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* dnn: Add a Vulkan based backend This commit adds a new backend "DNN_BACKEND_VKCOM" and a new target "DNN_TARGET_VULKAN". VKCOM means vulkan based computation library. This backend uses Vulkan API and SPIR-V shaders to do the inference computation for layers. The layer types that implemented in DNN_BACKEND_VKCOM include: Conv, Concat, ReLU, LRN, PriorBox, Softmax, MaxPooling, AvePooling, Permute This is just a beginning work for Vulkan in OpenCV DNN, more layer types will be supported and performance tuning is on the way. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> * dnn/vulkan: Add FindVulkan.cmake to detect Vulkan SDK In order to build dnn with Vulkan support, need installing Vulkan SDK and setting environment variable "VULKAN_SDK" and add "-DWITH_VULKAN=ON" to cmake command. You can download Vulkan SDK from: https://vulkan.lunarg.com/sdk/home#linux For how to install, see https://vulkan.lunarg.com/doc/sdk/latest/linux/getting_started.html https://vulkan.lunarg.com/doc/sdk/latest/windows/getting_started.html https://vulkan.lunarg.com/doc/sdk/latest/mac/getting_started.html respectively for linux, windows and mac. To run the vulkan backend, also need installing mesa driver. On Ubuntu, use this command 'sudo apt-get install mesa-vulkan-drivers' To test, use command '$BUILD_DIR/bin/opencv_test_dnn --gtest_filter=*VkCom*' Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> * dnn/Vulkan: dynamically load Vulkan runtime No compile-time dependency on Vulkan library. If Vulkan runtime is unavailable, fallback to CPU path. Use environment "OPENCL_VULKAN_RUNTIME" to specify path to your own vulkan runtime library. Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> * dnn/Vulkan: Add a python script to compile GLSL shaders to SPIR-V shaders The SPIR-V shaders are in format of text-based 32-bit hexadecimal numbers, and inserted into .cpp files as unsigned int32 array. * dnn/Vulkan: Put Vulkan headers into 3rdparty directory and some other fixes Vulkan header files are copied from https://github.com/KhronosGroup/Vulkan-Docs/tree/master/include/vulkan to 3rdparty/include Fix the Copyright declaration issue. Refine OpenCVDetectVulkan.cmake * dnn/Vulkan: Add vulkan backend tests into existing ones. Also fixed some test failures. - Don't use bool variable as uniform for shader - Fix dispathed group number beyond max issue - Bypass "group > 1" convolution. This should be support in future. * dnn/Vulkan: Fix multiple initialization in one thread.
163 lines
4.3 KiB
C++
163 lines
4.3 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2018, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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#include "precomp.hpp"
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#include <opencv2/dnn/shape_utils.hpp>
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#include "op_vkcom.hpp"
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namespace cv
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{
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namespace dnn
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{
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#ifdef HAVE_VULKAN
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void copyToTensor(vkcom::Tensor &dst, const Mat &src)
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{
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CV_Assert(src.isContinuous() && src.type() == CV_32F);
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std::vector<int> mat_shape = shape(src);
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dst.reshape((const char*)src.data, mat_shape);
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}
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void copyToMat(Mat &dst, vkcom::Tensor &src)
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{
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CV_Assert(dst.type() == CV_32F);
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std::vector<int> shape = src.getShape();
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void *data = src.map();
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Mat tmp(shape, CV_32F, data);
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tmp.copyTo(dst);
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src.unMap();
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}
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vkcom::Tensor VkComTensor(const Ptr<BackendWrapper>& ptr)
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{
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CV_Assert(!ptr.empty());
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return ptr.dynamicCast<VkComBackendWrapper>()->getTensor();
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}
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void setDirty(std::vector<Ptr<BackendWrapper> >& ptrs)
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{
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for (const Ptr<BackendWrapper>& ptr : ptrs)
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{
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ptr.dynamicCast<VkComBackendWrapper>()->setDeviceDirty();
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}
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}
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std::vector<vkcom::Tensor> VkComTensors(const std::vector<Ptr<BackendWrapper> >& ptrs)
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{
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std::vector<vkcom::Tensor> vec;
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vec.reserve(ptrs.size());
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for (const Ptr<BackendWrapper>& ptr : ptrs)
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{
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vec.push_back(VkComTensor(ptr));
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}
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return vec;
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}
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VkComBackendNode::VkComBackendNode(const std::vector<Ptr<BackendWrapper> >& inputsWrapper,
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const std::shared_ptr<vkcom::OpBase>& op,
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const std::vector<Ptr<BackendWrapper> >& blobsWrapper)
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: BackendNode(DNN_BACKEND_VKCOM)
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{
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operation = op;
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inputsWrapper_ = inputsWrapper;
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ins = VkComTensors(inputsWrapper_);
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if (!blobsWrapper.empty())
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{
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blobs = VkComTensors(blobsWrapper);
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}
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}
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bool VkComBackendNode::forward(std::vector<vkcom::Tensor>& outs)
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{
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for (int i = 0, n = inputsWrapper_.size(); i < n; ++i)
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{
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inputsWrapper_[i].dynamicCast<VkComBackendWrapper>()->copyToDevice();
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}
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return operation->forward(ins, blobs, outs);
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}
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VkComBackendWrapper::VkComBackendWrapper(Mat& m) : BackendWrapper(DNN_BACKEND_VKCOM, DNN_TARGET_VULKAN)
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{
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copyToTensor(tensor, m);
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host = &m;
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hostDirty = false;
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deviceDirty = false;
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}
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VkComBackendWrapper::VkComBackendWrapper(const Ptr<BackendWrapper>& baseBuffer, Mat& m)
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: BackendWrapper(DNN_BACKEND_VKCOM, DNN_TARGET_VULKAN)
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{
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Ptr<VkComBackendWrapper> base = baseBuffer.dynamicCast<VkComBackendWrapper>();
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CV_Assert(!base.empty());
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host = &m;
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tensor = base->tensor;
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CV_Assert(tensor.count() >= m.total());
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tensor.reshape(0, shape(m));
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hostDirty = false;
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deviceDirty = false;
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}
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void VkComBackendWrapper::copyToHost()
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{
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if (deviceDirty)
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copyToMat(*host, tensor);
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}
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void VkComBackendWrapper::setHostDirty()
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{
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hostDirty = true;
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};
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void VkComBackendWrapper::setDeviceDirty()
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{
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deviceDirty = true;
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};
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void VkComBackendWrapper::copyToDevice()
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{
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if (hostDirty)
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{
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copyToTensor(tensor, *host);
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hostDirty = false;
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}
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}
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vkcom::Tensor VkComBackendWrapper::getTensor()
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{
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return tensor;
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}
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#endif
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void forwardVkCom(std::vector<Ptr<BackendWrapper> > &outputs,
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const Ptr<BackendNode>& node)
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{
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#ifdef HAVE_VULKAN
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CV_Assert(!node.empty());
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Ptr<VkComBackendNode> node_ = node.dynamicCast<VkComBackendNode>();
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std::vector<vkcom::Tensor> outs = VkComTensors(outputs);
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node_->forward(outs);
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setDirty(outputs);
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#endif
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}
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bool haveVulkan()
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{
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#ifdef HAVE_VULKAN
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return vkcom::isAvailable();
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#else
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return false;
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#endif // HAVE_VULKAN
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}
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} // namespace dnn
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} // namespace cv
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