/******************************************************************************* * 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 // #include #if NOT_EXCLUDED(OP_dropout) #include #include 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