def test_spmm_success(self):
ref_1, precision_1 = _create_mkl_sparse(self.mat1)
ref_2, precision_2 = _create_mkl_sparse(self.mat2)
self.assertTrue(precision_1)
self.assertTrue(precision_2)
ref_3 = _matmul_mkl(ref_1, ref_2)
mat3 = _export_mkl(ref_3, precision_1 or precision_2)
mat3_sp = self.mat1.dot(self.mat2)
mat3_np = np.dot(self.mat1.A, self.mat2.A)
npt.assert_array_almost_equal(mat3.A, mat3_sp.A)
npt.assert_array_almost_equal(mat3_np, mat3.A)
def test_spmm_success_float32(self):
self.mat1.data = self.mat1.data.astype(np.float32)
self.mat2.data = self.mat2.data.astype(np.float32)
ref_1, precision_1 = _create_mkl_sparse(self.mat1)
ref_2, precision_2 = _create_mkl_sparse(self.mat2)
self.assertFalse(precision_1)
self.assertFalse(precision_2)
ref_3 = _matmul_mkl(ref_1, ref_2)
mat3 = _export_mkl(ref_3,
precision_1 or precision_2,
output_type="csr")
mat3_sp = self.mat1.dot(self.mat2)
mat3_np = np.dot(self.mat1.A, self.mat2.A)
npt.assert_array_almost_equal(mat3.A, mat3_sp.A)
npt.assert_array_almost_equal(mat3_np, mat3.A)
def test_spmm_error_bad_handle(self):
with self.assertRaises(ValueError):
_matmul_mkl(sparse_matrix_t(), sparse_matrix_t())
def test_spmm_error_bad_dims(self):
ref_1, prec_1 = _create_mkl_sparse(self.mat1.transpose())
ref_2, prec_2 = _create_mkl_sparse(self.mat2)
with self.assertRaises(ValueError):
_matmul_mkl(ref_1, ref_2)