wehub-resource-sync
111 lines
3.3 KiB
C++
111 lines
3.3 KiB
C++
/* ******************************************************************************
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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 raver119@gmail.com
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//
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#include <system/op_boilerplate.h>
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#if NOT_EXCLUDED(OP_crelu)
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/legacy_helpers.h>
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#include <ops/declarable/helpers/transforms.h>
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namespace sd {
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namespace ops {
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CUSTOM_OP_IMPL(crelu, 1, 1, false, 0, 0) {
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auto x = INPUT_VARIABLE(0);
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REQUIRE_TRUE(x->isR(), 0, "CRELU: input must be real type");
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auto tmp = x->dup(x->ordering());
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tmp->applyTransform(transform::Neg, tmp);
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auto z = OUTPUT_VARIABLE(0);
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helpers::concat(block.launchContext(), {x, tmp}, *z, x->rankOf() - 1);
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// TODO: make this configurable?
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double threshold = 0.0;
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z->applyScalar(scalar::RELU, threshold, z);
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STORE_RESULT(z);
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delete tmp;
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return Status::OK;
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}
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DECLARE_TYPES(crelu) { getOpDescriptor()->setAllowedInputTypes(0, ANY)->setSameMode(true); }
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DECLARE_SHAPE_FN(crelu) {
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auto inShape = inputShape->at(0);
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std::vector<LongType> shape;
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for (int e = 0; e < shape::rank(inShape); e++) shape.emplace_back(shape::shapeOf(inShape)[e]);
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shape[shape.size() - 1] *= 2;
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auto newShape =
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ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShape), shape::order(inShape), shape);
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return SHAPELIST(newShape);
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}
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CUSTOM_OP_IMPL(crelu_bp, 2, 1, false, 0, 0) {
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auto input = INPUT_VARIABLE(0);
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auto epsilonNext = INPUT_VARIABLE(1);
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auto epsilon = OUTPUT_VARIABLE(0);
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// at first step we build fwd activation
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crelu op;
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auto tmpResult = op.evaluate({input});
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if (tmpResult.status() != Status::OK) return tmpResult.status();
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auto actv = tmpResult.at(0);
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// now we do RELU backward pass
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helpers::reluDerivative(block.launchContext(), actv, epsilonNext);
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// now we split updated array into 2 chunks along last dimension
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concat_bp opc;
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auto dec = opc.evaluate({input, input, actv}, {-1});
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if (dec.status() != Status::OK) return dec.status();
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// and now we subtract two parts of epsilons and pass result out
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auto pos = dec.at(0);
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auto neg = dec.at(1);
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pos->applyPairwiseTransform(pairwise::Subtract, neg, epsilon);
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return Status::OK;
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}
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DECLARE_TYPES(crelu_bp) {
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getOpDescriptor()
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->setAllowedInputTypes(0, ANY)
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->setAllowedInputTypes(1, {FLOAT32, DOUBLE, HALF})
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->setAllowedOutputTypes(0, {FLOAT32, DOUBLE, HALF});
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}
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DECLARE_SHAPE_FN(crelu_bp) {
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auto inShape = inputShape->at(0);
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auto ret = SHAPELIST(ConstantShapeHelper::getInstance().bufferForShapeInfo(inShape)->primary());
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return ret;
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}
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} // namespace ops
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} // namespace sd
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#endif
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