mindspore2022/mindspore/core/ops/cdist.cc

/**
 * Copyright 2021 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/cdist.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) {
  MS_EXCEPTION_IF_NULL(primitive);
  for (const auto &item : input_args) {
    MS_EXCEPTION_IF_NULL(item);
  }
  auto x_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape())[kShape];
  auto y_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[1]->BuildShape())[kShape];
  auto x_size = x_shape.size();
  auto y_size = y_shape.size();
  if (x_size != y_size) {
    MS_EXCEPTION(ValueError) << "For Cdist, rank of input_x and input_y should be equal.";
  }
  CheckAndConvertUtils::CheckInRange("input_x dim", x_size, kIncludeBoth, {2, 3}, "Cdist");
  int64_t dim_R = y_shape[y_size - 2];
  auto out_shape = x_shape;
  out_shape.pop_back();
  out_shape.push_back(dim_R);
  return std::make_shared<abstract::Shape>(out_shape);
}

TypePtr InferType(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
  for (const auto &item : input_args) {
    MS_EXCEPTION_IF_NULL(item);
  }
  const std::set<TypePtr> valid_types = {kFloat32, kFloat16};
  std::map<std::string, TypePtr> types;
  (void)types.emplace("input_x", input_args[0]->BuildType());
  (void)types.emplace("input_y", input_args[1]->BuildType());
  return CheckAndConvertUtils::CheckTensorTypeSame(types, valid_types, primitive->name());
}
}  // namespace

AbstractBasePtr CdistInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                           const std::vector<AbstractBasePtr> &input_args) {
  MS_EXCEPTION_IF_NULL(primitive);
  const int64_t input_num = 2;
  CheckAndConvertUtils::CheckInputArgs(input_args, kEqual, input_num, primitive->name());
  auto infer_type = InferType(primitive, input_args);
  auto infer_shape = InferShape(primitive, input_args);
  return abstract::MakeAbstract(infer_shape, infer_type);
}
REGISTER_PRIMITIVE_EVAL_IMPL(Cdist, prim::kPrimCdist, CdistInfer, nullptr, true);
}  // namespace ops
}  // namespace mindspore