cavis/libnd4j/include/ops/declarable/generic/parity_ops/dropout.cpp

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2019-06-06 14:21:15 +02:00
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// Created by GS <sgazeos@gmail.com>
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_dropout)
#include <ops/declarable/headers/parity_ops.h>
#include <ops/declarable/helpers/dropout.h>
namespace nd4j {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CONFIGURABLE_OP_IMPL(dropout, 1, 1, true, 1, 1) {
auto input = INPUT_VARIABLE(0); // lookup param
NDArray *reduceShape = nullptr; // this param is optional
auto output = OUTPUT_VARIABLE(0); //
int seed = INT_ARG(0);
// FIXME: float?
double probValue = T_ARG(0);
if (block.width() > 1)
reduceShape = INPUT_VARIABLE(1);
REQUIRE_TRUE(probValue > 0.f && probValue <= 1.f, 0, "dropout: Probability should be with range 0 to 1.");
if (probValue == 1.0) {
*output = *input;
return Status::OK();
}
return helpers::dropOutFunctor(block, input, output, reduceShape, seed, probValue);
}
DECLARE_TYPES(dropout) {
getOpDescriptor()
->setAllowedInputTypes(0, {ALL_FLOATS})
->setAllowedInputTypes(1, {ALL_INTS})
->setAllowedOutputTypes({ALL_FLOATS})
->setSameMode(true);
}
//////////////////////////////////////////////////////////////////////////
CONFIGURABLE_OP_IMPL(dropout_bp, 2, 1, false, 1, 1) {
NDArray* input = INPUT_VARIABLE(0); // lookup param
NDArray* gradOut = INPUT_VARIABLE(1); // lookup param
NDArray* reduceShape = nullptr; // this param is optional
NDArray* output = OUTPUT_VARIABLE(0); //
int seed = INT_ARG(0);
double probValue = T_ARG(0);
if (block.width() > 2)
reduceShape = INPUT_VARIABLE(2);
REQUIRE_TRUE((probValue > 0. && probValue <= 1.), 0, "dropout_bp: Probability should be with range 0 to 1.");
if (probValue == 1.0) {
output->assign(0.f); // fill up output with 0
return ND4J_STATUS_OK;
}
REQUIRE_TRUE(helpers::dropOutFunctorBP(block, input, gradOut, output, reduceShape, seed, probValue) == ND4J_STATUS_OK, 0, "dropout_bp: Cannot backprop dropout." );
return ND4J_STATUS_OK;
}
DECLARE_TYPES(dropout_bp) {
getOpDescriptor()
->setAllowedInputTypes({ALL_FLOATS, ALL_INTS})
->setAllowedOutputTypes({ALL_FLOATS});
}
//////////////////////////////////////////////////////////////////////////
CONFIGURABLE_OP_IMPL(alpha_dropout_bp, 2, 1, false, 4, 1) {
NDArray* input = INPUT_VARIABLE(0); // lookup param
NDArray* gradOut = INPUT_VARIABLE(1); // lookup param
NDArray* reduceShape = nullptr; // this param is optional
NDArray* output = OUTPUT_VARIABLE(0); //
if (block.width() > 2)
reduceShape = INPUT_VARIABLE(2);
int seed = INT_ARG(0);
double probValue = T_ARG(0);
double alphaValue = T_ARG(0);
double alpha1Value = T_ARG(2);
double betaValue = T_ARG(3);
REQUIRE_TRUE(probValue > 0. && probValue <= 1., 0, "dropout_bp: Probability should be with range 0 to 1.");
if (probValue == 1.0) {
output->assign(0.); // fill up output with 0
return ND4J_STATUS_OK;
}
return helpers::alphaDropOutFunctorBP(block, input, gradOut, output, reduceShape, seed, probValue, alphaValue, alpha1Value, betaValue);
}
DECLARE_TYPES(alpha_dropout_bp) {
getOpDescriptor()
->setAllowedInputTypes({ALL_FLOATS})
->setSameMode(true);
}
}
}
#endif