class TestCuSparsePreconditioners(CUDATestCase):
def setUp(self):
from pyculib.sparse import Sparse
self.cus = Sparse()
def test_Scsric0(self):
"""
Just exercise the codepath
"""
dtype = np.float32
m = n = 3
trans = 'N'
sary = scipy.sparse.rand(m, n, 0.75, format='csr', dtype=dtype)
nnz = sary.nnz
csrValM = sary.data
csrRowPtrA = sary.indptr
csrColIndA = sary.indices
descr = self.cus.matdescr(matrixtype='S')
info = self.cus.csrsv_analysis(trans, m, nnz, descr, csrValM,
csrRowPtrA, csrColIndA)
self.cus.csric0(trans, m, descr, csrValM, csrRowPtrA, csrColIndA, info)
def test_Scsrilu0(self):
"""
Just exercise the codepath
"""
dtype = np.float32
m = n = 3
trans = 'N'
sary = scipy.sparse.rand(m, n, 0.75, format='csr', dtype=dtype)
csrValM = sary.data
csrRowPtrA = sary.indptr
csrColIndA = sary.indices
descr = self.cus.matdescr()
info = self.cus.api.solve_analysis_info()
self.cus.csrilu0(trans, m, descr, csrValM, csrRowPtrA, csrColIndA,
info)
def test_Sgtsv(self):
"""
Just exercise the codepath
"""
dtype = np.float32
m = 4
n = 3
ldb = m
dl = np.asarray([3] * 8, dtype=dtype)
d = np.asarray([1] * 9, dtype=dtype)
du = np.asarray([4] * 8, dtype=dtype)
B = np.ones((m, n), dtype=dtype, order='F')
Bcopy = B.copy()
self.cus.gtsv(m, n, dl, d, du, B, ldb)
self.assertTrue(not np.all(B == Bcopy))
def test_Sgtsv_nopivot(self):
"""
Just exercise the codepath
"""
dtype = np.float32
m = 4
n = 3
ldb = m
dl = np.asarray([3] * 8, dtype=dtype)
d = np.asarray([1] * 9, dtype=dtype)
du = np.asarray([4] * 8, dtype=dtype)
B = np.ones((m, n), dtype=dtype, order='F')
Bcopy = B.copy()
self.cus.gtsv_nopivot(m, n, dl, d, du, B, ldb)
self.assertTrue(not np.all(B == Bcopy))
def test_SgtsvStridedBatch(self):
"""
Just exercise the codepath
"""
dtype = np.float32
batchCount = 1
batchStride = 4
m = 4
n = 3
dl = np.asarray([3] * 8, dtype=dtype)
d = np.asarray([1] * 9, dtype=dtype)
du = np.asarray([4] * 8, dtype=dtype)
x = np.ones((m, n), dtype=dtype, order='F')
xcopy = x.copy()
self.cus.gtsvStridedBatch(m, dl, d, du, x, batchCount, batchStride)
self.assertTrue(not np.all(x == xcopy))
class TestCuSparseLevel2(CUDATestCase):
def setUp(self):
from pyculib.sparse import Sparse
self.cus = Sparse()
def generic_test_bsrmv(self, dtype):
from pyculib.sparse import bsr_matrix
row = np.array([0, 0, 1, 2, 2, 2])
col = np.array([0, 2, 2, 0, 1, 2])
data = np.array([1, 2, 3, 4, 5, 6], dtype=dtype)
bsrmat = bsr_matrix((data, (row, col)), shape=(3, 3))
x = np.ones(3, dtype=dtype)
y = np.ones(3, dtype=dtype)
oldy = y.copy()
alpha = 1
beta = 1
descr = self.cus.matdescr()
self.cus.bsrmv_matrix('C', 'N', alpha, descr, bsrmat, x, beta, y)
self.assertFalse(np.all(y == oldy))
def test_Sbsrmv(self):
dtype = np.float32
self.generic_test_bsrmv(dtype=dtype)
def test_Cbsrmv(self):
dtype = np.complex64
self.generic_test_bsrmv(dtype=dtype)
def test_Sbsrxmv(self):
"""
Just exercise the codepath
"""
dtype = np.float32
alpha = 0
beta = 0
descr = self.cus.matdescr()
bsrVal = np.zeros(10, dtype=dtype)
bsrMaskPtr = np.zeros(10, dtype=np.int32)
bsrRowPtr = np.zeros(10, dtype=np.int32)
bsrEndPtr = np.zeros(10, dtype=np.int32)
bsrColInd = np.zeros(10, dtype=np.int32)
blockDim = 1
x = np.zeros(10, dtype=dtype)
y = np.zeros(10, dtype=dtype)
self.cus.bsrxmv('C', 'N', 1, 1, 1, 1, alpha, descr, bsrVal, bsrMaskPtr,
bsrRowPtr, bsrEndPtr, bsrColInd, blockDim, x, beta, y)
def test_Scsrmv(self):
"""
Just exercise the codepath
"""
dtype = np.float32
alpha = 0
beta = 0
descr = self.cus.matdescr()
csrVal = np.zeros(10, dtype=dtype)
csrColInd = np.zeros(10, dtype=np.int32)
csrRowPtr = np.zeros(10, dtype=np.int32)
x = np.zeros(10, dtype=dtype)
y = np.zeros(10, dtype=dtype)
trans = 'N'
m = 1
n = 1
nnz = 1
self.cus.csrmv(trans, m, n, nnz, alpha, descr, csrVal, csrRowPtr,
csrColInd, x, beta, y)
def test_Scsrmv(self):
"""
Just exercise the codepath
"""
dtype = np.float32
descr = self.cus.matdescr()
csrVal = np.zeros(10, dtype=dtype)
csrColInd = np.zeros(10, dtype=np.int32)
csrRowPtr = np.zeros(10, dtype=np.int32)
trans = 'N'
m = 1
nnz = 1
info = self.cus.csrsv_analysis(trans, m, nnz, descr, csrVal, csrRowPtr,
csrColInd)
alpha = 1.0
x = np.zeros(10, dtype=dtype)
y = np.zeros(10, dtype=dtype)
self.cus.csrsv_solve(trans, m, alpha, descr, csrVal, csrRowPtr,
csrColInd, info, x, y)