/******************************************************************************* * 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 Yurii Shyrma, created on 16.02.2018 // #include #if NOT_EXCLUDED(OP_relu6) #include #include namespace nd4j { namespace ops { //////////////////////////////////////////////////////////////////////// CONFIGURABLE_OP_IMPL(relu6, 1, 1, true, 1, 0) { auto input = INPUT_VARIABLE(0); auto output = OUTPUT_VARIABLE(0); input->applyScalar(nd4j::scalar::RELU6, T_ARG(0), output); return Status::OK(); } DECLARE_TYPES(relu6) { getOpDescriptor() ->setAllowedInputTypes(0, DataType::ANY) ->setSameMode(true); } //////////////////////////////////////////////////////////////////////// CONFIGURABLE_OP_IMPL(relu6_bp, 2, 1, true, 0, 0) { auto input = INPUT_VARIABLE(0); auto gradO = INPUT_VARIABLE(1); auto gradI = OUTPUT_VARIABLE(0); //input->applyPairwiseTransform(pairwise::RELU6DerivativeE, gradO, gradI, nullptr); helpers::relu6Derivative(block.launchContext(), input, gradO, gradI); return Status::OK(); } DECLARE_TYPES(relu6_bp) { getOpDescriptor() ->setAllowedInputTypes(0, DataType::ANY) ->setAllowedInputTypes(1, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF}) ->setAllowedOutputTypes(0, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF}); } } } #endif