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416bf3253d
* attempt to add 0d/1d mat support to OpenCV * revised the patch; now 1D mat is treated as 1xN 2D mat rather than Nx1. * a step towards 'green' tests * another little step towards 'green' tests * calib test failures seem to be fixed now * more fixes _core & _dnn * another step towards green ci; even 0D mat's (a.k.a. scalars) are now partly supported! * * fixed strange bug in aruco/charuco detector, not sure why it did not work * also fixed a few remaining failures (hopefully) in dnn & core * disabled failing GAPI tests - too complex to dig into this compiler pipeline * hopefully fixed java tests * trying to fix some more tests * quick followup fix * continue to fix test failures and warnings * quick followup fix * trying to fix some more tests * partly fixed support for 0D/scalar UMat's * use updated parseReduce() from upstream * trying to fix the remaining test failures * fixed [ch]aruco tests in Python * still trying to fix tests * revert "fix" in dnn's CUDA tensor * trying to fix dnn+CUDA test failures * fixed 1D umat creation * hopefully fixed remaining cuda test failures * removed training whitespaces
127 lines
2.7 KiB
C++
127 lines
2.7 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 "internal.hpp"
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namespace cv { namespace dnn { namespace vkcom {
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#ifdef HAVE_VULKAN
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Tensor::Tensor(Format fmt, VkBufferUsageFlags usageFlag) : size_in_byte_(0), format_(fmt), usageFlag_(usageFlag)
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{
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}
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Tensor::Tensor(const char* data, std::vector<int>& shape, Format fmt, VkBufferUsageFlags usageFlag)
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: size_in_byte_(0), format_(fmt), usageFlag_(usageFlag)
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{
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reshape(data, shape);
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}
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void* Tensor::map()
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{
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void *p;
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VK_CHECK_RESULT(vkMapMemory(kDevice, buffer_->getVkMemory(),
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0, size_in_byte_, 0, (void **)&p));
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return p;
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}
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void Tensor::unMap()
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{
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vkUnmapMemory(kDevice, buffer_->getVkMemory());
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}
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Shape Tensor::getShape() const
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{
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return shape_;
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}
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int Tensor::count(const int start_axis, const int end_axis) const
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{
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return shapeCount(shape_, start_axis, end_axis);
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}
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int Tensor::dimSize(const int axis) const
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{
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CV_Assert(axis >= 0);
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CV_Assert(axis < shape_.size());
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return shape_[axis];
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}
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int Tensor::dimNum() const
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{
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return shape_.size();
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}
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Tensor Tensor::reshape(const char* data, const std::vector<int>& shape, bool alloc, Format fmt)
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{
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if (kDevice == VK_NULL_HANDLE)
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{
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CV_Error(Error::StsError, "device is NULL!");
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return *this;
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}
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CV_Assert(/*shape.size() > 0 &&*/ shape.size() <= 6);
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if (shape_ != shape) shape_ = shape;
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if (checkFormat(fmt) && fmt != format_) format_ = fmt;
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size_t new_size = shapeCount(shape_) * elementSize(format_);
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if (alloc || new_size > size_in_byte_)
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alloc = true;
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size_in_byte_ = new_size;
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if (alloc)
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{
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buffer_.reset(new Buffer(size_in_byte_, data, usageFlag_));
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}
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else if (data)
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{
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void* p = map();
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memcpy(p, data, size_in_byte_);
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unMap();
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}
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return *this;
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}
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void Tensor::setTo(float val)
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{
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if (kDevice == VK_NULL_HANDLE)
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{
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CV_Error(Error::StsError, "device is NULL!");
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return;
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}
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CV_Assert(format_ == kFormatFp32);
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float* p = (float *)map();
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int cnt = count();
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for (int i = 0; i < cnt; i++)
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*p++ = val;
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unMap();
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}
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int Tensor::getFormat() const
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{
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return format_;
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}
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void Tensor::copyTo(Tensor& dst)
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{
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void* p = map();
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dst.reshape((const char*)p, shape_, format_);
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unMap();
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}
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#endif // HAVE_VULKAN
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}}} // namespace cv::dnn::vkcom
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