81 lines
2.9 KiB
C++
81 lines
2.9 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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// @author raver119 on 29/10/17
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// @author GS <sgazeos@gmail.com> 2/16/18
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// @author Yurii Shyrma (iuriish@yahoo.com) -> back prop author
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//
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_lrn)
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#include <ops/declarable/helpers/lrn.h>
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#include <ops/declarable/CustomOperations.h>
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namespace nd4j {
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namespace ops {
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DECLARE_TYPES(lrn) {
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getOpDescriptor()
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->setAllowedInputTypes(nd4j::DataType::ANY)
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->setAllowedOutputTypes({ALL_FLOATS});
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}
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CONFIGURABLE_OP_IMPL(lrn, 1, 1, true, 3, 1) {
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auto input = INPUT_VARIABLE(0);
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auto output = OUTPUT_VARIABLE(0);
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REQUIRE_TRUE(input->rankOf() == 4, 0, "lrn: Input rank of 4 expected, but got %i instead", input->rankOf());
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double alpha = T_ARG(1);
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double beta = T_ARG(2);
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double bias = T_ARG(0);
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int depth = INT_ARG(0);
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return helpers::lrnFunctor(block, input, output, depth, bias, alpha, beta);
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}
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DECLARE_TYPES(lrn_bp) {
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getOpDescriptor()
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->setAllowedInputTypes(nd4j::DataType::ANY)
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->setAllowedOutputTypes({ALL_FLOATS});
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}
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CONFIGURABLE_OP_IMPL(lrn_bp, 2, 1, true, 3, 1) {
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auto input = INPUT_VARIABLE(0);
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auto gradO = INPUT_VARIABLE(1);
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auto gradI = OUTPUT_VARIABLE(0);
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REQUIRE_TRUE(input->rankOf() == 4, 0, "lrn_bp: Input rank of 4 expected, but got %i instead", input->rankOf());
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REQUIRE_TRUE(input->isSameShape(gradO), 0, "lrn_bp: Both input and grad_output should have the same shape, but got %s and %s correspondingly !", ShapeUtils::shapeAsString(input).c_str(), ShapeUtils::shapeAsString(gradO).c_str());
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// FIXME: double/float?
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float bias = T_ARG(0);
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float alpha = T_ARG(1);
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float beta = T_ARG(2);
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int depth = INT_ARG(0);
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helpers::lrnBP(block, *input, *gradO, *gradI, depth, bias, alpha, beta);
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return Status::OK();
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}
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DECLARE_SYN(local_response_normalization, lrn);
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}
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}
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#endif |