/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #ifdef GRU_UNIT_OP #pragma once #include #include "operators/math/math_function.h" #include "operators/kernel/activation_kernel.h" #include "operators/math/gemm.h" #include "operators/op_param.h" namespace paddle_mobile { namespace operators { template void GruUnitCompute(const GruUnitParam& param) { auto* input = param.InputInput(); auto* hidden_prev = param.InputHiddenPrev(); auto* weight = param.InputWeight(); auto* bias = param.InputBias(); auto* gate = param.OutGate(); auto* reset_hidden_prev = param.OutResetHiddenPrev(); auto* hidden = param.OutHidden(); if (bias) { math::RowwiseAdd add_bias; add_bias(*gate, *bias, gate); } int batch_size = input->dims()[0]; int frame_size = hidden_prev->dims()[1]; const P* weight_data = weight->data

(); math::GRUMetaValue

gru_value; gru_value.gate_weight = const_cast(weight_data); gru_value.state_weight = const_cast(weight_data + 2 * frame_size * frame_size); gru_value.output_value = hidden->data

(); gru_value.prev_out_value = gru_value.output_value; gru_value.gate_value = gate->data

(); gru_value.reset_output_value = reset_hidden_prev->data

(); auto active_node = math::GetActivationType(param.Activation()); auto active_gate = math::GetActivationType(param.GateActivation()); math::GRUUnitFunctor::compute(gru_value, frame_size, batch_size, active_node, active_gate); } } // namespace operators } // namespace paddle_mobile #endif