70 lines
4.8 KiB
C
70 lines
4.8 KiB
C
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author sgazeos@gmail.com
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//
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#ifndef __H_LEGACY_HELPERS__
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#define __H_LEGACY_HELPERS__
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#include <NDArray.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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/*
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FORCEINLINE void reluDerivative(NDArray* theFirst, NDArray const* theSecond);
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FORCEINLINE void reluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void relu6Derivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void leakyReluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void eluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void seluDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void cubeDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void reduceNorm1(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void sxeLossWithLogits(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void tanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void hardTanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void rationalTanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void rectifiedTanhDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void softSignDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void softPlusDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void sigmoidDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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FORCEINLINE void hardSigmoidDerivative(NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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*/
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void reluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond);
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void reluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void relu6Derivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void leakyReluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void eluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void seluDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void cubeDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void reduceNorm1(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void sigmCrossEntropy(nd4j::LaunchContext * context, NDArray* logits, NDArray* lablels, NDArray* theOutput);
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void sigmCrossEntropyGrad(nd4j::LaunchContext * context, NDArray* logits, NDArray* lablels, NDArray* theOutput);
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void tanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void hardTanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void rationalTanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void rectifiedTanhDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void softSignDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void softPlusDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void sigmoidDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void hardSigmoidDerivative(nd4j::LaunchContext * context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput);
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void logSumExp(nd4j::LaunchContext * context, NDArray* input, NDArray* axis, NDArray* output);
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void logSumExp(nd4j::LaunchContext * context, NDArray* input, NDArray* subtrah, NDArray* axis, NDArray* output);
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}
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}
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}
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#endif
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