def _matmul_mkl(sp_ref_a, sp_ref_b):
"""
Dot product two MKL objects together and return a handle to the result
:param sp_ref_a: Sparse matrix A handle
:type sp_ref_a: sparse_matrix_t
:param sp_ref_b: Sparse matrix B handle
:param sp_ref_b: sparse_matrix_t
:return: Sparse matrix handle that is the dot product A * B
:rtype: sparse_matrix_t
"""
ref_handle = sparse_matrix_t()
ret_val = MKL._mkl_sparse_spmm(_ctypes.c_int(10), sp_ref_a, sp_ref_b,
_ctypes.byref(ref_handle))
# Check return
if ret_val != 0:
_err_msg = "mkl_sparse_spmm returned {v} ({e})".format(
v=ret_val, e=RETURN_CODES[ret_val])
if ret_val == 2:
_err_msg += "; Try changing MKL to int64 with the environment variable MKL_INTERFACE_LAYER=ILP64"
raise ValueError(_err_msg)
return ref_handle
def test_empty_handle(self):
mkl_handle_empty = sparse_matrix_t()
with self.assertRaises(ValueError):
_export_mkl(mkl_handle_empty, True, output_type="csr")
with self.assertRaises(ValueError):
_convert_to_csr(mkl_handle_empty)
with self.assertRaises(ValueError):
_order_mkl_handle(mkl_handle_empty)
with self.assertRaises(ValueError):
_destroy_mkl_handle(mkl_handle_empty)
def _gram_matrix_sparse(matrix_a, aat=False, reorder_output=False):
"""
Calculate the gram matrix aTa for sparse matrix and return a sparse matrix
:param matrix_a: Sparse matrix
:type matrix_a: scipy.sparse.csr_matrix, scipy.sparse.csc_matrix
:param aat: Return A (dot) AT instead of AT (dot) A
:type aat: bool
:param reorder_output:
:type reorder_output: bool
:return: Sparse matrix
:rtype: scipy.sparse.csr_matrix
"""
sp_ref_a, double_prec = _create_mkl_sparse(matrix_a)
if _sps.isspmatrix_csc(matrix_a):
sp_ref_a = _convert_to_csr(sp_ref_a)
_order_mkl_handle(sp_ref_a)
ref_handle = sparse_matrix_t()
ret_val = MKL._mkl_sparse_syrk(10 if aat else 11, sp_ref_a,
_ctypes.byref(ref_handle))
# Check return
if ret_val != 0:
_err_msg = "mkl_sparse_syrk returned {v} ({e})".format(
v=ret_val, e=RETURN_CODES[ret_val])
if ret_val == 2:
_err_msg += "; Try changing MKL to int64 with the environment variable MKL_INTERFACE_LAYER=ILP64"
raise ValueError(_err_msg)
if reorder_output:
_order_mkl_handle(ref_handle)
output_arr = _export_mkl(ref_handle, double_prec, output_type="csr")
_destroy_mkl_handle(sp_ref_a)
_destroy_mkl_handle(ref_handle)
return output_arr
def _syrk_mkl(sp_ref_a):
"""
Dot product an MKL object with its transpose and return a handle to the result
:param sp_ref_a: Sparse matrix A handle
:type sp_ref_a: sparse_matrix_t
:return: Sparse matrix handle that is the dot product A * A.T
:rtype: sparse_matrix_t
"""
ref_handle = sparse_matrix_t()
ret_val = MKL._mkl_sparse_syrk(_ctypes.c_int(10), sp_ref_a,
_ctypes.byref(ref_handle))
# Check return
if ret_val != 0:
raise ValueError("mkl_sparse_spmm returned {v} ({e})".format(
v=ret_val, e=RETURN_CODES[ret_val]))
return ref_handle
def _matmul_mkl(sp_ref_a, sp_ref_b):
"""
Dot product two MKL objects together and return a handle to the result
:param sp_ref_a: Sparse matrix A handle
:type sp_ref_a: sparse_matrix_t
:param sp_ref_b: Sparse matrix B handle
:param sp_ref_b: sparse_matrix_t
:return: Sparse matrix handle that is the dot product A * B
:rtype: sparse_matrix_t
"""
ref_handle = sparse_matrix_t()
ret_val = MKL._mkl_sparse_spmm(_ctypes.c_int(10), sp_ref_a, sp_ref_b,
_ctypes.byref(ref_handle))
# Check return
if ret_val != 0:
raise ValueError("mkl_sparse_spmm returned {v} ({e})".format(
v=ret_val, e=RETURN_CODES[ret_val]))
return ref_handle
def test_spmm_error_bad_handle(self):
with self.assertRaises(ValueError):
_matmul_mkl(sparse_matrix_t(), sparse_matrix_t())