void weightedMeanAllTest(af::dim4 dims)
{
typedef typename meanOutType<T>::type outType;
if (noDoubleTests<T>()) return;
if (noDoubleTests<outType>()) return;
if (noDoubleTests<wtsType>()) return;
using af::array;
using af::mean;
std::srand(std::time(0));
vector<T> data(dims.elements());
vector<wtsType> wts(dims.elements());
std::generate(data.begin(), data.end(), random<T>);
std::generate(wts.begin(), wts.end(), random<wtsType>);
outType wtdSum = outType(0);
wtsType wtsSum = wtsType(0);
for(int i = 0; i < (int)data.size(); i++) {
wtdSum = wtdSum + data[i]*wts[i];
wtsSum = wtsSum + wts[i];
}
outType gold = wtdSum / wtsSum;
array a(dims, &(data.front()));
array w(dims, &(wts.front()));
outType output = mean<outType>(a, w);
ASSERT_NEAR(::real(output), ::real(gold), 1.0e-2);
ASSERT_NEAR(::imag(output), ::imag(gold), 1.0e-2);
}
Array<T>::Array(af::dim4 dims, const T * const in_data, bool is_device) :
info(getActiveDeviceId(), dims, af::dim4(0,0,0,0), calcStrides(dims), (af_dtype)dtype_traits<T>::af_type),
data((is_device ? (T *)in_data : memAlloc<T>(dims.elements())), memFree<T>),
data_dims(dims),
node(), offset(0), ready(true), owner(true)
{
#if __cplusplus > 199711L
static_assert(std::is_standard_layout<Array<T>>::value, "Array<T> must be a standard layout type");
static_assert(offsetof(Array<T>, info) == 0, "Array<T>::info must be the first member variable of Array<T>");
#endif
if (!is_device) {
CUDA_CHECK(cudaMemcpy(data.get(), in_data, dims.elements() * sizeof(T), cudaMemcpyHostToDevice));
}
}
static Array<T> diff(const Array<T> &in, const int dim)
{
const af::dim4 iDims = in.dims();
af::dim4 oDims = iDims;
oDims[dim] -= (isDiff2 + 1);
if(iDims.elements() == 0 || oDims.elements() == 0) {
throw std::runtime_error("Elements are 0");
}
Array<T> out = createEmptyArray<T>(oDims);
switch (dim) {
case (0): kernel::diff<T, 0, isDiff2>(out, in, in.ndims());
break;
case (1): kernel::diff<T, 1, isDiff2>(out, in, in.ndims());
break;
case (2): kernel::diff<T, 2, isDiff2>(out, in, in.ndims());
break;
case (3): kernel::diff<T, 3, isDiff2>(out, in, in.ndims());
break;
}
return out;
}
af_err af_tile(af_array *out, const af_array in, const af::dim4 &tileDims)
{
try {
ArrayInfo info = getInfo(in);
af_dtype type = info.getType();
if(info.ndims() == 0) {
return af_retain_array(out, in);
}
DIM_ASSERT(1, info.dims().elements() > 0);
DIM_ASSERT(2, tileDims.elements() > 0);
af_array output;
switch(type) {
case f32: output = tile<float >(in, tileDims); break;
case c32: output = tile<cfloat >(in, tileDims); break;
case f64: output = tile<double >(in, tileDims); break;
case c64: output = tile<cdouble>(in, tileDims); break;
case b8: output = tile<char >(in, tileDims); break;
case s32: output = tile<int >(in, tileDims); break;
case u32: output = tile<uint >(in, tileDims); break;
case s64: output = tile<intl >(in, tileDims); break;
case u64: output = tile<uintl >(in, tileDims); break;
case s16: output = tile<short >(in, tileDims); break;
case u16: output = tile<ushort >(in, tileDims); break;
case u8: output = tile<uchar >(in, tileDims); break;
default: TYPE_ERROR(1, type);
}
std::swap(*out,output);
}
CATCHALL;
return AF_SUCCESS;
}
Array<T> resize(const Array<T> &in, const dim_type odim0, const dim_type odim1,
const af_interp_type method)
{
if ((std::is_same<T, double>::value || std::is_same<T, cdouble>::value) &&
!isDoubleSupported(getActiveDeviceId())) {
OPENCL_NOT_SUPPORTED();
}
const af::dim4 iDims = in.dims();
af::dim4 oDims(odim0, odim1, iDims[2], iDims[3]);
if(iDims.elements() == 0 || oDims.elements() == 0) {
throw std::runtime_error("Elements is 0");
}
Array<T> out = createEmptyArray<T>(oDims);
switch(method) {
case AF_INTERP_NEAREST:
kernel::resize<T, AF_INTERP_NEAREST> (out, in);
break;
case AF_INTERP_BILINEAR:
kernel::resize<T, AF_INTERP_BILINEAR>(out, in);
break;
default:
break;
}
return out;
}
Array<T>::Array(af::dim4 dims, const T * const in_data, bool is_device, bool copy_device) :
info(getActiveDeviceId(), dims, 0, calcStrides(dims), (af_dtype)dtype_traits<T>::af_type),
data(((is_device & !copy_device) ? const_cast<T*>(in_data) : memAlloc<T>(dims.elements()).release()), memFree<T>),
data_dims(dims),
node(bufferNodePtr<T>()), ready(true), owner(true)
{
#if __cplusplus > 199711L
static_assert(std::is_standard_layout<Array<T>>::value, "Array<T> must be a standard layout type");
static_assert(offsetof(Array<T>, info) == 0, "Array<T>::info must be the first member variable of Array<T>");
#endif
if (!is_device) {
CUDA_CHECK(cudaMemcpyAsync(data.get(), in_data, dims.elements() * sizeof(T),
cudaMemcpyHostToDevice, cuda::getActiveStream()));
CUDA_CHECK(cudaStreamSynchronize(cuda::getActiveStream()));
} else if (copy_device) {
CUDA_CHECK(cudaMemcpyAsync(data.get(), in_data, dims.elements() * sizeof(T),
cudaMemcpyDeviceToDevice, cuda::getActiveStream()));
CUDA_CHECK(cudaStreamSynchronize(cuda::getActiveStream()));
}
}
void testCPPMean(T const_value, af::dim4 dims)
{
typedef typename meanOutType<T>::type outType;
if (noDoubleTests<T>()) return;
using af::array;
using af::mean;
vector<T> hundred(dims.elements(), const_value);
outType gold = outType(0);
//for(auto i:hundred) gold += i;
for(int i = 0; i < (int)hundred.size(); i++) {
gold += hundred[i];
}
gold /= dims.elements();
array a(dims, &(hundred.front()));
outType output = mean<outType>(a);
ASSERT_NEAR(::real(output), ::real(gold), 1.0e-3);
ASSERT_NEAR(::imag(output), ::imag(gold), 1.0e-3);
}
Array<T> tile(const Array<T> &in, const af::dim4 &tileDims)
{
const af::dim4 iDims = in.dims();
af::dim4 oDims = iDims;
oDims *= tileDims;
if(iDims.elements() == 0 || oDims.elements() == 0) {
throw std::runtime_error("Elements are 0");
}
Array<T> out = createEmptyArray<T>(oDims);
T* outPtr = out.get();
const T* inPtr = in.get();
const af::dim4 ist = in.strides();
const af::dim4 ost = out.strides();
for(dim_t ow = 0; ow < oDims[3]; ow++) {
const dim_t iw = ow % iDims[3];
const dim_t iW = iw * ist[3];
const dim_t oW = ow * ost[3];
for(dim_t oz = 0; oz < oDims[2]; oz++) {
const dim_t iz = oz % iDims[2];
const dim_t iZW = iW + iz * ist[2];
const dim_t oZW = oW + oz * ost[2];
for(dim_t oy = 0; oy < oDims[1]; oy++) {
const dim_t iy = oy % iDims[1];
const dim_t iYZW = iZW + iy * ist[1];
const dim_t oYZW = oZW + oy * ost[1];
for(dim_t ox = 0; ox < oDims[0]; ox++) {
const dim_t ix = ox % iDims[0];
const dim_t iMem = iYZW + ix;
const dim_t oMem = oYZW + ox;
outPtr[oMem] = inPtr[iMem];
}
}
}
}
return out;
}
void testCPPVar(T const_value, af::dim4 dims)
{
typedef typename varOutType<T>::type outType;
if (noDoubleTests<T>()) return;
if (noDoubleTests<outType>()) return;
using af::array;
using af::var;
vector<T> hundred(dims.elements(), const_value);
outType gold = outType(0);
array a(dims, &(hundred.front()));
outType output = var<outType>(a, false);
ASSERT_NEAR(::real(output), ::real(gold), 1.0e-3);
ASSERT_NEAR(::imag(output), ::imag(gold), 1.0e-3);
output = var<outType>(a, true);
ASSERT_NEAR(::real(output), ::real(gold), 1.0e-3);
ASSERT_NEAR(::imag(output), ::imag(gold), 1.0e-3);
gold = outType(2.5);
outType tmp[] = { outType(0), outType(1), outType(2), outType(3),
outType(4) };
array b(5, tmp);
output = var<outType>(b, false);
ASSERT_NEAR(::real(output), ::real(gold), 1.0e-3);
ASSERT_NEAR(::imag(output), ::imag(gold), 1.0e-3);
gold = outType(2);
output = var<outType>(b, true);
ASSERT_NEAR(::real(output), ::real(gold), 1.0e-3);
ASSERT_NEAR(::imag(output), ::imag(gold), 1.0e-3);
}
size_t elements() const { return dim_size.elements(); }
Array<T>::Array(af::dim4 dims) :
info(getActiveDeviceId(), dims, 0, calcStrides(dims), (af_dtype)dtype_traits<T>::af_type),
data((dims.elements() ? memAlloc<T>(dims.elements()).release() : nullptr), memFree<T>), data_dims(dims),
node(bufferNodePtr<T>()), ready(true), owner(true)
{}
Array<T>::Array(af::dim4 dims) :
info(getActiveDeviceId(), dims, af::dim4(0,0,0,0), calcStrides(dims), (af_dtype)dtype_traits<T>::af_type),
data(memAlloc<T>(dims.elements()), memFree<T>), data_dims(dims),
node(), offset(0), ready(true), owner(true)
{}
