cavis/libnd4j/include/ops/declarable/helpers/legacy_helpers.h

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/*******************************************************************************
* 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
******************************************************************************/
//
// @author sgazeos@gmail.com
//
#ifndef __H_LEGACY_HELPERS__
#define __H_LEGACY_HELPERS__
#include <NDArray.h>
namespace nd4j {
namespace ops {
namespace helpers {
/*
FORCEINLINE void reluDerivative(NDArray* theFirst, NDArray const* theSecond);
FORCEINLINE void reluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void relu6Derivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void leakyReluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void eluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void seluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void cubeDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void reduceNorm1(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void sxeLossWithLogits(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void tanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void hardTanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void rationalTanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void rectifiedTanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void softSignDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void softPlusDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void sigmoidDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
FORCEINLINE void hardSigmoidDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
*/
void reluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond);
void reluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void relu6Derivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void leakyReluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void eluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void seluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void cubeDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void reduceNorm1(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void sigmCrossEntropy(nd4j::LaunchContext * context, NDArray* logits, NDArray* lablels, NDArray* theOutput);
void sigmCrossEntropyGrad(nd4j::LaunchContext * context, NDArray* logits, NDArray* lablels, NDArray* theOutput);
void tanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void hardTanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void rationalTanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void rectifiedTanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void softSignDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void softPlusDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void sigmoidDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void hardSigmoidDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
void logSumExp(nd4j::LaunchContext * context, NDArray* input, NDArray* axis, NDArray* output);
void logSumExp(nd4j::LaunchContext * context, NDArray* input, NDArray* subtrah, NDArray* axis, NDArray* output);
void weightedCrossEntropyWithLogitsFunctor(nd4j::LaunchContext * context, NDArray const* targets, NDArray const* input, NDArray const* weights, NDArray* output);
}
}
}
#endif