/* 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 FUSION_CONVADDRELU_OP #include "operators/kernel/conv_add_relu_kernel.h" namespace paddle_mobile { namespace operators { template <> bool ConvAddReluKernel::Init(FusionConvAddReluParam *param) { bool relu_enabled = true; auto input = const_cast(param->Input()); const Tensor *bias = param->Bias(); auto bias_ptr = bias->data(); auto filter = const_cast(param->Filter()); auto out = param->Output(); PADDLE_MOBILE_ENFORCE(out->dims()[1] == bias->dims()[0], "Output channel should be equal to bias number"); int channel = out->dims()[1]; auto bs_ptr = (float *)fpga::fpga_malloc(2 * channel * sizeof(float)); for (int i = 0; i < channel; i++) { bs_ptr[i + channel] = 1; bs_ptr[i] = bias_ptr[i]; } float max_value = fpga::filter_find_max(filter); fpga::format_filter(filter, max_value, param->Groups()); int element_num_per_div = fpga::get_filter_num_per_div(filter, param->Groups()); fpga::format_bias_scale_array(&bs_ptr, element_num_per_div, channel); fpga::format_fp16_ofm(out); fpga::WrapperConvArgs conv_arg; fpga::fill_conv_arg(&conv_arg, input, out, filter, relu_enabled, param->Groups(), param->Strides()[0], param->Strides()[1], param->Paddings()[0], param->Paddings()[1], bs_ptr); param->SetFpgaArgs(conv_arg); return true; } template <> void ConvAddReluKernel::Compute( const FusionConvAddReluParam ¶m) const { fpga::ComputeFpgaConv(param.FpgaArgs()); } } // namespace operators } // namespace paddle_mobile #endif