InferImplTupleEqual, false}},
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{prim::kPrimListEqual, {InferImplListEqual, false}},
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{prim::kPrimMakeRange, {InferImplMakeRange, false}},
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{prim::kPrimStopGradient, {InferImplStopGradient, false}},
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{prim::kPrimStringEqual, {InferImplStringEqual, false}},
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{prim::kPrimStringConcat, {InferImplStringConcat, false}},
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{prim::kPrimDictLen, {InferImplDictLen, false}},
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// NN
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{prim::kPrimPooling, {InferImplPooling, true}},
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{prim::kPrimPoolingGrad, {InferImplPoolingGrad, true}},
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{prim::kPrimFusedBatchNorm, {InferImplFusedBatchNorm, true}},
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{prim::kPrimFusedBatchNormGrad, {InferImplFusedBatchNormGrad, true}},
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{prim::kPrimReluGrad, {InferImplReluGrad, true}},
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{prim::kPrimConv2DBackpropInput, {InferImplConv2DBackpropInput, true}},
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{prim::kPrimConv2DBackpropFilter, {InferImplConv2DBackpropFilter, true}},
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{prim::kPrimBiasAddGrad, {InferImplBiasAddGrad, true}},
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{prim::kPrimRelu, {InferImplRelu, true}},
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{prim::kPrimFakeBprop, {InferImplFakeBprop, false}},
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{prim::kPrimZerosLike, {InferImplZerosLike, true}},
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{prim::kPrimBpropCut, {InferImplBpropCut, true}},
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{prim::kPrimLayerNorm, {InferImplLayerNorm, true}},
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{prim::kPrimLayerNormGrad, {InferImplLayerNormGrad, true}},
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{prim::kPrimDropoutGenMask, {InferImplDropoutGenMask, true}},
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// Others
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{prim::kPrimIdentity, {InferImplIdentity, true}},
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// Set impl to null as it will use PartialEvaluator;
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{prim::kPrimPartial, {nullptr, true}},
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{prim::kPrimJ, {InferImplJ, false}},
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{prim::kPrimEnvGetItem, {InferImplEnvGetItem, true}},
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{prim::kPrimEnvSetItem, {InferImplEnvSetItem, true}},
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{prim::kPrimEnvAdd, {InferImplEnvAdd, true}},
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{prim::kPrimMakeRefKey, {InferImplMakeRefKey, true}},
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{prim::kPrimMakeRef, {InferImplMakeRef, true}},
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{prim::kPrimGetRefKey, {InferImplGetRefKey, true}},
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{prim::kPrimGetRefValue, {InferImplGetRefValue, true}},
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{prim::kPrimGetRefOrigin, {InferImplGetRefOrigin, true}},
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{prim::kPrimStateSetItem, {InferImplStateSetItem, true}},
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{prim::kPrimDepend, {InferImplDepend, true}},
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{prim::kPrimBroadcastGradientArgs, {InferImplBroadcastGradientArgs, false}},
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{prim::kPrimControlDepend, {InferImplControlDepend, true}},
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};
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return prim_eval_implement_map;
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}
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using mindspore::parse::PyObjectWrapper;
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EvalResultPtr StandardPrimEvaluator::EvalPrim(const AnalysisEnginePtr &engine, const AbstractBasePtrList &args) {
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prim_->BeginRecordAddAttr();
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AbstractBasePtr abs_base = eval_impl_(engine, prim_, args);
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prim_->EndRecordAddAttr();
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auto added_attrs = prim_->evaluate_added_attrs();
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auto infer_result = std::make_shared<EvalResult>(abs_base, std::make_shared<AttrValueMap>(added_attrs));
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return infer_result;
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}
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EvalResultPtr DoSignatureEvaluator::Run(AnalysisEnginePtr engine, const ConfigPtrList &args_conf_list,
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AnfNodeConfigPtr out_conf) {
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AbstractBasePtrList args_spec_list;
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if (out_conf->node() == nullptr || !out_conf->node()->isa<CNode>()) {
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MS_LOG(EXCEPTION) << "Node of out_conf should be CNode";
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}
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auto do_signature = dyn_cast<prim::DoSignaturePrimitive>(prim_);
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auto out_node = dyn_cast<CNode>(out_conf->node());
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const auto &out_node_inputs = out_node->inputs();
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if (out_node->inputs().size() == 0 || (out_node_inputs.size() - 1) != args_conf_list.size()) {
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MS_LOG(EXCEPTION) << "Op: " << do_signature->function()->ToString()
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<< " args size should equal to inputs size minus 1, but args size " << args_conf_list.size()
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<< ", inputs size " << out_node_inputs.size();
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}
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AnfNodePtrList args_inputs{out_node_inputs.begin() + 1, out_node_inputs.end()};
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(void)std::transform(args_conf_list.begin(), args_conf_list.end(), std::back_inserter(args_spec_list),
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[](const ConfigPtr &ref) -> AbstractBasePtr { return ref->GetEvaluatedValue()->abstract(); });
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ScopePtr scope = kDefaultScope;
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if (out_conf != nullptr) {
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scope = out_conf->node()->scope();
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}
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ScopeGuard scope_guard(scope);
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AnfNodePtr new_cnode = nullptr;
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if (bound_node() != nullptr) {
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TraceManager::DebugTrace(std::make_shared<TraceDoSignature>(bound_node()->debug_info()));
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new_cnode = prim::GenerateCNode(out_node->func_graph(), prim_->ToString(), do_signature->function(), args_spec_list,
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args_inputs);
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TraceManager::EndTrace();
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} else {
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new_cnode = prim::GenerateCNode(out_node->func_graph(), prim_->ToString(), do_signature->function(), args_spec_list,
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args_inputs);
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}
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AnfNodeConfigPtr fn_conf = engine->MakeConfig(new_cnode, out_conf->context());
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return engine->ForwardConfig(out_conf, fn_conf);
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}
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static AbstractBasePtrList GetUnpackGraphSpecArgsList(AbstractBasePtrList args_spec_list, bool need_unpack) {
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// arg[0] is the func graph to unpack, ignore it
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AbstractBasePtrList specialize_args_before_unpack(args_spec_list.begin() + 1, args_spec_list.end());
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AbstractBasePtrList graph_specialize_args;
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if (need_unpack) {
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for (size_t index = 0; index < specialize_args_before_unpack.size(); index++) {
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MS_EXCEPTION_IF_NULL(specialize_args_before_unpack[index]);
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if (specialize_args_before_unpack[index]->isa<AbstractTuple>()) {
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AbstractTuplePtr arg_tuple = specialize_args_before_unpack[index]->cast<AbstractTuplePtr>();
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std::transform(arg_tuple->elements().begin(), arg_tuple->elements().end(),
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std::back_inserter(graph_specialize_args), [](AbstractBasePtr abs) { return abs; });
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} else if (specialize_args_before_unpack[index]->isa<AbstractDictionary>()) {
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AbstractDictionaryPtr arg_dict = specialize_args_before_unpack[index]->cast<AbstractDictionaryPtr>();
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auto dict_elems = arg_dict->elements();
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(void)std::transform(
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dict_elems.begin(), dict_elems.end(), std::back_inserter(graph_specialize_args),
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[](const AbstractAttribute &item) { return std::make_shared<AbstractKeywordArg>(item.first, item.second); });
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} else {
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MS_LOG(EXCEPTION) << "UnpackGraph require args should be tuple or dict, but got "
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<< specialize_args_before_unpack[index]->ToString();
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}
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}
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} else {
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graph_specialize_args = specialize_args_before_unpack;
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}
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return graph_specialize_args;
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}
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EvalResultPtr UnpackGraphEvaluator::Run(AnalysisEnginePtr engine, const ConfigPtrList &args_conf_list,
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AnfNodeConfigPtr out_conf) {
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if (out_conf->node() == nullptr || !out_conf->node()->isa<CNode>()) {
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MS_LOG(EXCEPTION) << "Node of out_conf should be CNode";
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}
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auto unpack_graph = prim_->cast<prim::UnpackGraphPrimitivePtr>();
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auto out_node = out_conf->node()->cast<CNodePtr>();
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const auto &out_node_inputs = out_node->inputs();
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if (out_node->inputs().size() == 0 || (out_node_inputs.size() - 1) != args_conf_list.size()) {
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MS_LOG(EXCEPTION) << "UnpackGraphPrimitive"
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<< " args size should equal to inputs size minus 1, but args size " << args_conf_list.size()
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<< ", inputs size " << out_node_inputs.size();
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}
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AnfNodePtrList args_inputs{out_node_inputs.begin() + 1, out_node_inputs.end()};
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AbstractBasePtrList args_spec_list;
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(void)std::transform(args_conf_list.begin(), args_conf_list.end(), std::back_inserter(args_spec_list),
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[](const ConfigPtr &ref) -> AbstractBasePtr { return ref->GetEvaluatedValue()->abstract(); });
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// get the forward graph
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MS_EXCEPTION_IF_NULL(args_spec_list[0]);
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AbstractFunctionPtr fn = args_spec_list[0]->cast<AbstractFunctionPtr>();
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if (fn == nullptr) {
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MS_LOG(EXCEPTION) << "UnpackGraphPrimitive arg0 must be AbstractFunction, but " << args_spec_list[0]->ToString();
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}
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auto real_fn = fn->cast<FuncGraphAbstractClosurePtr>();
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MS_EXCEPTION_IF_NULL(real_fn);
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FuncGraphPtr forward_graph = real_fn->func_graph();
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MS_EXCEPTION_IF_NULL(forward_graph);
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AbstractBasePtrList graph_specialize_args =
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GetUnpackGraphSpecArgsList(args_spec_list, unpack_graph->need_unpack_args());
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AbstractBasePtrList graph_specialize_args_without_sens;
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(void)std::transform(graph_specialize_args.begin(),
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graph_specialize_args.end() - (unpack_graph->with_sens_in_args() ? 1 : 0),
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std::back_inserter(graph_specialize_args_without_sens), [](AbstractBasePtr abs) { return abs; });
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auto new_graph = forward_graph->GenerateGraph(graph_specialize_args_without_sens);
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engine->func_graph_manager()->AddFuncGraph(new_graph);
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ScopePtr scope = kDefaultScope;
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if (out_conf != nullptr) {
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scope = out_conf->node()->scope();
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}
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ScopeGuard scope_guard(scope);
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AnfNodePtr new_vnode = NewValueNode(new_graph);
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AnfNodeConfigPtr fn_conf = engine->MakeConfig(new_vnode, out_conf->context());
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return engine->ForwardConfig(out_conf, fn_conf);
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}
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AnfNodePtr MixedPrecisionCastHelper(AnfNodePtr source_node, AbstractBasePtr node_type, AnfNodePtr target_type,
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FuncGraphPtr func_graph) {
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AnfNodePtr target_node = source_node;
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if (node_type->isa<AbstractTensor>()) {
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auto x = node_type->cast<AbstractTensorPtr>();
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if (x->element()->BuildType()->isa<Float>()) {
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auto cast = prim::GetPythonOps("cast", "mindspore.ops.functional");
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MS_EXCEPTION_IF_NULL(cast);
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target_node = func_graph->NewCNode({NewValueNode(cast), source_node, target_type});
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}
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} else if (node_type->isa<AbstractTuple>()) {
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auto x = node_type->cast<AbstractTuplePtr>();
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auto &items = x->elements();
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std::vector<AnfNodePtr> nodes;
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nodes.emplace_back(NewValueNode(prim::kPrimMakeTuple));
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int idx = 0;
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for (const auto &item : items) {
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AnfNodePtr tuple_node =
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func_graph->NewCNode({NewValueNode(prim::kPrimTupleGetItem), source_node, NewValueNode(idx)});
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AnfNodePtr node = MixedPrecisionCastHelper(tuple_node, item, target_type, func_graph);
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nodes.emplace_back(node);
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++idx;
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}
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target_node = func_graph->NewCNode(nodes);
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}
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return target_node;
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}
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EvalResultPtr MixedPrecisionCastEvaluator::Run(AnalysisEnginePtr engine, const ConfigPtrList &args_conf_list,
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AnfNodeConfigPtr out_conf) {
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AbstractBasePtrList args_spec_list;
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if (out_conf->node() == nullptr || !out_conf->node()->isa<CNode>()) {
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MS_LOG(EXCEPTION) << "Node of out_conf should be CNode";
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}
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auto out_node = out_conf->node()->cast<CNodePtr>();
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const auto &out_node_inputs = out_node->inputs();
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if (out_node->inputs().size() == 0 || (out_node_inputs.size() - 1) != args_conf_list.size()) {
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MS_LOG(EXCEPTION) << "MixedPrecisionCast"
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<< " args size should equal to inputs size minus 1, but args size " << args_conf_list.size()
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<< ", inputs size " << out_node_inputs.size();
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}
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AnfNodePtrList args_inputs{out_node_inputs.begin() + 1, out_node_inputs.end()};
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(void)std::transform(args_conf_list.begin(), args_conf_list.end(), std::back_inserter(args_spec_list),
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[](const ConfigPtr &ref) -> AbstractBasePtr { return ref->GetEvaluatedValue()->abstract(); });
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ScopePtr scope = kDefaultScope;
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if (out_conf != nullptr) {
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scope = out_conf->node()->scope();
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}
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ScopeGuard scope_guard(scope);
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FuncGraphPtr func_graph = out_conf->node()->func_graph();
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AnfNodePtr new_node = MixedPrecisionCastHelper(out_node_inputs[2], args_spec_list[1], out_node_inputs[1], func_graph);
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AnfNodeConfigPtr fn_conf = engine->MakeConfig(new_node, out_conf->context());
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return engine->ForwardConfig(out_conf, fn_conf);
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}
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namespace {
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py::object BuildValue(const ValuePtr &value_ptr) {
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if (value_ptr == nullptr) {
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return py::none();
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} else {
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return ValuePtrToPyData(value_ptr);
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}
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}
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} // end anonymous namespace
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py::dict ConvertAbstractToPython(const AbstractBasePtr &abs_base) {
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MS_EXCEPTION_IF_NULL(abs_base);
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py::dict dic;
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if (abs_base->isa<AbstractTensor>()) {
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auto arg_tensor = dyn_cast<AbstractTensor>(abs_base);
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dic["shape"] = arg_tensor->shape()->shape();
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dic["dtype"] = arg_tensor->BuildType();
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dic["value"] = BuildValue(arg_tensor->BuildValue());
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} else if (abs_base->isa<AbstractScalar>() || abs_base->isa<AbstractType>() || abs_base->isa<AbstractRefKey>()) {
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std::vector<int> shape;
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dic["shape"] = shape;
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dic["dtype"] = abs_base->BuildType();
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dic["value"] = BuildValue(abs_base->BuildValue());
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} else if (abs_base->isa<AbstractSlice>()) {
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auto arg_slice = dyn_cast<AbstractSlice>(abs_base);
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std::vector<int> shape;
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dic["shape"] = shape;
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dic["dtype"] = arg_slice->BuildType();
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dic["value"] = BuildValue(arg_slice->BuildValue());
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} else if (abs_base->isa<AbstractRef>()) {
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auto value = abs_base->cast<AbstractRefPtr>()->ref();
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dic = ConvertAbstractToPython(value);
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} else if (abs_base->isa<AbstractEllipsis>()) {
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auto arg_slice = dyn_cast<AbstractEllipsis>(abs_base);
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std::vector<int> shape;
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dic["shape"] = shape;
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dic["dtype"] = arg_slice->BuildType();
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dic["value"] = BuildValue(arg_slice->BuildValue());
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} else if (abs_base->isa<AbstractTuple>()) {
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auto arg_tuple = dyn_cast<AbstractTuple>(abs_base);
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size_t len = arg_tuple->size();
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py::tuple shape_tuple(len);
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py::tuple dtype_tuple(len);
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for (size_t i = 0; i < len; i++) {
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py::dict out = ConvertAbstractToPython(arg_tuple->elements()[i]);
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shape_tuple[i] = out["shape"];
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dtype_tuple[i] = out["dtype"];
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}
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dic["shape"] = shape_tuple;
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dic["dtype"] = dtype_tuple;
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dic["value"] = BuildValue(arg_tuple->BuildValue());
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} else if (abs_base->isa<AbstractList>()) {
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auto arg_list = dyn_cast<AbstractList>(abs_base);
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size_t len = arg_list->size();
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py::list shape_list(len);
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py::list dtype_list(len);
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|
|
for (size_t i = 0; i < len; i++) {
|
|
py::dict out = ConvertAbstractToPython(arg_list->elements()[i]);
|
|
shape_list[i] = out["shape"];
|
|
dtype_list[i] = out["dtype"];
|
|
}
|
|
dic["shape"] = shape_list;
|
|
dic["dtype"] = dtype_list;
|
|
dic["value"] = BuildValue(arg_list->BuildValue());
|
|
} else if (abs_base->isa<AbstractNone>()) {
|
|
dic["shape"] = py::none();
|
|
dic["dtype"] = py::none();
|
|
dic["value"] = py::none();
|
|
} else if (abs_base->isa<AbstractFunction>()) {
|
|
dic["shape"] = py::none();
|
|
dic["dtype"] = abs_base->BuildType();
|
|
dic["value"] = py::none();
|
|
} else {
|
|
auto value = abs_base->BuildValue();
|
|
if ((*value == *kAnyValue)) {
|
|
auto value_desc = abs_base->value_desc();
|
|
MS_EXCEPTION(TypeError) << "Unsupported parameter " << (value_desc.empty() ? "type" : value_desc)
|
|
<< " for python primitive." << abs_base->ToString();
|
|
}
|
|
MS_EXCEPTION(TypeError) << "Unsupported parameter type for python primitive, the parameter value is "
|
|
<< value->ToString();
|
|
}
|
|
return dic;
|
|
}
|
|
|
|
namespace {
|
|
py::tuple PreparePyInputs(const PrimitivePyPtr &prim_py, const AbstractBasePtrList &args) {
|
|
const AbstractBasePtrList *args_ptr;
|
|
|
|
if (prim_py->is_tuple_input_) {
|
|
if (args.empty()) {
|
|
MS_LOG(EXCEPTION) << "Primitive args is empty";
|
|
}
|
|
if (args[0] == nullptr || !args[0]->isa<AbstractTuple>()) {
|
|
MS_LOG(EXCEPTION) << "Custom Primitive inputs should be packed into a Tuple after converting"
|
|
"prim convert pass for GE.";
|
|
}
|
|
args_ptr = &(args[0]->cast<AbstractTuplePtr>()->elements());
|
|
} else {
|
|
args_ptr = &args;
|
|
}
|
|
|
|
py::tuple py_args(args_ptr->size());
|
|
for (size_t i = 0; i < args_ptr->size(); i++) {
|
|
auto arg_i = (*args_ptr)[i];
|
|
py_args[i] = ConvertAbstractToPython(arg_i);
|
|
}
|
|
return py_args;
|
|
}
|
|
|
|
AbstractBasePtr PyInferRes2Abstract(const PrimitivePyPtr &prim_py, const py::dict &output) {
|
|
// Convert to AbstractValue based on type and shape
|
|
if (output["value"].is_none()) {
|
|
auto out_shape = output["shape"];
|
|
auto out_dtype = output["dtype"];
|
|
return PyListDtype2AbstractTensor(out_shape, out_dtype);
|
|
}
|
|
// Convert pyobject to Value, then to AbstractValue
|
|
ValuePtr converted_ret = nullptr;
|
|
bool converted = parse::ConvertData(output["value"], &converted_ret);
|
|
if (!converted) {
|
|
MS_LOG(EXCEPTION) << "Convert data failed";
|
|
}
|
|
auto res_spec = FromValue(converted_ret);
|
|
MS_EXCEPTION_IF_NULL(res_spec);
|
|
if (res_spec->isa<AbstractTensor>()) {
|
|
// Replace to tensor constant node in specialize
|
|
auto res_tensor = res_spec->cast<AbstractTensorPtr>();
|
|
res_tensor->set_value(converted_ret);
|
|
}
|
|
if (prim_py->IsCustomPrim()) {
|
|
// Raise error if output_num is not match the infer result.
|
|
int output_num = GetValue<int>(prim_py->GetAttr("output_num"));
|
|
if (res_spec->isa<AbstractTensor>() && output_num != 1) {
|
|
MS_LOG(EXCEPTION) << "Custom primitive " << prim_py->ToString() << " output_num " << output_num
|
|
<< " not matches the infer result.";
|
|
} else if (res_spec->isa<AbstractTuple>() &&
|
|
(res_spec->cast<AbstractTuplePtr>()->size() != IntToSize(output_num))) {
|
|
MS_LOG(EXCEPTION) << "Custom primitive " << prim_py->ToString() << " output_num " << output_num
|
|
<< " not matches the infer result.";
|
|
}
|
|
}
|
|
return res_spec;
|
|
}
|
|
} // end anonymous namespace
|
|
|
|
EvalResultPtr PythonPrimEvaluator::EvalPrim(const AnalysisEnginePtr &, const AbstractBasePtrList &args) {
|
|
MS_LOG(DEBUG) << "Eval for:" << prim_py_->ToString();
|
|
|
|
const auto &iter = cache_->find(args);
|
|
if (iter != cache_->end()) {
|
|
return iter->second;
|
|
}
|
|
auto py_args = PreparePyInputs(prim_py_, args);
|
|
|
|
auto pyobj = prim_py_->GetPyObj();
|
|
if (pyobj == nullptr) {
|
|
MS_LOG(EXCEPTION) << "[" << prim_py_->ToString() << "]: pyobj is empty";
|
|
}
|
|
auto infer_fuc = pyobj.attr("__infer__");
|
|
prim_py_->BeginRecordAddAttr();
|
|
py::dict output = infer_fuc(*py_args);
|
|
prim_py_->EndRecordAddAttr();
|
|
auto added_attrs = prim_py_->evaluate_added_attrs();
|
|
MS_LOG(DEBUG) << "Output type is " << (std::string)py::str(output);
|
|
auto res_spec = PyInferRes2Abstract(prim_py_, output);
|
|
|
|
MS_LOG(DEBUG) << "Python InferTensor result spec: " << res_spec->ToString() << ".";
|
|
auto infer_result = std::make_shared<EvalResult>(res_spec, std::make_shared<AttrValueMap>(added_attrs));
|
|
(*cache_)[args] = infer_result;
|
|
return infer_result;
|
|
}
|
|
|
|
EvalResultPtr UniformPrimEvaluator::EvalPrim(const AnalysisEnginePtr &, const AbstractBasePtrList &args) {
|
|
// if func_desc_.retval type is super class of parameter type, then make the retval type as parameter type.
|
|
if (nargs_ != args.size()) {
|
|
MS_LOG(ERROR) << "UniformPrimEvaluator expect " << nargs_ << " args, but got " << args.size() << " inputs";
|
|
return nullptr;
|
|
}
|
|
TypePtr ret_value_type = return_value_type_;
|
|
ValuePtrList value_list;
|
|
for (const auto &arg : args) {
|
|
// Check if all arguments are scalar type.
|
|
MS_EXCEPTION_IF_NULL(arg);
|
|
if (arg->isa<AbstractScalar>()) {
|
|
auto arg_scalar = dyn_cast<AbstractScalar>(arg);
|
|
auto arg_value = arg_scalar->GetValueTrack();
|
|
value_list.push_back(arg_value);
|
|
} else {
|
|
// Raise TypeError Expected Scalar.
|
|
MS_LOG(EXCEPTION) << "Expect scalar arguments for uniform primitives.";
|
|
}
|
|
}
|
|
for (const auto &item : type_map_) {
|
|
TypePtrList selections;
|
|
MS_EXCEPTION_IF_NULL(item.second);
|
|
(void)std::transform(item.second->begin(), item.second->end(), std::back_inserter(selections),
|
|
[&args](size_t arg_idx) -> TypePtr { return args[arg_idx]->GetTypeTrack(); });
|
|
TypePtr res = CheckTypeList(item.first, selections);
|
|
if (*return_value_type_ == *(item.first)) {
|
|
ret_value_type = res;
|
|
}
|
|
}
|
|
|
|
ValuePtr evaluated_value = RunImpl(value_list);
|
|
if (!(*evaluated_value == *kAnyValue)) {
|
|
ret_value_type = evaluated_value->type();
|
|
}
|
|
// for comparison primitives , return type shall have be specified to be bool.
|
|
if (specify_out_type_ != nullptr) {
|
|
ret_value_type = specify_out_type_;
|
|
}
|
|
|
|
AbstractScalarPtr abs_base = std::make_shared<AbstractScalar>(evaluated_value, ret_value_type);
|
|
return std::make_shared<EvalResult>(abs_base, std::make_shared<AttrValueMap>());
|
|
}
|
|
|
|
ValuePtr UniformPrimEvaluator::RunImpl(const ValuePtrList &args) const {
|
|
if (!eval_value_) {
|
|
return kAnyValue;
|
|
} else {
|
|
if (std::any_of(args.begin(), args.end(), [](const ValuePtr &arg) {
|
|
MS_EXCEPTION_IF_NULL(arg);
|
|
return arg->isa<AnyValue>();
|
|
})) {
|
|
return kAnyValue;
|
|
}
|
|
return impl_(args);
|
|
}
|
|
}
|
|
|
|
// Primitive implementation
|
|
// static function start
|
|
namespace {
|
|
EvaluatorPtr InitStandardPrimEvaluator(PrimitivePtr primitive, const StandardPrimitiveEvalImpl eval_impl) {
|
|
EvaluatorPtr prim_evaluator = std::make_shared<StandardPrimEvaluator>(primitive, eval_impl);
|
|
return prim_evaluator;
|
|
}
|
|
|
|
EvaluatorPtr InitUniformPrimEvaluator(const PrimitivePtr &primitive, PrimitiveImpl prim_impl, bool eval_value,
|
|
const TypePtr &specify_out_type) {
|
|
FunctionPtr func = nullptr;
|
|
(void)prim::PrimToFunction::GetInstance().GetFunction(primitive, &func);
|
|
MS_EXCEPTION_IF_NULL(func);
|
|
|
|
EvaluatorPtr uniform_primitive_evaluator =
|
|
std::make_shared<UniformPrimEvaluator>(func, prim_impl, eval_value, specify_out_type);
|
|
return uniform_primitive_evaluator;
|
|
}
|
|
|
|
const int kResolveCaseUserDefineClass = 1;
|
|
const int kResolveCaseBuildinTypeMethod = 2;
|
|
const int kResolveCaseFunction = 3;
|
|
int GetResolveCase(const TypePtr &data_type) {
|
|
MS_EXCEPTION_IF_NULL(data_type);
|
|
if (data_type->type_id() == kObjectTypeClass) {
|
|
return kResolveCaseUserDefineClass;
|
|
}
|
|
|
|
// try method map, if not in method map, the data_type should be External type.
|
|
if (pipeline::Resource::IsTypeInMethodMap(data_type->type_id())) {
|
|
return kResolveCaseBuildinTypeMethod;
|
|
}
|
|
|
|
return kResolveCaseFunction;
|
|
}
|
|
|
|
FuncGraphPtr PyObjToGraph(const AnalysisEnginePtr &engine, const ValuePtr &method) {
|
|
MS_EXCEPTION_IF_NULL(engine);
|
|
MS_EXCEPTION_IF_NULL(method);
|
|
if (!method->isa<parse::PyObjectWrapper>()) {
|
|
MS_LOG(EXCEPTION) << "Method type error: " << method->ToString();
|
|
}
|
|
|
|
std::shared_ptr<PyObjectWrapper> obj = method->cast<std::shared_ptr<PyObjectWrapper>>();
|
|
FuncGraphPtr func_graph = mindspore::parse::ConvertToFuncGraph(obj->obj());
|
|
if (func_graph == nullptr) {
|
|
MS_LOG(EXCEPTION) << "Parse python object: " << method->ToString() << " failed";
|
|
}
|
|
|
|
FuncGraphManagerPtr manager = engine->func_graph_manager();
|
|
manager->AddFuncGraph(func_graph);
|
|
return func_graph;
|
|
}
|
|
|
|
inline void AddToManager(const AnalysisEnginePtr &engine, const FuncGraphPtr func_graph) {
|
|
MS_EXCEPTION_IF_NULL(engine);
|
|
FuncGraphManagerPtr manager = engine->func_graph_manager();
|
|
manager->AddFuncGraph(func_graph);
|
|
}
|
|
|
|
EvalResultPtr StaticGetterInferred(const ValuePtr &value, const ConfigPtr &data_conf,
|
|
const AnfNodeConfigPtr &old_conf) {
|
|
MS_EXCEPTION_IF_NULL(old_conf);
|
|
|
|
AbstractBasePtr abs_ptr = ToAbstract(value, AnalysisContext::DummyContext(), old_conf);
|
|
AbstractFunctionPtr abs_func = dyn_cast<abstract::AbstractFunction>(abs_ptr);
|
|
MS_EXCEPTION_IF_NULL(abs_func);
|
|
|
|
// Create new cnode
|
|
std::vector<AnfNodePtr> input = {NewValueNode(prim::kPrimPartial)};
|
|
auto func_graph_func = dyn_cast<abstract::FuncGraphAbstractClosure>(abs_func);
|
|
if (func_graph_func != nullptr) {
|
|
FuncGraphPtr fg = func_graph_func->func_graph();
|
|
input.push_back(NewValueNode(fg));
|
|
} else {
|
|
auto prim_func = dyn_cast<abstract::PrimitiveAbstractClosure>(abs_func);
|
|
MS_EXCEPTION_IF_NULL(prim_func);
|
|
PrimitivePtr prim = prim_func->prim();
|
|
input.push_back(NewValueNode(prim));
|
|
}
|
|
|
|
AnfNodeConfigPtr conf = dyn_cast<abstract::AnfNodeConfig>(data_conf);
|
|
MS_EXCEPTION_IF_NULL(conf);
|
|
input.push_back(conf->node());
|
|
MS_EXCEPTION_IF_NULL(old_conf);
|
|
FuncGraphPtr func_graph = old_conf->node()->func_graph();
|
|
CNodePtr new_cnode = func_graph->NewCNode(input);
|
|
AnalysisEnginePtr eng = old_conf->engine();
|
|
AnfNodeConfigPtr fn_conf = eng->MakeConfig(new_cnode, old_conf->context());
|
|
return eng->ForwardConfig(old_conf, fn_conf);
|
|
}
|
|
|
|
EvalResultPtr GetEvaluatedValueForNameSpaceString(const AnalysisEnginePtr &engine,
|
|
const AbstractBasePtrList &args_spec_list,
|
|
const AnfNodeConfigPtr &out_conf) {
|
|
// args_spec_list: same as StaticGetter
|
|
if (args_spec_list.size() < 2) {
|
|
MS_LOG(EXCEPTION) << "Size of args_spec_list is less than 2";
|
|
}
|
|
MS_EXCEPTION_IF_NULL(out_conf);
|
|
// An external type.
|
|
MS_EXCEPTION_IF_NULL(args_spec_list[0]);
|
|
MS_EXCEPTION_IF_NULL(args_spec_list[1]);
|
|
MS_LOG(DEBUG) << "Args[0]: " << args_spec_list[0]->ToString();
|
|
MS_LOG(DEBUG) << "Args[1]: " << args_spec_list[1]->ToString();
|
|
auto data_v = args_spec_list[0]->BuildValue();
|
|
if (!data_v->isa<parse::NameSpace>()) {
|
|
MS_LOG(EXCEPTION) << "Data is not NameSpace : " << data_v->ToString();
|
|
}
|
|
|
|
auto item_v = args_spec_list[1]->BuildValue();
|
|
if (item_v->isa<StringImm>()) {
|
|
item_v = std::make_shared<parse::Symbol>(item_v->cast<StringImmPtr>()->value());
|
|
}
|
|
|
|
if (!item_v->isa<parse::Symbol>()) {
|
|
MS_LOG(EXCEPTION) << "The value of the attribute could not be inferred: " << item_v->ToString();
|
|
}
|
|
|
|
// item_name to func addr from obj_map
|
|
parse::SymbolPtr symbol = item_v->cast<parse::SymbolPtr>();
|
|
parse::NameSpacePtr name_space = data_v->cast<parse::NameSpacePtr>();
|
|
FuncGraphPtr func_graph = out_conf->node()->func_graph();
|
|
|
|
auto new_node = parse::ResolveSymbol(func_graph->manager(), name_space, symbol, out_conf->node());
|
|
if (new_node == nullptr) {
|
|
MS_LOG(EXCEPTION) << "Resolve node failed";
|
|
}
|
|
|
|
AnalysisEnginePtr eng = out_conf->engine();
|
|
AnfNodeConfigPtr fn_conf = eng->MakeConfig(new_node, out_conf->context());
|
|
return eng->ForwardConfig(out_conf, fn_conf);
|
|
}
|
|
|
|
EvalResultPtr GetEvaluatedValueForClassAttrOrMethod(const AnalysisEnginePtr &engine,
|
|
const AbstractBasePtrList &args_spec_list, const ValuePtr &item_v,
|
|
const ConfigPtr &data_conf, const AnfNodeConfigPtr &out_conf) {
|
|
if (args_spec_list.empty()) {
|
|
MS_LOG(EXCEPTION) << "args_spec_list is empty";
|
|
}
|
|
AbstractClassPtr cls = CheckArg<AbstractClass>("__FUNC__", args_spec_list, 0);
|
|
|
|
// If item_v is an attribute, get abstract value from AbstractClass
|
|
MS_EXCEPTION_IF_NULL(item_v);
|
|
if (!item_v->isa<StringImm>()) {
|
|
MS_LOG(EXCEPTION) << "Attribute type error";
|
|
}
|
|
std::string item_name = item_v->cast<StringImmPtr>()->value();
|
|
MS_LOG(DEBUG) << "Resolve name: " << cls->tag().name();
|
|
MS_LOG(DEBUG) << "Resolve item: " << item_name;
|
|
|
|
AbstractBasePtr attr = cls->GetAttribute(item_name);
|
|
if (attr != nullptr) {
|
|
return std::make_shared<EvalResult>(attr, nullptr);
|
|
}
|
|
|
|
ValuePtr method = cls->GetMethod(item_name);
|
|
if (method->isa<AnyValue>()) {
|
|
MS_LOG(EXCEPTION) << "Unknown field, data type: " << args_spec_list[0]->BuildType()->ToString()
|
|
<< ", item value: " << item_v->ToString();
|
|
}
|
|
|
|
// Infer class method
|
|
ValuePtr converted_v = PyObjToGraph(engine, method);
|
|
return StaticGetterInferred(converted_v, data_conf, out_conf);
|
|
}
|
|
|
|
EvalResultPtr GetEvaluatedValueForBuiltinTypeMethod(const AnalysisEnginePtr &engine, const ValuePtr &item_v,
|
|
const TypePtr &data_type, const ConfigPtr &data_conf,
|
|
const AnfNodeConfigPtr &out_conf) {
|
|
MS_EXCEPTION_IF_NULL(item_v);
|
|
MS_EXCEPTION_IF_NULL(data_type);
|
|
// The method maybe a Primitive or Composite
|
|
if (!item_v->isa<StringImm>()) {
|
|
MS_LOG(EXCEPTION) << "Error item is not string";
|
|
}
|
|
|
|
std::string item_name = item_v->cast<StringImmPtr>()->value();
|
|
Any method = pipeline::Resource::GetMethodPtr(data_type->type_id(), item_name);
|
|
if (method.empty()) {
|
|
MS_LOG(EXCEPTION) << "Object type: " << data_type->ToString() << " has no method: " << item_name;
|
|
}
|
|
|
|
ValuePtr converted_v = nullptr;
|
|
if (method.is<std::string>()) {
|
|
// composite registered in standard_method_map go to this branch
|
|
converted_v = prim::GetPythonOps(method.cast<std::string>());
|
|
AddToManager(engine, converted_v->cast<FuncGraphPtr>());
|
|
} else if (method.is<PrimitivePtr>()) {
|
|
converted_v = method.cast<PrimitivePtr>();
|
|
} else {
|
|
MS_LOG(EXCEPTION) << "Expect to get string or PrimitivePtr from method map, but got " << method.ToString();
|
|
}
|
|
return StaticGetterInferred(converted_v, data_conf, out_conf);
|
|
}
|
|
|
|
EvalResultPtr StaticGetter(const AnalysisEnginePtr &engine, const AbstractBasePtrList &args_spec_list,
|
|
const ConfigPtr &data_conf, const AnfNodeConfigPtr &out_conf) {
|
|
// Inputs: namespace and its static function; or class and its member function
|
|
CheckArgsSize("StaticGetter", args_spec_list, 2);
|
|
|
|
MS_EXCEPTION_IF_NULL(args_spec_list[0]);
|
|
MS_EXCEPTION_IF_NULL(args_spec_list[1]);
|
|
TypePtr data_type = args_spec_list[0]->BuildType();
|
|
ValuePtr item_value = args_spec_list[1]->BuildValue();
|
|
ScopePtr scope = kDefaultScope;
|
|
if (out_conf != nullptr) {
|
|
scope = out_conf->node()->scope();
|
|
}
|
|
ScopeGuard scope_guard(scope);
|
|
if (item_value->isa<AnyValue>()) {
|
|
MS_LOG(EXCEPTION) << "The value of the attribute could not be inferred: " << item_value->ToString();
|
|
}
|
|
|
|
int case_v = GetResolveCase(data_type);
|
|
if (case_v == kResolveCaseUserDefineClass) {
|
|
return GetEvaluatedValueForClassAttrOrMethod(engine, args_spec_list, item_value, data_conf, out_conf);
|
|
} else if (case_v == kResolveCaseBuildinTypeMethod) {
|
|
return GetEvaluatedValueForBuiltinTypeMethod(engine, item_value, data_type, data_conf, out_conf);
|
|
} else {
|
|
return GetEvaluatedValueForNameSpaceString(engine, args_spec_list, out_conf);
|
|
}
|
|
}
|
|
} // end anonymous namespace
|
|
|
|
// static variable start;
|
|
namespace {
|
|
class EmbedEvaluator : public SymbolicPrimEvaluator {
|
|
public:
|
|
EmbedEvaluator() : SymbolicPrimEvaluator("EmbedEvaluator") {}
|
|
~EmbedEvaluator() override = default;
|
|
MS_DECLARE_PARENT(EmbedEvaluator, SymbolicPrimEvaluator);
|
|
EvalResultPtr EvalPrim(const ConfigPtrList &args_conf_list) override {
|
|
// arg: free variable to be embedded
|
|
if (args_conf_list.size() != 1) {
|
|
MS_LOG(EXCEPTION) << "EmbedEvaluator requires 1 parameter, but got " << args_conf_list.size();
|
|
}
|
|
AnfNodeConfigPtr node_conf = dyn_cast<AnfNodeConfig>(args_conf_list[0]);
|
|
MS_EXCEPTION_IF_NULL(node_conf);
|
|
|
|
AbstractBasePtr x = node_conf->GetEvaluatedValue()->abstract();
|
|
x = SensitivityTransform(x);
|
|
SymbolicKeyInstancePtr key = std::make_shared<SymbolicKeyInstance>(node_conf->node(), x);
|
|
AbstractScalarPtr abs_scalar = std::make_shared<AbstractScalar>(key, std::make_shared<SymbolicKeyType>());
|
|
return std::make_shared<EvalResult>(abs_scalar, std::make_shared<AttrValueMap>());
|
|
}
|
|
};
|
|
|
|
static AnfNodePtr FindParameterNodeByString(const FuncGraphManagerPtr &manager, const std::string &name) {
|
|
auto root_g_set = manager->roots();
|
|
if (root_g_set.size() != 1) {
|
|
return nullptr;
|
|
}
|
|
const FuncGraphPtr &root_g = root_g_set.back();
|
|
|
|
for (auto ¶m_node : root_g->parameters()) {
|
|
auto param = param_node->cast<ParameterPtr>();
|
|
if (param && name == param->name()) {
|
|
return param;
|
|
}
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
class RefToEmbedEvaluator : public SymbolicPrimEvaluator {
|
|
public:
|
|
RefToEmbedEvaluator() : SymbolicPrimEvaluator("RefToEmbedEvaluator") {}
|
|
~RefToEmbedEvaluator() override = default;
|
|
MS_DECLARE_PARENT(RefToEmbedEvaluator, SymbolicPrimEvaluator);
|
|
EvalResultPtr EvalPrim(const ConfigPtrList &args_conf_list) override {
|
|
if (args_conf_list.size() != 1) {
|
|
MS_LOG(ERROR) << "Requires 1 parameter, but has: " << args_conf_list.size();
|
|
return nullptr;
|
|
}
|
|
static TypePtr type = std::make_shared<SymbolicKeyType>();
|
|
auto node_conf = dyn_cast<AnfNodeConfig>(args_conf_list[0]);
|
|
if (node_conf == nullptr) {
|
|
MS_LOG(ERROR) << "Conf should be AnfNodeConfig";
|
|
return nullptr;
|
|
}
|
|
AbstractBasePtr abs = node_conf->GetEvaluatedValue()->abstract();
|
|
AbstractRefPtr ref_abs = abs->cast<AbstractRefPtr>();
|
|
if (ref_abs == nullptr) {
|
|
MS_LOG(ERROR) << "The first parameter of RefToEmbed should be Ref, but " << abs->ToString();
|
|
return nullptr;
|
|
}
|
|
auto key_abs = ref_abs->ref_key();
|
|
if (key_abs == nullptr) {
|
|
MS_LOG(ERROR) << "RefToEmbed input Ref key is nullptr.";
|
|
return nullptr;
|
|
}
|
|
auto key_value = key_abs->BuildValue();
|
|
if (key_value == nullptr) {
|
|
MS_LOG(ERROR) << "RefToEmbed input Ref key value is nullptr.";
|
|
return nullptr;
|
|
}
|
|
auto refkey = key_value->cast<RefKeyPtr>();
|
|
if (refkey == nullptr) {
|
|
auto ret = std::make_shared<AbstractScalar>(type);
|
|
auto ref_value = ref_abs->ref();
|
|
MS_EXCEPTION_IF_NULL(ref_value);
|
|
ret->set_sparse_grad(ref_value->sparse_grad());
|
|
return std::make_shared<EvalResult>(ret, std::make_shared<AttrValueMap>());
|
|
}
|
|
|
|
std::string name = refkey->tag();
|
|
const auto &manager = node_conf->node()->func_graph()->manager();
|
|
auto node = FindParameterNodeByString(manager, name);
|
|
if (node == nullptr) {
|
|
MS_LOG(ERROR) << "RefToEmbed input can't find parameter \"" << name << "\" in graph.";
|
|
return nullptr;
|
|
}
|
|
AbstractBasePtr x = ref_abs->ref();
|
|
x = SensitivityTransform(x);
|
|
std::shared_ptr<SymbolicKeyInstance> key = std::make_shared<SymbolicKeyInstance>(node, x);
|
|
std::shared_ptr<AbstractScalar> abs_scalar = std::make_shared<AbstractScalar>(key, type);
|
|
abs_scalar->set_sparse_grad(x->sparse_grad());
|
|
return std::make_shared<EvalResult>(abs_scalar, std::make_shared<AttrValueMap>());
|
|
}
|
|
};
|
|
|
|
class GetAttrEvaluator : public TransitionPrimEvaluator {
|
|
public:
|
|
GetAttrEvaluator() : TransitionPrimEvaluator("GetAttrEvaluator") {}
|
|
~GetAttrEvaluator() override = default;
|
|
MS_DECLARE_PARENT(GetAttrEvaluator, TransitionPrimEvaluator);
|
|
EvalResultPtr EvalPrim(const AnalysisEnginePtr &engine, const AbstractBasePtrList &args_spec_list,
|
|
const ConfigPtr &in_conf0, const AnfNodeConfigPtr &out_conf) override {
|
|
// Inputs: data, item
|
|
if (args_spec_list.size() != 2) {
|
|
MS_LOG(EXCEPTION) << "Expected args_spec_list size = 2, but has size:" << args_spec_list.size();
|
|
}
|
|
EvalResultPtr ret = nullptr;
|
|
if (bound_node() != nullptr) {
|
|
TraceManager::DebugTrace(std::make_shared<TraceResolve>(bound_node()->debug_info()));
|
|
ret = StaticGetter(engine, args_spec_list, in_conf0, out_conf);
|
|
TraceManager::EndTrace();
|
|
} else {
|
|
ret = StaticGetter(engine, args_spec_list, in_conf0, out_conf);
|
|
}
|
|
// don't lookup from cache, as different out_conf with same node but different context
|
|
// may add different entry to anfnode_config_map, like getattr primitive;
|
|
(*cache_)[args_spec_list] = ret;
|
|
return ret;
|
|
}
|
|
};
|
|
|
|
class ResolveEvaluator : public TransitionPrimEvaluator {
|
|
public:
|
|
ResolveEvaluator() : TransitionPrimEvaluator("ResolveEvaluator") {}
|
|
~ResolveEvaluator() override = default;
|
|
MS_DECLARE_PARENT(ResolveEvaluator, TransitionPrimEvaluator);
|
|
EvalResultPtr EvalPrim(const AnalysisEnginePtr &engine, const AbstractBasePtrList &args_spec_list,
|
|
const ConfigPtr &in_conf0, const AnfNodeConfigPtr &out_conf) override {
|
|
// Inputs: namespace, symbol
|
|
if (args_spec_list.size() != 2) {
|
|
MS_LOG(EXCEPTION) << "Expected args_spec_list size = 2, but has size:" << args_spec_list.size();
|
|
}
|
|
EvalResultPtr ret = nullptr;
|
|
if (bound_node() != nullptr) {
|
|
TraceManager::DebugTrace(std::make_shared<TraceResolve>(bound_node()->debug_info()));
|
|
ret = StaticGetter(engine, args_spec_list, in_conf0, out_conf);
|
|
TraceManager::EndTrace();
|
|
} else {
|
|
ret = StaticGetter(engine, args_spec_list, in_conf0, out_conf);
|
|
}
|
|
return ret;
|
|
}
|
|
};
|
|
|
|
class CreateInstanceEvaluator : public TransitionPrimEvaluator {
|
|
public:
|
|
CreateInstanceEvaluator() : TransitionPrimEvaluator("CreateInstanceEvaluator") {}
|
|
~CreateInstanceEvaluator() override = default;
|
|
MS_DECLARE_PARENT(CreateInstanceEvaluator, TransitionPrimEvaluator);
|
|
EvalResultPtr EvalPrim(const AnalysisEnginePtr &engine, const AbstractBasePtrList &args_spec_list, const ConfigPtr &,
|
|
const AnfNodeConfigPtr &out_conf) override {
|
|
if (args_spec_list.empty()) {
|
|
MS_LOG(EXCEPTION) << "'args_spec_list' should not be empty";
|
|
}
|
|
|
|
// get the type parameter
|
|
MS_EXCEPTION_IF_NULL(args_spec_list[0]);
|
|
TypePtr type = args_spec_list[0]->GetTypeTrack();
|
|
if (type->type_id() != kMetaTypeTypeType) {
|
|
MS_LOG(EXCEPTION) << "CreateInstanceEvaluator require first parameter should be an object of TypeType, but got "
|
|
<< type->ToString();
|
|
}
|
|
|
|
ValuePtr value_track = args_spec_list[0]->GetValueTrack();
|
|
MS_EXCEPTION_IF_NULL(value_track);
|
|
|
|
std::shared_ptr<parse::PyObjectWrapper> type_obj = dyn_cast<parse::PyObjectWrapper>(value_track);
|
|
if (type_obj == nullptr) {
|
|
MS_LOG(EXCEPTION) << "Cast value failed, not PyObjectWrapper:" << value_track->ToString() << ".";
|
|
}
|
|
|
|
if (!type_obj->isa<parse::ClassType>()) {
|
|
MS_LOG(EXCEPTION) << "CreateInstanceEvaluator the type_obj should be an object of ClassType, but got "
|
|
<< type_obj->ToString() << ".";
|
|
}
|
|
|
|
auto class_type = type_obj->obj();
|
|
MS_LOG(DEBUG) << "Get class type is " << type_obj->ToString() << ".";
|
|
|
|
// get the create instance obj's parameters
|
|
pybind11::tuple params = GetParameters(args_spec_list);
|
|
|
|
// create class instance
|
|
auto obj = parse::data_converter::CreatePythonObject(class_type, params);
|
|
if (py::isinstance<py::none>(obj)) {
|
|
MS_LOG(EXCEPTION) << "Create python object failed, only support Cell and Primitive type";
|
|
}
|
|
|
|
// process the object
|
|
ValuePtr converted_ret = nullptr;
|
|
bool converted = parse::ConvertData(obj, &converted_ret, true);
|
|
if (!converted) {
|
|
MS_LOG(EXCEPTION) << "Convert the python object failed";
|
|
}
|
|
MS_EXCEPTION_IF_NULL(converted_ret);
|
|
|
|
if (converted_ret->isa<FuncGraph>()) {
|
|
AddToManager(engine, converted_ret->cast<FuncGraphPtr>());
|
|
}
|
|
|
|
AbstractBasePtr ret = ToAbstract(converted_ret, AnalysisContext::DummyContext(), out_conf);
|
|
auto infer_result = std::make_shared<EvalResult>(ret, nullptr);
|
|
(*cache_)[args_spec_list] = infer_result;
|
|
return infer_result;
|
|
}
|
|
|
|
pybind11::tuple GetParameters(const AbstractBasePtrList &args_spec_list) const {
|
|
// Exclude class type by minus 1;
|
|
std::size_t params_size = args_spec_list.size() - 1;
|
|
auto params = py::tuple(params_size);
|
|
if (params_size > 0) {
|
|
for (size_t i = 0; i < params_size; i++) {
|
|
// Only support the Scalar parameters type. Bypass class type by offset with 1.
|
|
auto arg = args_spec_list[i + 1];
|
|
MS_EXCEPTION_IF_NULL(arg);
|
|
// Because the Tensor's AbstractTensor can't get value from GetValueTrack.
|
|
ValuePtr param_value = arg->BuildValue();
|
|
py::object param = ValuePtrToPyData(param_value);
|
|
params[i] = param;
|
|
}
|
|
}
|
|
return params;
|
|
}
|
|
};
|
|
|
|
class PartialEvaluator : public Evaluator {
|
|
public:
|
|
PartialEvaluator() : Evaluator("PartialEvaluator") {}
|
|
~PartialEvaluator() override = default;
|
|
EvalResultPtr Run(AnalysisEnginePtr engine, const ConfigPtrList &args_conf_list,
|
|
AnfNodeConfigPtr out_conf = nullptr) override {
|
|
if (args_conf_list.size() == 0) {
|
|
MS_LOG(EXCEPTION) << "Args size should be greater than 0";
|
|
}
|
|
|
|
MS_EXCEPTION_IF_NULL(out_conf);
|
|
MS_EXCEPTION_IF_NULL(out_conf->node());
|
|
auto arg0_value = args_conf_list[0]->GetEvaluatedValue()->abstract();
|
|
AbstractBasePtrList args_spec_list{arg0_value};
|
|
// Func in hypermap(partial(Func, arg0), arg1, arg2) may become Poly Node.
|
|
if (arg0_value->isa<AbstractError>()) {
|
|
auto ret = std::make_shared<AbstractError>(arg0_value->GetValueTrack()->cast<StringImmPtr>(), out_conf->node());
|
|
MS_LOG(DEBUG) << "AbstractError for node: " << out_conf->node()->DebugString()
|
|
<< " as func is: " << arg0_value->ToString();
|
|
auto eval_result = std::make_shared<EvalResult>(ret, std::make_shared<AttrValueMap>());
|
|
(*cache_)[args_spec_list] = eval_result;
|
|
return eval_result;
|
|
}
|
|
auto func = CheckArg<AbstractFunction>("partial", args_spec_list, 0);
|
|
// Sometimes, node[0] in out_conf becomes phi0;
|
|
if (func->isa<PrimitiveAbstractClosure>()) {
|
|
auto prim_func = dyn_cast<PrimitiveAbstractClosure>(func);
|
|
if (prim_func->prim()->isa<prim::DoSignaturePrimitive>()) {
|
|
prim::DoSignaturePrimitivePtr do_signature_prim = dyn_cast<prim::DoSignaturePrimitive>(prim_func->prim());
|
|
return HandleDoSignature(engine, do_signature_prim->function(), out_conf);
|
|
}
|
|
}
|
|
|
|
(void)std::transform(
|
|
args_conf_list.begin() + 1, args_conf_list.end(), std::back_inserter(args_spec_list),
|
|
[](const ConfigPtr &config) -> AbstractBasePtr { return config->GetEvaluatedValue()->abstract(); });
|
|
AbstractBasePtrList args(args_spec_list.begin() + 1, args_spec_list.end());
|
|
|
|
auto cnode = out_conf->node()->cast<CNodePtr>();
|
|
MS_EXCEPTION_IF_NULL(cnode);
|
|
if (cnode->size() != (args_conf_list.size() + 1)) {
|
|
MS_LOG(EXCEPTION) << "Out_conf node: " << cnode->DebugString()
|
|
<< ", args_conf_list: " << mindspore::ToString(args_conf_list);
|
|
}
|
|
|
|
AbstractFuncAtomPtrList partial_funcs_list;
|
|
auto build_partial = [args, cnode, &partial_funcs_list](const AbstractFuncAtomPtr &atom_func) {
|
|
auto new_func = std::make_shared<PartialAbstractClosure>(atom_func, args, cnode);
|
|
partial_funcs_list.push_back(new_func);
|
|
};
|
|
func->Visit(build_partial);
|
|
|
|
auto ret = AbstractFunction::MakeAbstractFunction(partial_funcs_list);
|
|
auto infer_result = std::make_shared<EvalResult>(ret, std::make_shared<AttrValueMap>());
|
|
(*cache_)[args_spec_list] = infer_result;
|
|
return infer_result;
|
|
}
|
|
|
|
EvalResultPtr Eval(AnalysisEnginePtr, const AbstractBasePtrList &) override {
|
|
MS_LOG(EXCEPTION) << "Eval() should not be called, Run() method should be called";
|
|
}
|
|
|
|
EvalResultPtr HandleDoSignature(const AnalysisEnginePtr &engine, const ValuePtr &signature_value,
|
|
const AnfNodeConfigPtr &out_conf = nullptr) const {
|
|
MS_EXCEPTION_IF_NULL(out_conf);
|
|
MS_EXCEPTION_IF_NULL(out_conf->node());
|
|
auto cnode = out_conf->node()->cast<CNodePtr>();
|
|
if (cnode == nullptr) {
|
|
MS_LOG(EXCEPTION) << "Cnode is nullptr";
|
|
}
|
|
std::vector<AnfNodePtr> new_nodes_inputs = cnode->inputs();
|
|
auto new_signature_value = std::make_shared<prim::DoSignatureMetaFuncGraph>("signature", signature_value);
|
|
new_nodes_inputs[1] = NewValueNode(new_signature_value);
|
|
FuncGraphPtr func_graph = cnode->func_graph();
|
|
|
|
ScopePtr scope = out_conf->node()->scope();
|
|
ScopeGuard scope_guard(scope);
|
|
|
|
CNodePtr new_cnode = func_graph->NewCNode(new_nodes_inputs);
|
|
AnfNodeConfigPtr fn_conf = engine->MakeConfig(new_cnode, out_conf->context());
|
|
return engine->ForwardConfig(out_conf, fn_conf);
|
|
}
|
|
};
|
|
|
|
struct PrimitiveImplInferValue {
|
|
PrimitiveImpl impl_; // implement function of primitive
|
|
bool eval_value_; // whether evaluate value
|
|
TypePtr specify_out_type_; // whether specify return type
|
|
bool in_white_list_; // true if this Primitive in white list, else false.
|
|
};
|
|
|
|
using PrimitiveToImplMap = std::unordered_map<PrimitivePtr, PrimitiveImplInferValue, PrimitiveHasher, PrimitiveEqual>;
|
|
PrimitiveToImplMap &GetUniformPrimitiveToImplMap() {
|
|
static PrimitiveToImplMap uniform_prim_implement_map = {
|
|
{prim::kPrimScalarAdd, {prim::ScalarAdd, true, nullptr, true}},
|
|
{prim::kPrimScalarSub, {prim::ScalarSub, true, nullptr, true}},
|
|
{prim::kPrimScalarMul, {prim::ScalarMul, true, nullptr, true}},
|
|
{prim::kPrimScalarDiv, {prim::ScalarDiv, true, nullptr, true}},
|
|
{prim::kPrimScalarMod, {prim::ScalarMod, true, nullptr, true}},
|
|
{prim::kPrimScalarPow, {prim::ScalarPow, true, nullptr, true}},
|
|
{prim::kPrimScalarFloordiv, {prim::ScalarFloordiv, true, nullptr, true}},
|
|
{prim::kPrimScalarUadd, {prim::ScalarUAdd, true, nullptr, true}},
|
|
{prim::kPrimScalarUsub, {prim::ScalarUSub, true, nullptr, true}},
|
|
{prim::kPrimScalarLog, {prim::ScalarLog, true, nullptr, true}},
|
|
{prim::kPrimScalarEq, {prim::ScalarEq, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimScalarLt, {prim::ScalarLt, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimScalarGt, {prim::ScalarGt, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimScalarNe, {prim::ScalarNe, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimScalarLe, {prim::ScalarLe, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimScalarGe, {prim::ScalarGe, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimBoolNot, {prim::BoolNot, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimBoolAnd, {prim::BoolAnd, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimBoolEq, {prim::BoolEq, true, std::make_shared<Bool>(), true}},
|
|
{prim::kPrimBoolOr, {prim::BoolOr, true, std::make_shared<Bool>(), true}},
|
|
};
|
|
return uniform_prim_implement_map;
|
|
}
|
|
|
|
PrimEvaluatorMap PrimEvaluatorConstructors = PrimEvaluatorMap();
|
|
std::mutex PrimEvaluatorConstructorMutex;
|
|
|
|
void InitPrimEvaluatorConstructors() {
|
|
PrimEvaluatorMap &constructor = PrimEvaluatorConstructors;
|
|
|
|
for (const auto &iter : GetPrimitiveToEvalImplMap()) {
|
|
constructor[iter.first] = InitStandardPrimEvaluator(iter.first, iter.second.impl_);
|
|
}
|
|
|
|
for (const auto &iter : GetUniformPrimitiveToImplMap()) {
|
|
constructor[iter.first] =
|
|
InitUniformPrimEvaluator(iter.first, iter.second.impl_, iter.second.eval_value_, iter.second.specify_out_type_);
|
|
}
|
|
constructor[prim::kPrimEmbed] = std::make_shared<EmbedEvaluator>();
|
|
constructor[prim::kPrimRefToEmbed] = std::make_shared<RefToEmbedEvaluator>();
|
|
constructor[prim::kPrimGetAttr] = std::make_shared<GetAttrEvaluator>();
|
|
constructor[prim::kPrimResolve] = std::make_shared<ResolveEvaluator>();
|
|
constructor[prim::kPrimCreateInstance] = std::make_shared<CreateInstanceEvaluator>();
|
|
constructor[prim::kPrimPartial] = std::make_shared<PartialEvaluator>();
|
|
}
|
|
} // namespace
|
|
|
|
void ClearPrimEvaluatorMap() {
|
|
PrimEvaluatorConstructors.clear();
|
|
GetPrimitiveToEvalImplMap().clear();
|
|
GetUniformPrimitiveToImplMap().clear();
|
|
}
|
|
|
|
bool IsInWhiteList(const PrimitivePtr primitive) {
|
|
MS_EXCEPTION_IF_NULL(primitive);
|
|
|
|
auto iter = GetPrimitiveToEvalImplMap().find(primitive);
|
|
if (iter != GetPrimitiveToEvalImplMap().end()) {
|
|
return iter->second.in_white_list_;
|
|
}
|
|
|
|
auto uni_iter = GetUniformPrimitiveToImplMap().find(primitive);
|
|
if (uni_iter != GetUniformPrimitiveToImplMap().end()) {
|
|
return uni_iter->second.in_white_list_;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
StandardPrimitiveEvalImpl GetPrimitiveInferImpl(const PrimitivePtr &primitive) {
|
|
MS_EXCEPTION_IF_NULL(primitive);
|
|
auto iter = GetPrimitiveToEvalImplMap().find(primitive);
|
|
if (iter == GetPrimitiveToEvalImplMap().end()) {
|
|
return nullptr;
|
|
}
|
|
return iter->second.impl_;
|
|
}
|
|
|
|
PrimEvaluatorMap &GetPrimEvaluatorConstructors() {
|
|
PrimEvaluatorMap &constructor = PrimEvaluatorConstructors;
|
|
if (!constructor.empty()) {
|
|
return constructor;
|
|
}
|
|
std::lock_guard<std::mutex> initLock(PrimEvaluatorConstructorMutex);
|
|
if (constructor.empty()) {
|
|
InitPrimEvaluatorConstructors();
|
|
}
|
|
|
|
return constructor;
|
|
}
|
|
|
|
namespace {
|
|
bool IsSubtypeTuple(const AbstractBasePtr x, const TypePtr model) {
|
|
MS_EXCEPTION_IF_NULL(x);
|
|
MS_EXCEPTION_IF_NULL(model);
|
|
auto x_tuple = dyn_cast<AbstractTuple>(x);
|
|
auto model_tuple = dyn_cast<Tuple>(model);
|
|
|
|
if (x_tuple == nullptr || model_tuple == nullptr) {
|
|
return false;
|
|
}
|
|
|
|
if (model->IsGeneric()) {
|
|
return true;
|
|
}
|
|
|
|
if (x_tuple->size() != model_tuple->size()) {
|
|
return false;
|
|
}
|
|
|
|
for (size_t i = 0; i < x_tuple->size(); i++) {
|
|
bool is_subtype = IsSubtype((*x_tuple)[i], (*model_tuple)[i]);
|
|
if (!is_subtype) {
|
|
return false;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool IsSubtypeArray(const AbstractBasePtr x, const TypePtr model) {
|
|
MS_EXCEPTION_IF_NULL(x);
|
|
MS_EXCEPTION_IF_NULL(model);
|
|
auto x_tensor = dyn_cast<AbstractTensor>(x);
|
|
auto model_tensor = dyn_cast<TensorType>(model);
|
|
|
|
if (x_tensor == nullptr || model_tensor == nullptr) {
|
|
return false;
|
|
}
|
|
|
|
if (model->IsGeneric()) {
|
|
return true;
|
|
}
|
|
|
|
return IsSubtype(x_tensor->element(), model_tensor->element());
|
|
}
|
|
|
|
bool IsSubtypeList(const AbstractBasePtr x, const TypePtr model) {
|
|
MS_EXCEPTION_IF_NULL(x);
|
|
MS_EXCEPTION_IF_NULL(model);
|
|
auto x_list = dyn_cast<AbstractList>(x);
|
|
auto model_list = dyn_cast<List>(model);
|
|
|
|
if (x_list == nullptr || model_list == nullptr) {
|
|
return false;
|
|
}
|
|
|
|
if (model->IsGeneric()) {
|
|
return true;
|
|
}
|
|
|
|
if (x_list->size() != model_list->size()) {
|
|
return false;
|
|
}
|
|
|
|
bool is_subtype = true;
|
|
for (size_t i = 0; i < x_list->size(); i++) {
|
|
is_subtype = IsSubtype((*x_list)[i], (*model_list)[i]);
|
|
if (!is_subtype) {
|
|
return false;
|
|
}
|
|
}
|
|
return is_subtype;
|
|
}
|
|
|
|
bool IsSubtypeClass(const AbstractBasePtr x, const TypePtr model) {
|
|
MS_EXCEPTION_IF_NULL(x);
|
|
MS_EXCEPTION_IF_NULL(model);
|
|
auto x_class = dyn_cast<AbstractClass>(x);
|
|
auto model_class = dyn_cast<Class>(model);
|
|
if (x_class == nullptr) {
|
|
return false;
|
|
}
|
|
if (model->IsGeneric()) {
|
|
return true;
|
|
}
|
|
|
|
if (x_class->tag() == model_class->tag()) {
|
|
auto m_attributes = model_class->GetAttributes();
|
|
auto x_attributes = x_class->attributes();
|
|
if (m_attributes.size() != x_attributes.size()) {
|
|
return false;
|
|
}
|
|
|
|
for (size_t i = 0; i < m_attributes.size(); i++) {
|
|
if (!IsSubtype(x_attributes[i].second, m_attributes[i].second)) {
|
|
return false;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
inline bool IsSubtypeScalar(const AbstractBasePtr x, const TypePtr model) {
|
|
MS_EXCEPTION_IF_NULL(x);
|
|
MS_EXCEPTION_IF_NULL(model);
|
|
if (dyn_cast<AbstractScalar>(x) == nullptr) {
|
|
return false;
|
|
}
|
|
TypePtr x_type = x->GetTypeTrack();
|
|
return IsSubType(x_type, model);
|
|
}
|
|
} // namespace
|
|
|
|
bool IsSubtype(const AbstractBasePtr x, const TypePtr model) {
|
|
MS_EXCEPTION_IF_NULL(x);
|
|
MS_EXCEPTION_IF_NULL(model);
|
|
TypeId model_typeid = model->type_id();
|
|
switch (model_typeid) {
|
|
case kMetaTypeObject:
|
|
return true;
|
|
case kObjectTypeTuple:
|
|
return IsSubtypeTuple(x, model);
|
|
case kObjectTypeTensorType:
|
|
return IsSubtypeArray(x, model);
|
|
case kObjectTypeList:
|
|
return IsSubtypeList(x, model);
|
|
case kObjectTypeClass:
|
|
return IsSubtypeClass(x, model);
|
|
default:
|
|
if (IsSubType(model, std::make_shared<Number>())) {
|
|
return IsSubtypeScalar(x, model);
|
|
}
|
|
MS_LOG(EXCEPTION) << "Invalid model type: " << model->ToString() << ".";
|
|
}
|
|
}
|
|
} // namespace abstract
|
|
} // namespace mindspore
|