src/api/operator/numpy/np_insert_op.cc - master - githubmirror/incubator-mxnet

src/api/operator/numpy/np_insert_op.cc
160 строк6 KB
mozga
[master][bugfix] Zero initialization to avoid error message on a Centos (#20582)
18 ноя 2021, 15:21
18 ноя 2021, 15:21bfa71cf
/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you 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.
 */

/*!
 * \file np_insert_op.cc
 * \brief Implementation of the API of functions in the following file:
          src/operator/numpy/np_insert_op_scalar.cc
          src/operator/numpy/np_insert_op_slice.cc
          src/operator/numpy/np_insert_op_tensor.cc
 */
#include <mxnet/api_registry.h>
#include <mxnet/runtime/packed_func.h>
#include <vector>
#include "../utils.h"
#include "../../../operator/numpy/np_insert_op-inl.h"

namespace mxnet {

MXNET_REGISTER_API("_npi.insert_scalar")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      static const nnvm::Op* op = Op::Get("_npi_insert_scalar");
      nnvm::NodeAttrs attrs;
      op::NumpyInsertParam param = {};
      int num_inputs = 0;
      param.start    = dmlc::nullopt;
      param.step     = dmlc::nullopt;
      param.stop     = dmlc::nullopt;
      if (args[1].type_code() == kDLInt || args[1].type_code() == kDLUInt ||
          args[1].type_code() == kDLFloat) {
        param.val  = args[1].operator double();
        num_inputs = 1;
      } else {
        param.val  = dmlc::nullopt;
        num_inputs = 2;
      }
      if (features::is_enabled(features::INT64_TENSOR_SIZE)) {
        param.int_ind = args[2].operator int64_t();
      } else {
        param.int_ind = args[2].operator int();
      }
      if (args[3].type_code() == kNull) {
        param.axis = dmlc::nullopt;
      } else {
        param.axis = args[3].operator int();
      }
      attrs.parsed = param;
      attrs.op     = op;
      SetAttrDict<op::NumpyInsertParam>(&attrs);
      std::vector<NDArray*> inputs;
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }
      int num_outputs = 0;
      auto ndoutputs  = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, nullptr);
      *ret            = ndoutputs[0];
    });

MXNET_REGISTER_API("_npi.insert_slice")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      static const nnvm::Op* op = Op::Get("_npi_insert_slice");
      nnvm::NodeAttrs attrs;
      op::NumpyInsertParam param = {};
      int num_inputs = 0;
      if (args[1].type_code() == kDLInt || args[1].type_code() == kDLUInt ||
          args[1].type_code() == kDLFloat) {
        param.val  = args[1].operator double();
        num_inputs = 1;
      } else {
        param.val  = dmlc::nullopt;
        num_inputs = 2;
      }
      if (args[2].type_code() == kNull) {
        param.start = dmlc::nullopt;
      } else {
        param.start = args[2].operator int64_t();
      }
      if (args[3].type_code() == kNull) {
        param.stop = dmlc::nullopt;
      } else {
        param.stop = args[3].operator int64_t();
      }
      if (args[4].type_code() == kNull) {
        param.step = dmlc::nullopt;
      } else {
        param.step = args[4].operator int64_t();
      }
      if (args[5].type_code() == kNull) {
        param.axis = dmlc::nullopt;
      } else {
        param.axis = args[5].operator int();
      }
      attrs.parsed = param;
      attrs.op     = op;
      SetAttrDict<op::NumpyInsertParam>(&attrs);
      std::vector<NDArray*> inputs;
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }
      int num_outputs = 0;
      auto ndoutputs  = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, nullptr);
      *ret            = ndoutputs[0];
    });

MXNET_REGISTER_API("_npi.insert_tensor")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      static const nnvm::Op* op = Op::Get("_npi_insert_tensor");
      nnvm::NodeAttrs attrs;
      op::NumpyInsertParam param = {};
      param.start    = dmlc::nullopt;
      param.step     = dmlc::nullopt;
      param.stop     = dmlc::nullopt;
      int num_inputs = 0;
      if (args[2].type_code() == kDLInt || args[2].type_code() == kDLUInt ||
          args[2].type_code() == kDLFloat) {
        param.val  = args[2].operator double();
        num_inputs = 2;
      } else {
        param.val  = dmlc::nullopt;
        num_inputs = 3;
      }
      if (args[3].type_code() == kNull) {
        param.axis = dmlc::nullopt;
      } else {
        param.axis = args[3].operator int();
      }
      attrs.parsed = param;
      attrs.op     = op;
      SetAttrDict<op::NumpyInsertParam>(&attrs);
      std::vector<NDArray*> inputs;
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }
      int num_outputs = 0;
      auto ndoutputs  = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, nullptr);
      *ret            = ndoutputs[0];
    });

}  // namespace mxnet