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- /**
- * Copyright 2020 Huawei Technologies Co., Ltd
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
- #include "ops/round.h"
- #include "ops/op_utils.h"
- #include "utils/check_convert_utils.h"
- #include "abstract/primitive_infer_map.h"
-
- namespace mindspore {
- namespace ops {
- namespace {
- abstract::ShapePtr InferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
- auto x_shape = CheckAndConvertUtils::ConvertShapePtrToShape("x_shape", input_args[0]->BuildShape(), "round");
- return std::make_shared<abstract::Shape>(x_shape);
- }
-
- TypePtr InferType(const PrimitivePtr &prim, const std::vector<AbstractBasePtr> &input_args) {
- auto infer_type = input_args[0]->BuildType();
- CheckAndConvertUtils::CheckTensorTypeValid("x", infer_type, common_valid_types, prim->name());
- MS_EXCEPTION_IF_NULL(infer_type);
- auto tensor_type = infer_type->cast<TensorTypePtr>();
- MS_EXCEPTION_IF_NULL(tensor_type);
- auto data_type = tensor_type->element();
- MS_EXCEPTION_IF_NULL(data_type);
- return data_type;
- }
- } // namespace
-
- AbstractBasePtr RoundInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
- const std::vector<AbstractBasePtr> &input_args) {
- return std::make_shared<abstract::AbstractTensor>(InferType(primitive, input_args),
- InferShape(primitive, input_args)->shape());
- }
- REGISTER_PRIMITIVE_EVAL_IMPL(Round, prim::kPrimRound, RoundInfer);
- REGISTER_PRIMITIVE_C(kNameRound, Round);
- } // namespace ops
- } // namespace mindspore
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