Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

229 lines
6.2 KiB

// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2017, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
#include "precomp.hpp"
#include "op_halide.hpp"
#ifdef HAVE_HALIDE
#include <HalideRuntimeOpenCL.h>
#endif // HAVE_HALIDE
namespace cv
{
namespace dnn
{
#ifdef HAVE_HALIDE
static MatShape getBufferShape(const MatShape& shape)
{
if (shape.size() == 2 || shape.size() == 4)
{
int w, h, c, n;
getCanonicalSize(shape, &w, &h, &c, &n);
return {w, h, c, n};
}
else
{
MatShape bufferShape(shape);
std::reverse(bufferShape.begin(), bufferShape.end());
return bufferShape;
}
}
static MatShape getBufferShape(const MatSize& size)
{
return getBufferShape(MatShape(size.p, size.p + size[-1]));
}
Halide::Buffer<float> wrapToHalideBuffer(const Mat& mat)
{
return wrapToHalideBuffer(mat, getBufferShape(mat.size));
}
Halide::Buffer<float> wrapToHalideBuffer(const Mat& mat,
const std::vector<int>& sizes)
{
Halide::Buffer<float> buffer((float*)mat.data, sizes);
buffer.set_host_dirty(); // Indicate that data is on CPU.
return buffer;
}
Halide::Buffer<> halideBuffer(const Ptr<BackendWrapper>& ptr)
{
CV_Assert(!ptr.empty());
return ptr.dynamicCast<HalideBackendWrapper>()->buffer;
}
std::vector<Halide::Buffer<> > halideBuffers(const std::vector<Ptr<BackendWrapper> >& ptrs)
{
std::vector<Halide::Buffer<> > vec;
vec.reserve(ptrs.size());
for (const Ptr<BackendWrapper>& ptr : ptrs)
{
vec.push_back(halideBuffer(ptr));
}
return vec;
}
void getCanonicalSize(const Halide::Buffer<>& buffer, int* width, int* height,
int* channels, int* batch)
{
CV_Assert(buffer.dimensions() == 4);
*width = buffer.extent(0);
*height = buffer.extent(1);
*channels = buffer.extent(2);
*batch = buffer.extent(3);
}
HalideBackendNode::HalideBackendNode(const Halide::Func& func)
: BackendNode(DNN_BACKEND_HALIDE), funcs(1, func) {}
HalideBackendNode::HalideBackendNode(const std::vector<Halide::Func>& funcs)
: BackendNode(DNN_BACKEND_HALIDE), funcs(funcs) {}
HalideBackendNode::HalideBackendNode(const Ptr<HalideBackendNode>& base,
const Halide::Func& top)
: BackendNode(DNN_BACKEND_HALIDE), funcs(base->funcs)
{
funcs.back() = top;
}
HalideBackendWrapper::HalideBackendWrapper(int targetId, const cv::Mat& m)
: BackendWrapper(DNN_BACKEND_HALIDE, targetId)
{
managesDevMemory = true;
buffer = wrapToHalideBuffer(m);
if (targetId == DNN_TARGET_CPU)
{
return;
}
else if (targetId == DNN_TARGET_OPENCL)
{
Halide::Target t = Halide::get_host_target();
t.set_feature(Halide::Target::OpenCL);
buffer.copy_to_device(get_default_device_interface_for_target(t));
}
else
CV_Error(Error::StsNotImplemented, "Unknown target identifier");
}
HalideBackendWrapper::HalideBackendWrapper(const Ptr<BackendWrapper>& base,
const MatShape& shape)
: BackendWrapper(DNN_BACKEND_HALIDE, base->targetId)
{
managesDevMemory = false;
Halide::Buffer<float> baseBuffer = halideBuffer(base);
buffer = Halide::Buffer<float>((float*)baseBuffer.raw_buffer()->host,
getBufferShape(shape));
if (baseBuffer.has_device_allocation())
{
buffer.raw_buffer()->device = baseBuffer.raw_buffer()->device;
buffer.raw_buffer()->device_interface = baseBuffer.raw_buffer()->device_interface;
buffer.set_device_dirty();
}
else
{
buffer.set_host_dirty(); // Indicate that data is on CPU.
CV_Assert(targetId == DNN_TARGET_CPU);
}
}
HalideBackendWrapper::~HalideBackendWrapper()
{
if (buffer.has_device_allocation() && !managesDevMemory)
{
buffer.raw_buffer()->device = 0;
buffer.raw_buffer()->device_interface = 0;
buffer.set_device_dirty(false);
}
}
void HalideBackendWrapper::copyToHost()
{
if (buffer.device_dirty())
{
buffer.device_sync();
buffer.copy_to_host();
}
}
void HalideBackendWrapper::setHostDirty()
{
buffer.set_device_dirty(false);
buffer.set_host_dirty();
}
#endif // HAVE_HALIDE
void getCanonicalSize(const MatSize& size, int* w, int* h, int* c, int* n)
{
getCanonicalSize(MatShape(size.p, size.p + size[-1]), w, h, c, n);
}
void getCanonicalSize(const MatShape& shape, int* width, int* height,
int* channels, int* batch)
{
const int dims = shape.size();
CV_Assert(dims == 2 || dims == 4);
*batch = shape[0];
*channels = shape[1];
if (dims == 4)
{
*width = shape[3];
*height = shape[2];
}
else
{
*width = 1;
*height = 1;
}
}
void compileHalide(const std::vector<Mat> &outputs, Ptr<BackendNode>& node, int targetId)
{
#ifdef HAVE_HALIDE
CV_Assert(!node.empty());
Halide::Func& top = node.dynamicCast<HalideBackendNode>()->funcs.back();
int outW, outH, outC, outN;
Halide::Var x("x"), y("y"), c("c"), n("n");
getCanonicalSize(outputs[0].size, &outW, &outH, &outC, &outN);
top.bound(x, 0, outW).bound(y, 0, outH)
.bound(c, 0, outC).bound(n, 0, outN);
Halide::Target target = Halide::get_host_target();
target.set_feature(Halide::Target::NoAsserts);
if (targetId == DNN_TARGET_OPENCL)
{
target.set_feature(Halide::Target::OpenCL);
}
CV_Assert(target.supported());
top.compile_jit(target);
#endif // HAVE_HALIDE
}
void forwardHalide(std::vector<Ptr<BackendWrapper> > &outputs,
const Ptr<BackendNode>& node)
{
#ifdef HAVE_HALIDE
CV_Assert(!node.empty());
Halide::Func& top = node.dynamicCast<HalideBackendNode>()->funcs.back();
auto outputBuffers = halideBuffers(outputs);
top.realize(Halide::Realization(outputBuffers));
#endif // HAVE_HALIDE
}
bool haveHalide()
{
#ifdef HAVE_HALIDE
return true;
#else
return false;
#endif // HAVE_HALIDE
}
} // namespace dnn
} // namespace cv