// 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 #include #include "lite/backends/opencl/cl_half.h" #include "lite/backends/opencl/cl_image_converter.h" #include "lite/backends/opencl/cl_include.h" #include "lite/core/kernel.h" #include "lite/core/op_registry.h" #include "lite/kernels/opencl/image_helper.h" #include "lite/operators/op_params.h" #include "lite/utils/logging.h" #include "lite/utils/replace_stl/stream.h" namespace paddle { namespace lite { namespace kernels { namespace opencl { class Pad2dCompute : public KernelLite { public: using param_t = operators::Pad2dParam; std::string doc() const override { return "Pad2d using cl::Image2D(ImageDefault/RGBA), kFP16"; } void PrepareForRun() override { pad2d_param_ = param_.get_mutable(); if (pad2d_param_->mode == "constant") { kernel_func_name_ = "pad2d_constant"; } else if (pad2d_param_->mode == "reflect") { kernel_func_name_ = "pad2d_reflect"; } else if (pad2d_param_->mode == "edge") { kernel_func_name_ = "pad2d_edge"; } else { LOG(FATAL) << "Unknown mode type"; } auto& context = ctx_->As(); context.cl_context()->AddKernel( kernel_func_name_, "image/pad2d_kernel.cl", build_options_); VLOG(1) << "kernel_func_name_:" << kernel_func_name_; } void Run() override { auto& context = ctx_->As(); CHECK(context.cl_context() != nullptr); auto* x = pad2d_param_->X; auto* out = pad2d_param_->Out; auto out_dims = out->dims(); auto in_dims = x->dims(); int in_h = in_dims[2]; int in_w = in_dims[3]; int out_h = out_dims[2]; int out_w = out_dims[3]; VLOG(4) << "x->target():" << TargetToStr(x->target()); VLOG(4) << "out->target():" << TargetToStr(out->target()); VLOG(4) << "x->dims():" << in_dims; VLOG(4) << "out->dims():" << out_dims; auto out_image_shape = InitImageDimInfoWith(out_dims); auto* x_img = x->data(); auto* out_img = out->mutable_data( out_image_shape["width"], out_image_shape["height"]); VLOG(4) << "out_image_shape[w,h]: " << out_image_shape["width"] << " " << out_image_shape["height"]; VLOG(4) << "in_h: " << in_h << ", in_w: " << in_w; VLOG(4) << "out_h: " << out_h << ", out_w: " << out_w; STL::stringstream kernel_key; kernel_key << kernel_func_name_ << build_options_; auto kernel = context.cl_context()->GetKernel(kernel_key.str()); int arg_idx = 0; auto default_work_size = DefaultWorkSize(out_dims, DDim(std::vector{ static_cast(out_image_shape["width"]), static_cast(out_image_shape["height"])})); VLOG(4) << "default_work_size: " << default_work_size[0] << ", " << default_work_size[1] << ", " << default_work_size[2]; int pad_h0 = pad2d_param_->paddings[0]; int pad_h1 = pad2d_param_->paddings[1]; int pad_w0 = pad2d_param_->paddings[2]; int pad_w1 = pad2d_param_->paddings[3]; float pad_value = pad2d_param_->pad_value; cl_int status = kernel.setArg(arg_idx++, *x_img); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, *out_img); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, in_h); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, in_w); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, out_h); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, out_w); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, pad_h0); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, pad_h1); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, pad_w0); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, pad_w1); CL_CHECK_FATAL(status); status = kernel.setArg(arg_idx++, pad_value); CL_CHECK_FATAL(status); auto global_work_size = cl::NDRange{static_cast(default_work_size[0]), static_cast(default_work_size[1]), static_cast(default_work_size[2])}; status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel( kernel, cl::NullRange, global_work_size, cl::NullRange, nullptr, event_.get()); CL_CHECK_FATAL(status); context.cl_wait_list()->emplace(out_img, event_); VLOG(4) << "global_work_size:[2D]:" << global_work_size[0] << " " << global_work_size[1] << " " << global_work_size[2]; } protected: param_t* pad2d_param_{nullptr}; std::string kernel_func_name_{}; std::string build_options_{"-DCL_DTYPE_half"}; std::shared_ptr event_{new cl::Event}; }; } // namespace opencl } // namespace kernels } // namespace lite } // namespace paddle namespace ocl = paddle::lite::kernels::opencl; REGISTER_LITE_KERNEL( pad2d, kOpenCL, kFP16, kImageDefault, ocl::Pad2dCompute, ImageDefault) .BindInput("X", {LiteType::GetTensorTy(TARGET(kOpenCL), PRECISION(kFP16), DATALAYOUT(kImageDefault))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kOpenCL), PRECISION(kFP16), DATALAYOUT(kImageDefault))}) .Finalize();