Correct the wrong indents of paramters

huningxin · Jul 16, 2020 · 6580754 · 6580754
1 parent 9a64e09
commit 6580754
Show file tree

Hide file tree

Showing 14 changed files with 33 additions and 35 deletions.
diff --git a/modules/dnn/src/op_webgpu.cpp b/modules/dnn/src/op_webgpu.cpp
@@ -20,7 +20,7 @@ void copyToMat(Mat &dst, webgpu::Tensor &src)
     CV_Assert(dst.type() == CV_32F);
 
     std::vector<int> shape = src.getShape();
-    void *data = const_cast<void *>(src.map() );
+    void *data = const_cast<void *>(src.mapRead() );
     Mat tmp(shape, CV_32F, data);
     tmp.copyTo(dst);
     src.unMap();

diff --git a/modules/dnn/src/webgpu/dawnAPITest/helloCompute.cpp b/modules/dnn/src/webgpu/dawnAPITest/helloCompute.cpp
@@ -183,7 +183,7 @@ wgpu::Device createCppDawnDevice() {
     return wgpu::Device::Acquire(backendDevice);
 }
 
-wgpu::CreateBufferMappedResult createBufferMappedFromData( wgpu::Device& device,
+wgpu::CreateBufferMappedResult createBufferMappedFromData(wgpu::Device& device,
                                                         const void* data,
                                                         size_t size,
                                                         wgpu::BufferUsage usage){

diff --git a/modules/dnn/src/webgpu/dawnWrapperTest/CMakeLists.txt b/modules/dnn/src/webgpu/dawnWrapperTest/CMakeLists.txt
@@ -20,7 +20,7 @@ file(GLOB DNN
     ${OPENCV_SOURCE_DIR}/modules/dnn/src/webgpu/dawn/*.cpp
 )
 
-add_executable( softmaxTest op_softmax_test.cpp  
+add_executable(softmaxTest op_softmax_test.cpp  
                 ${SOURCES} 
                 ${Dawn} 
                 ${DNN}

diff --git a/modules/dnn/src/webgpu/dawnWrapperTest/op_softmax_test.cpp b/modules/dnn/src/webgpu/dawnWrapperTest/op_softmax_test.cpp
@@ -18,8 +18,7 @@ void printData(const void * data, int num) {
 }
 int main(int argc, char** argv )
 {
-    webgpu::wDevice = std::make_shared<wgpu::Device>(webgpu::createCppDawnDevice());
-    webgpu::wQueue = std::make_shared<wgpu::Queue>(webgpu::wDevice->GetDefaultQueue());
+    webgpu::isAvailable();
     float inputData1[] = {1, 2, 3, 4, 5, 6, 7, 8};
     std::vector<int> shape = {2,4,1}; // outer_size * channels * channel_size
 

diff --git a/modules/dnn/src/webgpu/include/buffer.hpp b/modules/dnn/src/webgpu/include/buffer.hpp
@@ -27,9 +27,9 @@ class Buffer
     wgpu::BufferUsage getBufferUsage() { return usage_;}
 
     static void BufferMapReadCallback(WGPUBufferMapAsyncStatus status,
-                                   const void* data,
-                                   uint64_t dataLength,
-                                   void* userdata)
+                                      const void* data,
+                                      uint64_t dataLength,
+                                      void* userdata)
     {
         static_cast<Buffer*>(userdata)->mappedData = data;
     }

diff --git a/modules/dnn/src/webgpu/include/op_base.hpp b/modules/dnn/src/webgpu/include/op_base.hpp
@@ -36,7 +36,7 @@ class OpBase
     void createCommandBuffer();
     void runCommandBuffer();
     wgpu::FenceCompletionStatus WaitForCompletedValue(wgpu::Fence fence, 
-                                                uint64_t completedValue);
+                                                      uint64_t completedValue);
 
     std::shared_ptr<wgpu::Device> device_;
     wgpu::ComputePipeline pipeline_;

diff --git a/modules/dnn/src/webgpu/include/tensor.hpp b/modules/dnn/src/webgpu/include/tensor.hpp
@@ -13,7 +13,7 @@ class Tensor{
 public:
     Tensor(Format fmt = wFormatFp32);
     Tensor(const void* data, std::vector<int>& shape,  
-            Format fmt = wFormatFp32);
+           Format fmt = wFormatFp32);
     const void* mapRead();
     void unMap();
     Shape getShape() const;
@@ -24,8 +24,8 @@ class Tensor{
     // Copy data if data != NULL
     // Allocate new internal buffer if new size > old size or alloc flag is true
     Tensor reshape(const void* data, const std::vector<int>& shape, 
-                    bool alloc = false, 
-                    Format fmt = wFormatInvalid);
+                   bool alloc = false, 
+                   Format fmt = wFormatInvalid);
     Tensor fillData(const void * data);
     int getFormat() const;
     size_t size() const { return size_in_byte_; }
@@ -38,7 +38,8 @@ class Tensor{
     size_t size_in_byte_;
     std::shared_ptr<Buffer> buffer_;
     Format format_;
-    wgpu::BufferUsage usage_;
+    wgpu::BufferUsage usage_ = wgpu::BufferUsage::Storage | 
+    wgpu::BufferUsage::CopySrc | wgpu::BufferUsage::CopyDst;
 };
 
 // #endif  //HAVE_WEBGPU

diff --git a/modules/dnn/src/webgpu/src/buffer.cpp b/modules/dnn/src/webgpu/src/buffer.cpp
@@ -7,13 +7,14 @@ namespace cv { namespace dnn { namespace webgpu {
 
 Buffer::Buffer(std::shared_ptr<wgpu::Device> device)
 {
-    device_ =  device;
-    usage_ = wgpu::BufferUsage::Storage;
+    device_ = device;
+    usage_ = wgpu::BufferUsage::Storage | wgpu::BufferUsage::CopyDst |
+             wgpu::BufferUsage::CopySrc;
 }
 
 Buffer::Buffer(std::shared_ptr<wgpu::Device> device, 
-                const void* data, size_t size, 
-                wgpu::BufferUsage usage) 
+               const void* data, size_t size, 
+               wgpu::BufferUsage usage) 
 {
     device_ = device;
     usage_ = usage;
@@ -26,7 +27,7 @@ Buffer::Buffer(std::shared_ptr<wgpu::Device> device,
 }
 
 Buffer::Buffer(const void* data, size_t size,  
-        wgpu::BufferUsage usage)
+               wgpu::BufferUsage usage)
 {
     createContext();
     device_ = wDevice;
@@ -55,8 +56,8 @@ const void* Buffer::MapReadAsyncAndWait()
         gpuReadBuffer_ = device_->CreateBuffer(& desc);
     }
     wgpu::CommandEncoder encoder = device_->CreateCommandEncoder();
-    encoder.CopyBufferToBuffer( buffer_, 0, 
-                                gpuReadBuffer_, 0, size_);
+    encoder.CopyBufferToBuffer(buffer_, 0, 
+                               gpuReadBuffer_, 0, size_);
     wgpu::CommandBuffer cmdBuffer = encoder.Finish();
     encoder.Release();
     wQueue->Submit(1, &cmdBuffer);

diff --git a/modules/dnn/src/webgpu/src/context.cpp b/modules/dnn/src/webgpu/src/context.cpp
@@ -39,13 +39,11 @@ bool isAvailable()
 }
 Context::Context() 
 {
-    // create wgpu::Device
     wDevice = std::make_shared<wgpu::Device>(createCppDawnDevice());
     wQueue = std::make_shared<wgpu::Queue>(wDevice->GetDefaultQueue());
 }
 Context::~Context() 
 {
-    // how to release object
     wDevice->Release();
     wQueue->Release();
 }

diff --git a/modules/dnn/src/webgpu/src/context.hpp b/modules/dnn/src/webgpu/src/context.hpp
@@ -9,10 +9,6 @@ class Context
 public:
     Context();
     ~Context();
-std::shared_ptr<Context> wCtx;
-std::shared_ptr<wgpu::Device> wDevice = nullptr;
-std::shared_ptr<wgpu::Queue> wQueue = nullptr;
-cv::Mutex wContextMtx;
 };
 
 void createContext();

diff --git a/modules/dnn/src/webgpu/src/internal.cpp b/modules/dnn/src/webgpu/src/internal.cpp
@@ -58,7 +58,7 @@ void bindTensor(Tensor& tensor, uint32_t binding,
 }
 
 void bindUniform(Buffer& buffer, uint32_t binding,
-                std::vector<wgpu::BindGroupEntry>& bgEntries)
+                 std::vector<wgpu::BindGroupEntry>& bgEntries)
 {
     wgpu::BindGroupEntry bgEntry = {};
     bgEntry.binding = binding;
@@ -106,11 +106,11 @@ void computeConvOutputShapeAndPadding(const PaddingMode& padding_mode,
 }
 
 void computePoolOutputShape(const PaddingMode& padding_mode,
-        const int& padding_top, const int& padding_left,
-        const int& in_h, const int& in_w,
-        const int& filter_h, const int& filter_w,
-        const int& stride_h, const int& stride_w,
-        int& out_h, int& out_w)
+                            const int& padding_top, const int& padding_left,
+                            const int& in_h, const int& in_w,
+                            const int& filter_h, const int& filter_w,
+                            const int& stride_h, const int& stride_w,
+                            int& out_h, int& out_w)
 {
     if (padding_mode == wPaddingModeValid)
     {

diff --git a/modules/dnn/src/webgpu/src/internal.hpp b/modules/dnn/src/webgpu/src/internal.hpp
@@ -21,7 +21,7 @@ std::vector<uint32_t> compile(const std::string& name,
 void bindTensor(Tensor& tensor, uint32_t binding, 
                 std::vector<wgpu::BindGroupEntry>& bgEntries);
 void bindUniform(Buffer& buffer, uint32_t binding,
-                std::vector<wgpu::BindGroupEntry>& bgEntries);
+                 std::vector<wgpu::BindGroupEntry>& bgEntries);
 void computeConvOutputShapeAndPadding(const PaddingMode& padding_mode,
                                       int& padding_top, int& padding_left,
                                       const int& in_h, const int& in_w,

diff --git a/modules/dnn/src/webgpu/src/tensor.cpp b/modules/dnn/src/webgpu/src/tensor.cpp
@@ -15,7 +15,7 @@ Tensor::Tensor(const void* data, std::vector<int>& shape, Format fmt)
     createContext();
     device_ = wDevice;
     size_in_byte_ = 0;
-    usage_ = wgpu::BufferUsage::Storage | wgpu::BufferUsage::CopySrc | wgpu::BufferUsage::CopyDst;
+    usage_ = wgpu::BufferUsage::Storage | wgpu::BufferUsage::CopyDst | wgpu::BufferUsage::CopySrc;
     format_ = fmt;
     reshape(data, shape);
 }
@@ -54,7 +54,7 @@ int Tensor::dimNum() const
 }
 
 Tensor Tensor::reshape(const void* data, const std::vector<int>& shape, 
-                        bool alloc, Format fmt)
+                       bool alloc, Format fmt)
 {
     if (device_ == nullptr)
     {
@@ -76,6 +76,7 @@ Tensor Tensor::reshape(const void* data, const std::vector<int>& shape,
         return * this;
     }
     fillData(data);
+    return * this;
 }
 
 Tensor Tensor::fillData(const void * data) 

diff --git a/modules/dnn/test/test_common.impl.hpp b/modules/dnn/test/test_common.impl.hpp
@@ -25,6 +25,7 @@ void PrintTo(const cv::dnn::Backend& v, std::ostream* os)
     case DNN_BACKEND_HALIDE: *os << "HALIDE"; return;
     case DNN_BACKEND_INFERENCE_ENGINE: *os << "DLIE*"; return;
     case DNN_BACKEND_VKCOM: *os << "VKCOM"; return;
+    case DNN_BACKEND_WGPU: *os << "WGPU"; return;
     case DNN_BACKEND_OPENCV: *os << "OCV"; return;
     case DNN_BACKEND_CUDA: *os << "CUDA"; return;
     case DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019: *os << "DLIE"; return;
@@ -41,6 +42,7 @@ void PrintTo(const cv::dnn::Target& v, std::ostream* os)
     case DNN_TARGET_OPENCL_FP16: *os << "OCL_FP16"; return;
     case DNN_TARGET_MYRIAD: *os << "MYRIAD"; return;
     case DNN_TARGET_VULKAN: *os << "VULKAN"; return;
+    case DNN_TARGET_WGPU: *os << "WGPU"; return;
     case DNN_TARGET_FPGA: *os << "FPGA"; return;
     case DNN_TARGET_CUDA: *os << "CUDA"; return;
     case DNN_TARGET_CUDA_FP16: *os << "CUDA_FP16"; return;