// Copyright (c) 2019 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. #include "lite/kernels/cuda/conv_compute.h" #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace cuda { void ConvCompute::PrepareForRun() { auto& param = this->Param(); auto& ctx = this->ctx_->template As(); conv_impl_.reset(new lite::cuda::math::CudnnConv2D); conv_impl_->init(param, &ctx); } void ConvCompute::Run() { auto& param = this->Param(); conv_impl_->run(param); } template void ConvComputeInt8::PrepareForRun() { auto& param = this->Param(); auto& ctx = this->ctx_->template As(); conv_impl_.reset(new lite::cuda::math::CudnnConv2DInt8); conv_impl_->init(param, &ctx); } template void ConvComputeInt8::Run() { auto& param = this->Param(); conv_impl_->run(param); } template class ConvComputeInt8; template class ConvComputeInt8; } // namespace cuda } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL( conv2d, kCUDA, kFloat, kNCHW, paddle::lite::kernels::cuda::ConvCompute, def) .BindInput("Input", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kFloat), DATALAYOUT(kNCHW))}) .BindInput("Bias", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kFloat))}) .BindInput("Filter", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kFloat), DATALAYOUT(kNCHW))}) .BindOutput("Output", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kFloat), DATALAYOUT(kNCHW))}) .Finalize(); REGISTER_LITE_KERNEL( conv2d, kCUDA, kInt8, kNHWC, paddle::lite::kernels::cuda::ConvComputeInt8, fp32_out) .BindInput("Input", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kInt8), DATALAYOUT(kNHWC))}) .BindInput("Bias", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kFloat))}) .BindInput("Filter", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kInt8), DATALAYOUT(kNHWC))}) .BindOutput("Output", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kFloat), DATALAYOUT(kNHWC))}) .Finalize(); REGISTER_LITE_KERNEL( conv2d, kCUDA, kInt8, kNHWC, paddle::lite::kernels::cuda::ConvComputeInt8, int8_out) .BindInput("Input", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kInt8), DATALAYOUT(kNHWC))}) .BindInput("Bias", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kFloat))}) .BindInput("Filter", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kInt8), DATALAYOUT(kNHWC))}) .BindOutput("Output", {LiteType::GetTensorTy(TARGET(kCUDA), PRECISION(kInt8), DATALAYOUT(kNHWC))}) .Finalize();