def test_parse_tensor(self):
# Zero-rank tensor
attr = attr_value.AttrValue()
attr.tensor.version_number = 1
attr.tensor.dtype = types.DataType.DT_INT32
t = parse.parse_attr(attr)
self.assertTrue(isinstance(t, mil_types.int32))
self.assertEqual(0, t.val)
# Non-zero rank
attr = attr_value.AttrValue()
attr.tensor.version_number = 1
attr.tensor.dtype = types.DataType.DT_INT32
shaped_attr = self._attr_with_shape([(1, "outer"), (2, "middle"),
(3, "inner")])
attr.tensor.tensor_shape.dim.extend(shaped_attr.shape.dim)
attr.tensor.int_val.extend([55, 56, 57])
t = parse.parse_attr(attr)
self.assertEqual([55, 56, 57], t.val.tolist())
self.assertEqual("tensor", mil_types.get_type_info(t).name)
# Note that the result of t.get_primitive() is a function that returns a type
# rather than an instance of that type as it is when the tensor has rank zero.
self.assertTrue(isinstance(t.get_primitive()(), mil_types.int32))
self.assertEqual((1, 2, 3), t.get_shape())
def compare(expected, lst, field_name):
attr = attr_value.AttrValue()
field = getattr(attr.list, field_name)
field.extend(lst)
actual = parse.parse_attr(attr)
self.assertEqual(expected, actual)
def test_parse_scalar(self):
def compare(expected, val, field_name):
a = attr_value.AttrValue()
setattr(a, field_name, val)
actual = parse.parse_attr(a)
self.assertEqual(expected, actual)
compare("a String", b"a String", "s")
compare(55, 55, "i")
compare(True, True, "b")
attr = attr_value.AttrValue()
attr.f = 12.3
self.assertAlmostEqual(12.3, parse.parse_attr(attr), places=2)
def compare(expected, tf_type):
attr = attr_value.AttrValue()
attr.type = tf_type
self.assertEqual(expected, parse.parse_attr(attr))
def compare(expected, dims, unknown_rank=0):
attr = self._attr_with_shape(dims, unknown_rank)
actual = parse.parse_attr(attr)
self.assertEqual(expected, actual)
def compare(expected, val, field_name):
a = attr_value.AttrValue()
setattr(a, field_name, val)
actual = parse.parse_attr(a)
self.assertEqual(expected, actual)
