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https://github.com/opencv/opencv.git
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a2b3acfc6e
* cann backend impl v1 * cann backend impl v2: use opencv parsers to build models for cann * adjust fc according to the new transA and transB * put cann net in cann backend node and reuse forwardLayer * use fork() to create a child process and compile cann model * remove legacy code * remove debug code * fall bcak to CPU backend if there is one layer not supoorted by CANN backend * fix netInput forward
132 lines
3.5 KiB
C++
132 lines
3.5 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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#include "precomp.hpp"
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#include "legacy_backend.hpp"
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#include "op_halide.hpp"
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#include "op_inf_engine.hpp"
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#include "ie_ngraph.hpp"
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#include "op_vkcom.hpp"
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#include "op_cuda.hpp"
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#include "op_webnn.hpp"
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#include "op_timvx.hpp"
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#include "op_cann.hpp"
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namespace cv {
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namespace dnn {
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CV__DNN_INLINE_NS_BEGIN
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BackendNode::BackendNode(int backendId)
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: backendId(backendId)
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{}
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BackendNode::~BackendNode() {};
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BackendWrapper::BackendWrapper(int backendId, int targetId)
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: backendId(backendId)
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, targetId(targetId)
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{}
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BackendWrapper::BackendWrapper(int targetId, const cv::Mat& m)
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{
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CV_Error(Error::StsNotImplemented,
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"Constructor of backend wrapper must be implemented");
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}
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BackendWrapper::BackendWrapper(const Ptr<BackendWrapper>& base, const MatShape& shape)
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{
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CV_Error(Error::StsNotImplemented,
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"Constructor of backend wrapper must be implemented");
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}
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BackendWrapper::~BackendWrapper() {}
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inline namespace detail {
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Ptr<BackendWrapper> wrapMat(int backendId, int targetId, cv::Mat& m)
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{
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if (backendId == DNN_BACKEND_OPENCV)
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{
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if (targetId == DNN_TARGET_CPU)
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return Ptr<BackendWrapper>();
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#ifdef HAVE_OPENCL
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else if (IS_DNN_OPENCL_TARGET(targetId))
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return OpenCLBackendWrapper::create(m);
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#endif
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else
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CV_Error(Error::StsNotImplemented, "Unknown/unsupported target identifier");
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}
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else if (backendId == DNN_BACKEND_HALIDE)
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{
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CV_Assert(haveHalide());
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#ifdef HAVE_HALIDE
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return Ptr<BackendWrapper>(new HalideBackendWrapper(targetId, m));
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#endif // HAVE_HALIDE
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}
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else if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
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{
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CV_ERROR_DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019;
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}
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else if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH)
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{
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CV_Assert(0 && "Internal error: DNN_BACKEND_INFERENCE_ENGINE_NGRAPH must be implemented through inheritance");
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}
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else if (backendId == DNN_BACKEND_WEBNN)
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{
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#ifdef HAVE_WEBNN
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return Ptr<BackendWrapper>(new WebnnBackendWrapper(targetId, m));
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#else
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CV_Error(Error::StsNotImplemented, "This OpenCV version is built without support of WebNN");
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#endif
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}
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else if (backendId == DNN_BACKEND_VKCOM)
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{
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CV_Assert(haveVulkan());
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#ifdef HAVE_VULKAN
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return Ptr<BackendWrapper>(new VkComBackendWrapper(m));
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#endif // HAVE_VULKAN
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}
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else if (backendId == DNN_BACKEND_CUDA)
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{
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CV_Assert(haveCUDA());
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#ifdef HAVE_CUDA
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switch (targetId)
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{
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case DNN_TARGET_CUDA:
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return CUDABackendWrapperFP32::create(m);
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case DNN_TARGET_CUDA_FP16:
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return CUDABackendWrapperFP16::create(m);
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default:
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CV_Assert(IS_DNN_CUDA_TARGET(targetId));
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}
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#endif
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}
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else if (backendId == DNN_BACKEND_TIMVX)
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{
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CV_Assert(haveTimVX());
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#ifdef HAVE_TIMVX
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return Ptr<BackendWrapper>(new TimVXBackendWrapper(m));
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#endif // HAVE_TIMVX
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}
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else if (backendId == DNN_BACKEND_CANN)
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{
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CV_Assert(0 && "Internal error: DNN_BACKEND_CANN must be implemented through inheritance");
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}
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else
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CV_Error(Error::StsNotImplemented, "Unknown backend identifier");
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return Ptr<BackendWrapper>(); // TODO Error?
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} // wrapMat()
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} // namespace detail
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CV__DNN_INLINE_NS_END
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}} // namespace cv::dnn
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