def __init__(self, axis=0, prepend=None, append=None):
if prepend is not None:
prepend = cde.Tensor(np.array(prepend))
if append is not None:
append = cde.Tensor(np.array(append))
super().__init__(axis, prepend, append)
def __init__(self, fill_value):
super().__init__(cde.Tensor(np.array(fill_value)))
def __init__(self, operator, constant, dtype=mstype.bool_):
dtype = mstype_to_detype(dtype)
constant = cde.Tensor(np.array(constant))
super().__init__(DE_C_RELATIONAL[operator], constant, dtype)
def __init__(self, pad_shape, pad_value=None):
if pad_value is not None:
pad_value = cde.Tensor(np.array(pad_value))
super().__init__(cde.TensorShape(pad_shape), pad_value)
def test_basic():
x = np.array([["ab", "cde", "121"], ["x", "km", "789"]], dtype='S')
n = cde.Tensor(x)
arr = n.as_array()
np.testing.assert_array_equal(x, arr)
def __init__(self, axis=0, prepend=None, append=None):
self.axis = axis
self.prepend = cde.Tensor(
np.array(prepend)) if prepend is not None else prepend
self.append = cde.Tensor(
np.array(append)) if append is not None else append
def __init__(self, pad_shape, pad_value=None):
self.pad_shape = cde.TensorShape(pad_shape)
self.pad_value = cde.Tensor(
np.array(pad_value)) if pad_value is not None else pad_value
def __init__(self, operator, constant, dtype=mstype.bool_):
self.operator = operator
self.dtype = mstype_to_detype(dtype)
self.constant = cde.Tensor(np.array(constant))
def __init__(self, fill_value):
self.fill_value = cde.Tensor(np.array(fill_value))