(self, ary, dtype=None, name=None, persist_values=True)
return self.tensor_cls(
            backend=self,
            ary=np.zeros(ary.shape, dtype),
            dtype=dtype,
            name=name,
            persist_values=persist_values)
Instantiate a new instance of this backend's Tensor class, with the
        shape taken from ary.

        Arguments:
            ary (tensor object): Tensor to inherit the dimensions of.
            dtype (data-type, optional): If present, specifies the underlying
                                         type to employ for each element.
            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
        Returns:
            Tensor: array object
Instantiate a new instance of this backend's Tensor class, with the
        shape taken from ary.
Instantiate a new instance of this backend s Tensor class with the shape taken from ary .
def empty_like(self, ary, dtype=None, name=None, persist_values=True):
        """
        Instantiate a new instance of this backend's Tensor class, with the
        shape taken from ary.

        Arguments:
            ary (tensor object): Tensor to inherit the dimensions of.
            dtype (data-type, optional): If present, specifies the underlying
                                         type to employ for each element.
            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
        Returns:
            Tensor: array object
        """
        dtype = self.default_dtype if dtype is None else dtype
        return self.tensor_cls(
            backend=self,
            ary=np.zeros(ary.shape, dtype),
            dtype=dtype,
            name=name,
            persist_values=persist_values)
def empty_like ( self , ary , dtype = None , name = None , persist_values = True ) : dtype = self . default_dtype if dtype is None else dtype return self . tensor_cls ( backend = self , ary = np . zeros ( ary . shape , dtype ) , dtype = dtype , name = name , persist_values = persist_values )