52 lines
1.5 KiB
52 lines
1.5 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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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,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "TableProjection.h"
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namespace paddle {
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REGISTER_PROJECTION(table, TableProjection);
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TableProjection::TableProjection(const ProjectionConfig& config,
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const ParameterPtr& parameter,
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bool useGpu)
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: Projection(config, parameter, useGpu) {
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table_.reset(
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new Weight(config.input_size(), config.output_size(), parameter));
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}
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void TableProjection::prefetch(const Argument* in) {
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CHECK(in->ids);
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auto* sparseParam =
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dynamic_cast<SparsePrefetchRowCpuMatrix*>(table_->getW().get());
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if (sparseParam) {
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sparseParam->addRows(in->ids);
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}
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}
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void TableProjection::forward() {
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CHECK(in_->ids);
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out_->value->selectRows(*table_->getW(), *in_->ids);
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}
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void TableProjection::backward(const UpdateCallback& callback) {
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if (table_->getWGrad()) {
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CHECK(in_->ids);
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out_->grad->addToRows(*table_->getWGrad(), *in_->ids);
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parameter_->incUpdate(callback);
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}
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}
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} // namespace paddle
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