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56 lines
1.7 KiB
56 lines
1.7 KiB
9 years ago
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/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve.
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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 "paddle/utils/Util.h"
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#include "GruCompute.h"
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#include "hl_recurrent_apply.cuh"
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namespace paddle {
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void GruCompute::init(LayerConfig &config) {
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activeNode_ = hlActiveType(config.active_type());
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activeGate_ = hlActiveType(config.active_gate_type());
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}
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template <>
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void GruCompute::forward<0>(hl_gru_value value,
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int frameSize,
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int batchSize) {
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hl_cpu_gru_forward(hppl::forward::gru_resetOutput(),
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hppl::forward::gru_finalOutput(),
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value,
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frameSize,
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batchSize,
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activeNode_,
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activeGate_);
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}
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template <>
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void GruCompute::backward<0>(hl_gru_value value,
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hl_gru_grad grad,
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int frameSize,
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int batchSize) {
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hl_cpu_gru_backward(hppl::backward::gru_stateGrad(),
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hppl::backward::gru_resetGrad(),
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value,
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grad,
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frameSize,
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batchSize,
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activeNode_,
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activeGate_);
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}
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} // namespace paddle
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