def test_values_correctly_set(self):
self.check_vals(self.scalars, [], 0, pt.format())
self.check_vals(self.order2, self.shape2, len(self.format2), self.format2)
self.check_vals(self.order5, self.shape5, len(self.format5), self.format5)
self.assertEqual(self.implicit_scalar[0], 0)
self.assertFalse(self.false_bool_tensor[0])
for i, tensor in enumerate(self.setScalar):
self.assertEqual(tensor[0], i)
def test_format_methods(self):
mfs = [pt.dense, pt.compressed, pt.compressed]
mf_ordering = [2, 0, 1]
fmt = pt.format(mfs, mf_ordering)
self.assertEqual(fmt.order, len(mf_ordering))
self.assertEqual(fmt.mode_formats, mfs)
self.assertEqual(fmt.mode_ordering, mf_ordering)
self.assertTrue(pt.csr != fmt)
self.assertTrue(fmt == fmt)
self.assertTrue(pt.csc == pt.csc)
self.assertFalse(pt.is_dense(pt.csc))
def einsum(subscripts,
*operands,
optimize=True,
out_format=formats.DenseFormat()):
if isinstance(out_format, formats.DenseFormat):
return pt.einsum(subscripts, *operands)
pt_mode_formats = [
TacoBackend.pt_format_dict[fmt] for fmt in out_format.mode_formats
]
pt_format = pt.format(pt_mode_formats, out_format.mode_order)
return pt.einsum(subscripts, *operands, out_format=pt_format)
def setUp(self):
self.shape2 = [10, 10]
self.shape5 = [4, 4, 4, 4, 4]
self.format2 = pt.csr
self.format5 = pt.format([pt.compressed]*5)
self.implicit_scalar = pt.tensor([])
self.false_bool_tensor = pt.tensor(False)
self.scalars = [pt.tensor(dtype=dt) for dt in types]
self.order2 = [pt.tensor(self.shape2, self.format2, dtype=dt) for dt in types]
self.order5 = [pt.tensor(self.shape5, pt.compressed, dt) for dt in types]
self.setScalar = [pt.tensor(i, dtype=dt) for i, dt in enumerate(types)]
self.c_array = np.array(np.arange(100).reshape([10, 10]), order='C')
self.f_array = np.array(np.arange(100).reshape([10, 10]), order='F')