src/operator/rnn.cc

/*!
 * Copyright (c) 2015 by Contributors
 * \file rnn.cc
 * \brief
 * \author Sebastian Bodenstein
*/

#include "./rnn-inl.h"

namespace mxnet {
namespace op {
template<>
Operator *CreateOp<cpu>(RNNParam param, int dtype) {
  LOG(FATAL) << "RNN is only available for gpu at the moment.";
  Operator *op = NULL;
  MSHADOW_REAL_TYPE_SWITCH(dtype, DType, {
    op = new RNNOp<cpu, DType>(param);
  });
  return op;
}

Operator *RNNProp::CreateOperatorEx(Context ctx,
                                  std::vector<TShape> *in_shape,
                                  std::vector<int> *in_type) const {
  std::vector<TShape> out_shape, aux_shape;
  std::vector<int> out_type, aux_type;
  CHECK(InferType(in_type, &out_type, &aux_type));
  CHECK(InferShape(in_shape, &out_shape, &aux_shape));
  DO_BIND_DISPATCH(CreateOp, param_, (*in_type)[0]);
}

DMLC_REGISTER_PARAMETER(RNNParam);

MXNET_REGISTER_OP_PROPERTY(RNN, RNNProp)
.describe("Applies a recurrent layer to input.")
.add_argument("data", "NDArray-or-Symbol", "Input data to RNN")
.add_argument("parameters", "NDArray-or-Symbol",
              "Vector of all RNN trainable parameters concatenated")
.add_argument("state", "NDArray-or-Symbol", "initial hidden state of the RNN")
.add_argument("state_cell", "NDArray-or-Symbol",
              "initial cell state for LSTM networks (only for LSTM)")
.add_arguments(RNNParam::__FIELDS__());
}  // namespace op
}  // namespace mxnet