blob: 78c74f905f41c7184d0fe6fe6fe348341eb765bb [file] [log] [blame]
/*!
* Copyright (c) 2015 by Contributors
* \file dropout.cc
* \brief
* \author Bing Xu
*/
#include "./dropout-inl.h"
namespace mxnet {
namespace op {
template<>
Operator *CreateOp<cpu>(DropoutParam param, int dtype) {
Operator *op = NULL;
MSHADOW_REAL_TYPE_SWITCH(dtype, DType, {
op = new DropoutOp<cpu, DType>(param);
});
return op;
}
// DO_BIND_DISPATCH comes from operator_common.h
Operator *DropoutProp::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->at(0));
}
DMLC_REGISTER_PARAMETER(DropoutParam);
MXNET_REGISTER_OP_PROPERTY(Dropout, DropoutProp)
.describe(R"(Apply dropout to input.
During training, each element of the input is randomly set to zero with probability p.
And then the whole tensor is rescaled by 1/(1-p) to keep the expectation the same as
before applying dropout. During the test time, this behaves as an identity map.
)")
.add_argument("data", "Symbol", "Input data to dropout.")
.add_arguments(DropoutParam::__FIELDS__());
} // namespace op
} // namespace mxnet