[LITE][OPENCL]Add scale kernel. (#2861)

* [LITE][OPENCL]Add scale kernel.

* [LITE][OPENCL]Add scale kernel, format code style.

lite/backends/opencl/cl_kernel/image/scale_kernel.cl

+/* 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. */
+
+#include <cl_common.h>
+
+__kernel void scale(__read_only image2d_t input,
+                    __write_only image2d_t output,
+                    __private float scale,
+                    __private float bias){
+
+  const int x = get_global_id(0); // image_width
+  const int y = get_global_id(1); // image_height
+
+  const sampler_t sampler = CLK_NORMALIZED_COORDS_TRUE |
+                            CLK_ADDRESS_CLAMP |
+                            CLK_FILTER_NEAREST;
+
+  CL_DTYPE4 in = READ_IMG_TYPE(CL_DTYPE_CHAR, input, sampler, (int2)(x, y));
+  in = convert_float(scale) * in + convert_float(bias);
+  WRITE_IMG_TYPE(CL_DTYPE_CHAR, output, (int2)(x, y), in);
+}

lite/kernels/opencl/CMakeLists.txt

@@ -22,6 +22,7 @@ add_kernel(conv_opencl OPENCL basic SRCS conv_compute.cc DEPS ${cl_kernel_deps}
 add_kernel(layout_opencl OPENCL basic SRCS layout_compute.cc DEPS ${cl_kernel_deps})
 add_kernel(concat_opencl OPENCL basic SRCS concat_compute.cc DEPS ${cl_kernel_deps})
 add_kernel(nearest_interp_opencl OPENCL basic SRCS nearest_interp_compute.cc DEPS ${cl_kernel_deps})
+add_kernel(scale_opencl OPENCL basic SRCS scale_compute.cc DEPS ${cl_kernel_deps})
 
 lite_cc_test(test_elementwise_add_opencl SRCS elementwise_add_compute_test.cc
              DEPS elementwise_add_opencl fusion_elementwise_add_activation_opencl op_registry program context
@@ -92,3 +93,7 @@ lite_cc_test(test_concat_opencl SRCS concat_compute_test.cc
 lite_cc_test(test_nearest_interp_opencl SRCS nearest_interp_compute_test.cc
         DEPS nearest_interp_opencl layout_opencl op_registry program context cl_image_converter
         ARGS --cl_path=${CMAKE_SOURCE_DIR}/lite/backends/opencl)
+
+lite_cc_test(test_scale_opencl SRCS scale_compute_test.cc
+             DEPS scale_opencl op_registry program context
+             ARGS --cl_path=${CMAKE_SOURCE_DIR}/lite/backends/opencl)

lite/kernels/opencl/scale_compute.cc

+// 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 <vector>
+#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/replace_stl/stream.h"
+#include "lite/utils/string.h"
+
+namespace paddle {
+namespace lite {
+namespace kernels {
+namespace opencl {
+
+class ScaleComputeImage2D : public KernelLite<TARGET(kOpenCL),
+                                              PRECISION(kFloat),
+                                              DATALAYOUT(kImageDefault)> {
+ public:
+  using param_t = operators::ScaleParam;
+
+  std::string doc() const override { return "Scale using cl::Image2D, kFloat"; }
+
+  void PrepareForRun() override {
+    auto& context = ctx_->As<OpenCLContext>();
+    context.cl_context()->AddKernel(
+        kernel_func_name_, "image/scale_kernel.cl", build_options_);
+  }
+
+  void Run() override {
+    const auto& param = *param_.get_mutable<param_t>();
+    const auto& in_dims = param.x->dims();
+    auto* x_img = param.x->data<float, cl::Image2D>();
+    const float scale = param.scale;
+    const float bias = param.bias;
+
+    LOG(INFO) << "x_image" << x_img;
+    auto out_image_shape = InitImageDimInfoWith(in_dims);
+    LOG(INFO) << "out_image_shape = " << out_image_shape["width"] << " "
+              << out_image_shape["height"];
+    auto* out_img = param.output->mutable_data<float, cl::Image2D>(
+        out_image_shape["width"], out_image_shape["height"]);
+    LOG(INFO) << "out_image" << out_img;
+
+    auto& context = ctx_->As<OpenCLContext>();
+    CHECK(context.cl_context() != nullptr);
+    STL::stringstream kernel_key;
+    kernel_key << kernel_func_name_ << build_options_;
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
+
+    auto global_work_size =
+        cl::NDRange{static_cast<cl::size_type>(out_image_shape["width"]),
+                    static_cast<cl::size_type>(out_image_shape["height"])};
+
+    cl_int status;
+    int arg_idx = 0;
+    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, scale);
+    CL_CHECK_FATAL(status);
+    status = kernel.setArg(++arg_idx, bias);
+    CL_CHECK_FATAL(status);
+
+    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_);
+  }
+
+ private:
+  std::string kernel_func_name_{"scale"};
+  std::string build_options_{"-DCL_DTYPE_float"};
+  std::shared_ptr<cl::Event> event_{new cl::Event};
+};
+
+}  // namespace opencl
+}  // namespace kernels
+}  // namespace lite
+}  // namespace paddle
+
+REGISTER_LITE_KERNEL(scale,
+                     kOpenCL,
+                     kFloat,
+                     kImageDefault,
+                     paddle::lite::kernels::opencl::ScaleComputeImage2D,
+                     image2d)
+    .BindInput("X",
+               {LiteType::GetTensorTy(TARGET(kOpenCL),
+                                      PRECISION(kFloat),
+                                      DATALAYOUT(kImageDefault))})
+    .BindOutput("Out",
+                {LiteType::GetTensorTy(TARGET(kOpenCL),
+                                       PRECISION(kFloat),
+                                       DATALAYOUT(kImageDefault))})
+    .Finalize();

lite/kernels/opencl/scale_compute_test.cc

+// 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 <gtest/gtest.h>
+#include <memory>
+#include <random>
+#include "lite/backends/opencl/target_wrapper.h"
+#include "lite/core/op_registry.h"
+#include "lite/core/tensor.h"
+
+namespace paddle {
+namespace lite {
+
+void scale(const float* input_data,
+           const DDim& in_dim,
+           float* output_data,
+           const float scale,
+           const float bias) {
+  for (int i = 0; i < in_dim.production(); i++) {
+    output_data[i] = input_data[i] * scale + bias;
+  }
+}
+
+TEST(scale_image2d_fp32, compute) {
+  LOG(INFO) << "to get kernel ...";
+  auto kernels = KernelRegistry::Global().Create(
+      "scale", TARGET(kOpenCL), PRECISION(kFloat), DATALAYOUT(kImageDefault));
+  ASSERT_FALSE(kernels.empty());
+
+  auto kernel = std::move(kernels.front());
+
+  LOG(INFO) << "get kernel:" << kernel->doc();
+
+  lite::Tensor x, out;
+  operators::ScaleParam param;
+  param.x = &x;
+  param.output = &out;
+  param.scale = 1.5f;
+  param.bias = 0.3f;
+
+  std::unique_ptr<KernelContext> context(new KernelContext);
+  context->As<OpenCLContext>().InitOnce();
+
+  kernel->SetParam(param);
+  std::unique_ptr<KernelContext> scale_context(new KernelContext);
+  context->As<OpenCLContext>().CopySharedTo(
+      &(scale_context->As<OpenCLContext>()));
+  kernel->SetContext(std::move(scale_context));
+
+  const DDim in_dim = DDim(std::vector<DDim::value_type>{4, 11, 107, 107});
+  const DDim out_dim = DDim(std::vector<DDim::value_type>{4, 11, 107, 107});
+  x.Resize(in_dim);
+  out.Resize(out_dim);
+
+  std::default_random_engine engine;
+  std::uniform_real_distribution<float> dist(-5, 5);
+  std::vector<float> input_v(4 * 11 * 107 * 107);
+  for (auto& i : input_v) {
+    i = dist(engine);
+  }
+
+  LOG(INFO) << "prepare input";
+  CLImageConverterDefault* default_converter = new CLImageConverterDefault();
+  DDim image_shape = default_converter->InitImageDimInfoWith(in_dim);
+  LOG(INFO) << "image_shape = " << image_shape[0] << " " << image_shape[1];
+  std::vector<float> x_image_data(image_shape.production() * 4);  // 4 : RGBA
+  default_converter->NCHWToImage(input_v.data(), x_image_data.data(), in_dim);
+  auto* x_image = x.mutable_data<float, cl::Image2D>(
+      image_shape[0], image_shape[1], x_image_data.data());
+  LOG(INFO) << "x_image:" << x_image;
+
+  auto* out_image =
+      out.mutable_data<float, cl::Image2D>(image_shape[0], image_shape[1]);
+  LOG(INFO) << "out_image:" << out_image;
+  kernel->Launch();
+
+  auto* wait_list = context->As<OpenCLContext>().cl_wait_list();
+  auto* out_ptr = param.output->data<float, cl::Image2D>();
+  auto it = wait_list->find(out_ptr);
+  if (it != wait_list->end()) {
+    VLOG(4) << "--- Find the sync event for the target cl tensor. ---";
+    auto& event = *(it->second);
+    event.wait();
+  } else {
+    LOG(FATAL) << "Could not find the sync event for the target cl tensor.";
+  }
+
+  std::unique_ptr<float[]> out_ref(new float[out_dim.production()]);
+  scale(input_v.data(), in_dim, out_ref.get(), 1.5f, 0.3f);
+
+  const size_t cl_image2d_row_pitch{0};
+  const size_t cl_image2d_slice_pitch{0};
+  float* out_image_data = new float[image_shape.production() * 4];
+  TargetWrapperCL::ImgcpySync(out_image_data,
+                              out_image,
+                              image_shape[0],
+                              image_shape[1],
+                              cl_image2d_row_pitch,
+                              cl_image2d_slice_pitch,
+                              IoDirection::DtoH);
+  float* out_data = new float[image_shape.production() * 4];
+  default_converter->ImageToNCHW(
+      out_image_data, out_data, image_shape, out_dim);
+
+  for (int i = 0; i < out_dim.production(); i++) {
+    EXPECT_NEAR(out_data[i], out_ref[i], 1e-6);
+  }
+}
+
+}  // namespace lite
+}  // namespace paddle
+
+USE_LITE_KERNEL(scale, kOpenCL, kFloat, kImageDefault, image2d);