128 lines
4.2 KiB
C++
128 lines
4.2 KiB
C++
/*******************************************************************************
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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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// Created by GS <sgazeos@gmail.com>
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//
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_dropout)
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#include <ops/declarable/headers/parity_ops.h>
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#include <ops/declarable/helpers/dropout.h>
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namespace nd4j {
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namespace ops {
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//////////////////////////////////////////////////////////////////////////
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CONFIGURABLE_OP_IMPL(dropout, 1, 1, true, 1, 1) {
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auto input = INPUT_VARIABLE(0); // lookup param
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NDArray *reduceShape = nullptr; // this param is optional
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auto output = OUTPUT_VARIABLE(0); //
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int seed = INT_ARG(0);
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// FIXME: float?
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double probValue = T_ARG(0);
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if (block.width() > 1)
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reduceShape = INPUT_VARIABLE(1);
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REQUIRE_TRUE(probValue > 0.f && probValue <= 1.f, 0, "dropout: Probability should be with range 0 to 1.");
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if (probValue == 1.0) {
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*output = *input;
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return Status::OK();
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}
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return helpers::dropOutFunctor(block, input, output, reduceShape, seed, probValue);
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}
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DECLARE_TYPES(dropout) {
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getOpDescriptor()
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->setAllowedInputTypes(0, {ALL_FLOATS})
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->setAllowedInputTypes(1, {ALL_INTS})
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->setAllowedOutputTypes({ALL_FLOATS})
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->setSameMode(true);
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}
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//////////////////////////////////////////////////////////////////////////
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CONFIGURABLE_OP_IMPL(dropout_bp, 2, 1, false, 1, 1) {
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NDArray* input = INPUT_VARIABLE(0); // lookup param
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NDArray* gradOut = INPUT_VARIABLE(1); // lookup param
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NDArray* reduceShape = nullptr; // this param is optional
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NDArray* output = OUTPUT_VARIABLE(0); //
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int seed = INT_ARG(0);
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double probValue = T_ARG(0);
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if (block.width() > 2)
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reduceShape = INPUT_VARIABLE(2);
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REQUIRE_TRUE((probValue > 0. && probValue <= 1.), 0, "dropout_bp: Probability should be with range 0 to 1.");
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if (probValue == 1.0) {
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output->assign(0.f); // fill up output with 0
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return ND4J_STATUS_OK;
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}
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REQUIRE_TRUE(helpers::dropOutFunctorBP(block, input, gradOut, output, reduceShape, seed, probValue) == ND4J_STATUS_OK, 0, "dropout_bp: Cannot backprop dropout." );
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return ND4J_STATUS_OK;
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}
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DECLARE_TYPES(dropout_bp) {
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getOpDescriptor()
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->setAllowedInputTypes({ALL_FLOATS, ALL_INTS})
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->setAllowedOutputTypes({ALL_FLOATS});
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}
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//////////////////////////////////////////////////////////////////////////
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CONFIGURABLE_OP_IMPL(alpha_dropout_bp, 2, 1, false, 4, 1) {
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NDArray* input = INPUT_VARIABLE(0); // lookup param
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NDArray* gradOut = INPUT_VARIABLE(1); // lookup param
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NDArray* reduceShape = nullptr; // this param is optional
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NDArray* output = OUTPUT_VARIABLE(0); //
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if (block.width() > 2)
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reduceShape = INPUT_VARIABLE(2);
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int seed = INT_ARG(0);
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double probValue = T_ARG(0);
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double alphaValue = T_ARG(0);
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double alpha1Value = T_ARG(2);
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double betaValue = T_ARG(3);
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REQUIRE_TRUE(probValue > 0. && probValue <= 1., 0, "dropout_bp: Probability should be with range 0 to 1.");
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if (probValue == 1.0) {
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output->assign(0.); // fill up output with 0
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return ND4J_STATUS_OK;
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}
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return helpers::alphaDropOutFunctorBP(block, input, gradOut, output, reduceShape, seed, probValue, alphaValue, alpha1Value, betaValue);
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}
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DECLARE_TYPES(alpha_dropout_bp) {
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getOpDescriptor()
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->setAllowedInputTypes({ALL_FLOATS})
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->setSameMode(true);
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}
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}
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}
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#endif |