wehub-resource-sync
107 lines
4.0 KiB
Plaintext
107 lines
4.0 KiB
Plaintext
/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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 GS <sgazeos@gmail.com>
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//
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#include <array/NDArrayFactory.h>
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#include <ops/declarable/helpers/legacy_helpers.h>
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#include <ops/ops.h>
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#include <system/op_boilerplate.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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template <typename T>
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void reluDerivative__(NDArray* theFirst, NDArray* theSecond) {
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auto functor = LAMBDA_TT(x, y) { return x > (T)0.f ? y : T(0.f); });
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theFirst->applyPairwiseLambda(theSecond, functor,theFirst);
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}
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void reluDerivative(LaunchContext* context, NDArray* theFirst, NDArray* theSecond) {
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BUILD_SINGLE_SELECTOR(theFirst->dataType(), reluDerivative__, (theFirst, theSecond), SD_FLOAT_TYPES);
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}
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template <typename T>
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void reluDerivative_(NDArray* input, NDArray* epsilon, NDArray* output) {
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auto functor = LAMBDA_TT(x, y) { return x > (T)0.f ? y : T(0.f); });
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input->applyPairwiseLambda(epsilon, functor, output);
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}
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void reluDerivative(LaunchContext* context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput) {
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BUILD_SINGLE_SELECTOR(theFirst->dataType(), reluDerivative_, (theFirst, theSecond, theOutput), SD_FLOAT_TYPES);
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}
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template <typename T>
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void relu6Derivative_(NDArray* input, NDArray* epsilon, NDArray* output) {
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auto functor = LAMBDA_TT(x, y) { return x > (T)0.f && x < (T)6.f ? y : T(0.f); });
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input->applyPairwiseLambda(epsilon, functor, output);
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}
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void relu6Derivative(LaunchContext* context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput) {
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BUILD_SINGLE_SELECTOR(theFirst->dataType(), relu6Derivative_, (theFirst, theSecond, theOutput), SD_FLOAT_TYPES);
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}
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template <typename T>
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void leakyReluDerivative_(NDArray* input, NDArray* epsilon, NDArray* output, const float alpha) {
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const T alphaT = static_cast<T>(alpha);
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auto functor = LAMBDA_TT(x, y, alphaT) { return x < 0 ? alphaT * y : y; });
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input->applyPairwiseLambda(epsilon, functor, output);
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}
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void leakyReluDerivative(LaunchContext* context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput,
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const float alpha) {
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BUILD_SINGLE_SELECTOR(theFirst->dataType(), leakyReluDerivative_, (theFirst, theSecond, theOutput, alpha),
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SD_FLOAT_TYPES);
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}
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template <typename T>
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void eluDerivative_(NDArray* input, NDArray* epsilon, NDArray* output, const float alpha) {
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const T alphaT = static_cast<T>(alpha);
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auto functor = LAMBDA_TT(x, y, alphaT) { return y * math::sd_eluderivative<T, T>(x, alphaT); });
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input->applyPairwiseLambda(epsilon, functor, output);
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}
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void eluDerivative(LaunchContext* context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput,
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const float alpha) {
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BUILD_SINGLE_SELECTOR(theFirst->dataType(), eluDerivative_, (theFirst, theSecond, theOutput, alpha), SD_FLOAT_TYPES);
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}
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template <typename T>
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void seluDerivative_(NDArray* input, NDArray* epsilon, NDArray* output) {
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auto functor = LAMBDA_TT(x, y) { return y * simdOps::SELUDerivative<T>::op(x, nullptr); });
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input->applyPairwiseLambda(epsilon, functor, output);
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}
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void seluDerivative(LaunchContext* context, NDArray* theFirst, NDArray* theSecond, NDArray* theOutput) {
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BUILD_SINGLE_SELECTOR(theFirst->dataType(), seluDerivative_, (theFirst, theSecond, theOutput), SD_FLOAT_TYPES);
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}
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} // namespace helpers
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} // namespace ops
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} // namespace sd
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