// Copyright (c) 2019 PsublePsuble 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/opencl/elementwise_sub_image_compute.h" #include #include "lite/backends/opencl/cl_include.h" #include "lite/core/op_registry.h" #include "lite/utils/replace_stl/stream.h" namespace paddle { namespace lite { namespace kernels { namespace opencl { void ElementwiseSubImageCompute::PrepareForRun() { ele_param_ = param_.get_mutable(); auto* x = ele_param_->X; auto* y = ele_param_->Y; auto axis = ele_param_->axis; if (y->dims().size() == 4) { kernel_func_name_ = "elementwise_sub"; // y: ImageDefault } else if (y->dims().size() == 1) { if (axis == x->dims().size() - 1) { kernel_func_name_ = "width_sub"; // y: ImageDefault } else if (axis == x->dims().size() - 3) { kernel_func_name_ = "channel_sub"; // y: ImageFolder } else { LOG(FATAL) << "ElementwiseSubImage doesn't support axis:" << axis << ", x->dims().size():" << x->dims().size() << ", y->dims.size():" << y->dims().size(); } } else { LOG(FATAL) << "ElementwiseSubImage doesn't support axis:" << axis << ", x->dims().size():" << x->dims().size() << ", y->dims.size():" << y->dims().size(); } VLOG(1) << "kernel_func_name_:" << kernel_func_name_; auto& context = ctx_->As(); context.cl_context()->AddKernel(kernel_func_name_, "image/elementwise_sub_kernel.cl", build_options_, time_stamp_); } void ElementwiseSubImageCompute::Run() { auto& context = ctx_->As(); CHECK(context.cl_context() != nullptr); auto* x = ele_param_->X; auto* y = ele_param_->Y; auto* out = ele_param_->Out; auto axis = ele_param_->axis; #ifndef LITE_SHUTDOWN_LOG VLOG(4) << "x->target():" << TargetToStr(x->target()); VLOG(4) << "y->target():" << TargetToStr(y->target()); VLOG(4) << "out->target():" << TargetToStr(out->target()); VLOG(4) << "x->dims():" << x->dims(); VLOG(4) << "y->dims():" << y->dims(); VLOG(4) << "out->dims():" << out->dims(); VLOG(4) << "axis:" << axis; #endif paddle::lite::CLImageConverterDefault default_convertor; auto x_img_shape = default_convertor.InitImageDimInfoWith(x->dims()); // w, h auto x_img_width = x_img_shape[0]; auto x_img_height = x_img_shape[1]; auto out_img_shape = default_convertor.InitImageDimInfoWith(out->dims()); // w, h auto y_img_shape = default_convertor.InitImageDimInfoWith(y->dims()); auto* x_img = x->data(); auto* y_img = y->data(); auto* out_img = out->mutable_data(out_img_shape[0], out_img_shape[1]); #ifndef LITE_SHUTDOWN_LOG VLOG(4) << "x_img_shape[w,h]:" << x_img_width << " " << x_img_height; VLOG(4) << "y_img_shape[w,h]:" << y_img_shape[0] << " " << y_img_shape[1]; VLOG(4) << "out_img_shape[w,h]:" << out_img_shape[0] << " " << out_img_shape[1]; #endif STL::stringstream kernel_key; kernel_key << kernel_func_name_ << build_options_ << time_stamp_; auto kernel = context.cl_context()->GetKernel(kernel_key.str()); int arg_idx = 0; auto y_dims = y->dims(); if (y_dims.size() == 4) { cl_int status = kernel.setArg(arg_idx, *x_img); CL_CHECK_FATAL(status); status = kernel.setArg(++arg_idx, *y_img); CL_CHECK_FATAL(status); status = kernel.setArg(++arg_idx, *out_img); CL_CHECK_FATAL(status); } else if (y_dims.size() == 1) { if (axis == x->dims().size() - 1 || axis == x->dims().size() - 3) { int tensor_w = x->dims()[x->dims().size() - 1]; #ifndef LITE_SHUTDOWN_LOG VLOG(4) << "tensor_w:" << tensor_w; #endif cl_int status = kernel.setArg(arg_idx, *x_img); CL_CHECK_FATAL(status); status = kernel.setArg(++arg_idx, *y_img); CL_CHECK_FATAL(status); status = kernel.setArg(++arg_idx, *out_img); CL_CHECK_FATAL(status); status = kernel.setArg(++arg_idx, static_cast(tensor_w)); CL_CHECK_FATAL(status); } else { LOG(FATAL) << "ElementwiseSubImage doesn't support axis:" << axis << ", x->dims().size():" << x->dims().size() << ", y->dims.size():" << y->dims().size(); } } else { LOG(FATAL) << "ElementwiseSubImage doesn't support axis:" << axis << ", x->dims().size():" << x->dims().size() << ", y->dims.size():" << y->dims().size(); } auto global_work_size = cl::NDRange{static_cast(x_img_width), static_cast(x_img_height)}; #ifndef LITE_SHUTDOWN_LOG VLOG(4) << "global_work_size:[2D]:" << x_img_width << " " << x_img_height; #endif event_ = std::shared_ptr(new cl::Event); auto 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_); } } // namespace opencl } // namespace kernels } // namespace lite } // namespace paddle namespace ocl = paddle::lite::kernels::opencl; // TODO(ysh329): May need fix. // "Y" may from constant value like conv bias (kARM, need do cl_image_converter // on CPU); // may from anther branch like "X" (kOpenCL, nothing to do). // Consider 2 situations have different actions when pass running(pick kernel), // set target of "Y" as kOpenCL temporarily. REGISTER_LITE_KERNEL(elementwise_sub, kOpenCL, kFP16, kImageDefault, ocl::ElementwiseSubImageCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kOpenCL), PRECISION(kFP16), DATALAYOUT(kImageDefault))}) .BindInput("Y", {LiteType::GetTensorTy(TARGET(kOpenCL), PRECISION(kFP16), DATALAYOUT(kImageDefault))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kOpenCL), PRECISION(kFP16), DATALAYOUT(kImageDefault))}) .Finalize();