'Instantiate a new instance of this backend\'s Tensor class, populating
each element with a value of 1.
Arguments:
shape (int, list): length of each dimension of the Tensor.
dtype (data-type, optional): If present, specifies the underlying
type to employ for each element.
name (str, optional): name indentifying the tensor (used in printing).
persist_values (bool, optional): If set to True (the default), the
values assigned to this Tensor
will persist across multiple begin
and end calls.  Setting to False
may provide a performance increase
if values do not need to be
maintained across such calls
parallel (bool, optional): If True and using multi-GPU backend,
replicate copies of this tensor across
devices.  Defaults to False, and has no
effect on CPU, or (single) GPU backends.
distributed (bool, optional): If True and using multi-GPU backend,
this tensor is fragmented and
partitioned across devices.  Defaults
to False, and has no effect on CPU,
or (single) GPU backends.
Returns:
Tensor: array object
Raises:
NotImplementedError: Can\'t be instantiated directly.
See Also:
:py:func:`~neon.backends.backend.Backend.empty`,
:py:func:`~neon.backends.backend.Backend.zeros`,
:py:func:`~neon.backends.backend.Backend.array`'

@abc.abstractmethod
def ones(self, shape, dtype=None, name=None, persist_values=True, parallel=False, distributed=False):

    raise NotImplementedError()
