permute layer ocl implementation

Signed-off-by: Li Peng <peng.li@intel.com>
pull/10228/head
Li Peng 7 years ago
parent a3ec2ac3c5
commit 7b7033ac60
  1. 59
      modules/dnn/src/layers/permute_layer.cpp
  2. 67
      modules/dnn/src/opencl/permute.cl

@ -44,6 +44,7 @@
#include "layers_common.hpp"
#include <float.h>
#include <algorithm>
#include "opencl_kernels_dnn.hpp"
namespace cv
{
@ -173,6 +174,24 @@ public:
CV_Assert((int)_numAxes == inp0.dims);
computeStrides(shape(*inputs[0]), shape(outputs[0]));
#ifdef HAVE_OPENCL
if (uorder.empty())
{
std::vector<int> orderVec(_order.begin(), _order.end());;
Mat morder(1, orderVec.size(), CV_32SC1, &orderVec[0]);
std::vector<int> oldStrideVec(_oldStride.begin(), _oldStride.end());
Mat mold_stride(1, _oldStride.size(), CV_32SC1, &oldStrideVec[0]);
std::vector<int> newStrideVec(_newStride.begin(), _newStride.end());
Mat mnew_stride(1, newStrideVec.size(), CV_32SC1, &newStrideVec[0]);
morder.copyTo(uorder);
mold_stride.copyTo(uold_stride);
mnew_stride.copyTo(unew_stride);
}
#endif
}
class PermuteInvoker : public ParallelLoopBody
@ -247,11 +266,47 @@ public:
}
};
#ifdef HAVE_OPENCL
bool forward_ocl(InputArrayOfArrays inps, OutputArrayOfArrays outs, OutputArrayOfArrays internals)
{
std::vector<UMat> inputs;
std::vector<UMat> outputs;
inps.getUMatVector(inputs);
outs.getUMatVector(outputs);
if (!_needsPermute)
return false;
for (size_t i = 0; i < inputs.size(); i++)
{
ocl::Kernel kernel("permute", ocl::dnn::permute_oclsrc);
kernel.set(0, (int)_count);
kernel.set(1, ocl::KernelArg::PtrReadOnly(inputs[i]));
kernel.set(2, ocl::KernelArg::PtrReadOnly(uorder));
kernel.set(3, ocl::KernelArg::PtrReadOnly(uold_stride));
kernel.set(4, ocl::KernelArg::PtrReadOnly(unew_stride));
kernel.set(5, (int)_numAxes);
kernel.set(6, ocl::KernelArg::PtrWriteOnly(outputs[i]));
if (!kernel.run(1, &_count, NULL, false))
return false;
}
return true;
}
#endif
void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr)
{
CV_TRACE_FUNCTION();
CV_TRACE_ARG_VALUE(name, "name", name.c_str());
CV_OCL_RUN((preferableTarget == DNN_TARGET_OPENCL) &&
OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel()),
forward_ocl(inputs_arr, outputs_arr, internals_arr))
Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr);
}
@ -325,6 +380,10 @@ public:
std::vector<size_t> _newStride;
bool _needsPermute;
#ifdef HAVE_OPENCL
UMat uorder, uold_stride, unew_stride;
#endif
size_t _numAxes;
};

@ -0,0 +1,67 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
// License Agreement
// For Open Source Computer Vision Library
//
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//M*/
#define Dtype float
__kernel void permute(const int nthreads,
__global Dtype* bottom_data,
global int* permute_order,
global int* oldStride,
global int* newStride,
const int num_axes,
__global Dtype* top_data)
{
for (int i = get_global_id(0); i < nthreads; i += get_global_size(0))
{
int oldPosition = 0;
int newPosition = i;
for (int j = 0; j < num_axes; ++j)
{
int order = permute_order[j];
oldPosition += (newPosition / newStride[j]) * oldStride[order];
newPosition %= newStride[j];
}
top_data[i] = bottom_data[oldPosition];
}
}
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