forked from huawei/mindspore2022
85 lines
3.2 KiB
C++
85 lines
3.2 KiB
C++
/**
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* Copyright 2019 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/param_validator.h"
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#include "pipeline/static_analysis/prim.h"
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#include "operator/ops.h"
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#include "pipeline/static_analysis/utils.h"
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#include "utils/symbolic.h"
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namespace mindspore {
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namespace abstract {
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AbstractBasePtr InferImplScalarSummary(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
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const AbstractBasePtrList &args_spec_list) {
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// Inputs: a scalar and a tensor or scalar.
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const std::string op_name = primitive->name();
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CheckArgsSize(op_name, args_spec_list, 2);
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// check the tag
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AbstractScalarPtr descriptions = CheckArg<AbstractScalar>(op_name, args_spec_list, 0);
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// check the value: scalar or shape = (1,)
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auto scalar_value = dyn_cast<AbstractScalar>(args_spec_list[1]);
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if (scalar_value == nullptr) {
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auto tensor_value = dyn_cast<AbstractTensor>(args_spec_list[1]);
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if (tensor_value == nullptr) {
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MS_LOG(EXCEPTION) << "Input must be scalar or shape(1,)";
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}
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} else {
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auto item_v = scalar_value->BuildValue();
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if (item_v->isa<StringImm>()) {
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auto value = item_v->cast<StringImmPtr>()->value();
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if (value.empty()) {
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MS_LOG(EXCEPTION) << "Input summary value can't be null";
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}
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}
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}
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// Reomve the force check to support batch set summary use 'for' loop
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auto item_v = descriptions->BuildValue();
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if (!item_v->isa<StringImm>()) {
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MS_EXCEPTION(TypeError) << "Summary first parameter should be string";
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}
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return std::make_shared<AbstractScalar>(kAnyValue, kBool);
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}
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AbstractBasePtr InferImplTensorSummary(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
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const AbstractBasePtrList &args_spec_list) {
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// Inputs: a scalar(tag) and a tensor(value)
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const std::string op_name = primitive->name();
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CheckArgsSize(op_name, args_spec_list, 2);
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// check the tag
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auto descriptions = CheckArg<AbstractScalar>(op_name, args_spec_list, 0);
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auto tensor_value = CheckArg<AbstractTensor>(op_name, args_spec_list, 1);
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int tensor_rank = SizeToInt(tensor_value->shape()->shape().size());
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if (tensor_rank == 0) {
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MS_LOG(EXCEPTION) << op_name << " summary evaluator second arg should be an tensor, but got a scalar, rank is 0";
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}
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// Reomve the force check to support batch set summary use 'for' loop
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auto item_v = descriptions->BuildValue();
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if (!item_v->isa<StringImm>()) {
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MS_EXCEPTION(TypeError) << "Summary first parameter should be string";
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}
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return std::make_shared<AbstractScalar>(kAnyValue, std::make_shared<Bool>());
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}
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} // namespace abstract
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} // namespace mindspore
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