src/api/operator/numpy_extension/npx_softmax_op.cc

/*
 * 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 npx_softmax_op.cc
 * \brief Implementation of the API of functions in src/operator/numpy_extension/npx_softmax_op.cc
 */
#include <mxnet/api_registry.h>
#include <mxnet/runtime/packed_func.h>
#include "../utils.h"
#include "../../../operator/nn/softmax-inl.h"

namespace mxnet {

MXNET_REGISTER_API("_npx.softmax")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      nnvm::NodeAttrs attrs;
      static const nnvm::Op* op = Op::Get("_npx_softmax");
      op::SoftmaxParam param    = {};
      int args_size             = args.size();
      // inputs
      int num_inputs = args_size - 4;
      std::vector<NDArray*> inputs;
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }

      // parse use_length
      if (args[args_size - 2].type_code() == kNull) {
        param.use_length = false;
      } else {
        param.use_length = args[args_size - 2].operator bool();
      }

      // parse axis
      if (args[args_size - 4].type_code() == kDLInt) {
        param.axis = args[args_size - 4].operator int();
      } else if (args[args_size - 4].type_code() == kDLFloat) {
        param.axis = static_cast<int>(args[args_size - 4].operator double());
      } else {
        param.axis = -1;
      }

      // parse temperature
      if (args[args_size - 3].type_code() == kNull) {
        param.temperature = dmlc::nullopt;
      } else {
        param.temperature = args[args_size - 3].operator double();
      }

      // parse dtype
      if (args[args_size - 1].type_code() == kNull) {
        param.dtype = dmlc::nullopt;
      } else {
        param.dtype = String2MXNetTypeWithBool(args[args_size - 1].operator std::string());
      }

      attrs.parsed = param;
      attrs.op     = op;
      SetAttrDict<op::SoftmaxParam>(&attrs);

      int num_outputs = 0;
      auto ndoutputs  = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, nullptr);
      *ret            = ndoutputs[0];
    });

MXNET_REGISTER_API("_npx.log_softmax")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      nnvm::NodeAttrs attrs;
      static const nnvm::Op* op = Op::Get("_npx_log_softmax");
      op::SoftmaxParam param    = {};

      int args_size = args.size();
      // inputs
      int num_inputs = args_size - 4;
      std::vector<NDArray*> inputs;
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }

      // parse use_length
      if (args[args_size - 2].type_code() == kNull) {
        param.use_length = false;
      } else {
        param.use_length = args[args_size - 2].operator bool();
      }

      // parse axis
      if (args[args_size - 4].type_code() == kDLInt) {
        param.axis = args[args_size - 4].operator int();
      } else if (args[args_size - 4].type_code() == kDLFloat) {
        param.axis = static_cast<int>(args[args_size - 4].operator double());
      } else {
        param.axis = -1;
      }

      // parse temperature
      if (args[args_size - 3].type_code() == kNull) {
        param.temperature = dmlc::nullopt;
      } else {
        param.temperature = args[args_size - 3].operator double();
      }

      // parse dtype
      if (args[args_size - 1].type_code() == kNull) {
        param.dtype = dmlc::nullopt;
      } else {
        param.dtype = String2MXNetTypeWithBool(args[args_size - 1].operator std::string());
      }

      attrs.parsed = param;
      attrs.op     = op;
      SetAttrDict<op::SoftmaxParam>(&attrs);

      int num_outputs = 0;
      auto ndoutputs  = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, nullptr);
      *ret            = ndoutputs[0];
    });

MXNET_REGISTER_API("_npx.masked_softmax")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      nnvm::NodeAttrs attrs;
      static const nnvm::Op* op    = Op::Get("_npx_masked_softmax");
      op::MaskedSoftmaxParam param = {};

      // inputs
      int num_inputs = 2;
      std::vector<NDArray*> inputs;
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }
      // parse axis
      if (args[2].type_code() == kDLInt) {
        param.axis = args[2].operator int();
      } else if (args[2].type_code() == kDLFloat) {
        param.axis = static_cast<int>(args[2].operator double());
      } else {
        param.axis = -1;
      }
      // parse temperature
      if (args[3].type_code() == kNull) {
        param.temperature = dmlc::nullopt;
      } else {
        param.temperature = args[3].operator double();
      }
      // parse normalize
      if (args[4].type_code() == kNull) {
        param.normalize = true;
      } else {
        param.normalize = args[4].operator bool();
      }

      attrs.parsed = param;
      attrs.op     = op;
      SetAttrDict<op::MaskedSoftmaxParam>(&attrs);

      int num_outputs = 0;
      auto ndoutputs  = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, nullptr);
      *ret            = ndoutputs[0];
    });

MXNET_REGISTER_API("_npx.masked_log_softmax")
    .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
      using namespace runtime;
      nnvm::NodeAttrs attrs;
      static const nnvm::Op* op    = Op::Get("_npx_masked_log_softmax");
      op::MaskedSoftmaxParam param = {};

      // inputs
      int num_inputs = 2;
      std::vector<NDArray*> inputs;
      inputs.reserve(num_inputs);
      for (int i = 0; i < num_inputs; ++i) {
        inputs.push_back(args[i].operator mxnet::NDArray*());
      }
      // parse axis
      if (args[2].type_code() == kDLInt) {
        param.axis = args[2].operator int();
      } else if (args[2].type_code() == kDLFloat) {
        param.axis = static_cast<int>(args[2].operator double());
      } else {
        param.axis = -1;
      }
      // parse temperature
      if (args[3].type_code() == kNull) {
        param.temperature = dmlc::nullopt;
      } else {
        param.temperature = args[3].operator double();
      }
      // parse normalize
      if (args[4].type_code() == kNull) {
        param.normalize = true;
      } else {
        param.normalize = args[4].operator bool();
      }

      attrs.parsed = param;
      attrs.op     = op;
      SetAttrDict<op::MaskedSoftmaxParam>(&attrs);

      int num_outputs = 0;
      auto ndoutputs  = Invoke(op, &attrs, num_inputs, inputs.data(), &num_outputs, nullptr);
      *ret            = ndoutputs[0];
    });

}  // namespace mxnet