def todense(self, out=None, allocator=mem_alloc, stream=None):
if out is None:
out = gpuarray.empty(self.shape, allocator=allocator, dtype=self.dtype, order="C")
if self.nnz == 0: # weird but happens
out.fill(0.0, stream=stream)
return out
# we need to out-of-place transpose if we want rowmajor outputs
# thus we need a temporary to store our results
if out.flags.c_contiguous:
tmp = gpuarray.empty(self.shape, allocator=allocator, dtype=self.dtype, order="C")
else:
tmp = out
if stream is not None:
cusparse.cusparseSetStream(cusparse_handle, stream.handle)
cublas.cublasSetStream(cublas_handle, stream.handle)
cusparse.cusparseScsr2dense(cusparse_handle, self.shape[0],
self.shape[1], self.descr, self.data.gpudata, self.indptr.gpudata,
self.indices.gpudata, tmp.gpudata, tmp.shape[0])
if out.flags.c_contiguous:
cublas.cublasSgeam(cublas_handle, 1, 1, tmp.shape[1], tmp.shape[0],
1.0, tmp.gpudata, tmp.shape[0],
0.0, 0, tmp.shape[0], out.gpudata, out.shape[1])
if stream is not None:
cusparse.cusparseSetStream(cusparse_handle, 0)
cublas.cublasSetStream(cublas_handle, 0)
return out
def todense(self, out=None, allocator=mem_alloc, stream=None):
if out is None:
out = gpuarray.empty(self.shape, allocator=allocator, dtype=self.dtype, order="C")
if self.nnz == 0: # weird but happens
out.fill(0.0, stream=stream)
return out
# we need to out-of-place transpose if we want rowmajor outputs
# thus we need a temporary to store our results
if out.flags.c_contiguous:
tmp = gpuarray.empty(self.shape, allocator=allocator, dtype=self.dtype, order="C")
else:
tmp = out
if stream is not None:
cusparse.cusparseSetStream(cusparse_handle, stream.handle)
cublas.cublasSetStream(cublas_handle, stream.handle)
cusparse.cusparseScsr2dense(
cusparse_handle,
self.shape[0],
self.shape[1],
self.descr,
self.data.gpudata,
self.indptr.gpudata,
self.indices.gpudata,
tmp.gpudata,
tmp.shape[0],
)
if out.flags.c_contiguous:
cublas.cublasSgeam(
cublas_handle,
1,
1,
tmp.shape[1],
tmp.shape[0],
1.0,
tmp.gpudata,
tmp.shape[0],
0.0,
0,
tmp.shape[0],
out.gpudata,
out.shape[1],
)
if stream is not None:
cusparse.cusparseSetStream(cusparse_handle, 0)
cublas.cublasSetStream(cublas_handle, 0)
return out
def test_cusparseSetStream():
A = np.random.laplace(size=(3, 5)).astype(np.float32)
A[A<0.1] = 0
A = sparse.csr_matrix(A, dtype=np.float32)
A.sort_indices()
a_data = gpu.to_gpu(A.data)
a_indptr = gpu.to_gpu(A.indptr)
a_indices = gpu.to_gpu(A.indices)
out = gpu.empty((A.shape[0], A.shape[1]), dtype=A.dtype, order="F")
h = cusparse.cusparseCreate()
descrA = cusparse.cusparseCreateMatDescr()
stream = Stream()
cusparse.cusparseSetStream(h, stream.handle)
cusparse.cusparseScsr2dense(h, A.shape[0], A.shape[1],
descrA, a_data.gpudata, a_indptr.gpudata, a_indices.gpudata,
out.gpudata, out.shape[0])
cusparse.cusparseSetStream(h, 0)
stream.synchronize()
assert_allclose(out.get(), A.A, rtol=1e-4)
