(self, a, axis=None, partial=None, out=None, keepdims=True, binary=False)
return self.mean(op(a - self.mean(a, axis=axis)), axis=axis, out=out)
Calculates the variance of the elements along the specified
        axes.

        Arguments:
            a (Tensor): the Tensor on which to perform the operation
            axis (int, optional): the dimension along which to compute.
                                  If set to None, we will take var over all
                                  dimensions.  Defaults to None
            partial (bool, optional): Not currently used.
            out (Tensor, optional): where the result will be stored. If out is
                                    None, only the op-tree will be returned.
            keepdims (bool, optional): Keep the axes being computed over in the
                                       output (with size 1), instead of
                                       collapsing.  Defaults to True.

        Returns:
            OpTreeNode: the resulting op-tree
Calculates the variance of the elements along the specified
        axes.
Calculates the variance of the elements along the specified axes .
def var(self, a, axis=None, partial=None, out=None, keepdims=True, binary=False):
        """
        Calculates the variance of the elements along the specified
        axes.

        Arguments:
            a (Tensor): the Tensor on which to perform the operation
            axis (int, optional): the dimension along which to compute.
                                  If set to None, we will take var over all
                                  dimensions.  Defaults to None
            partial (bool, optional): Not currently used.
            out (Tensor, optional): where the result will be stored. If out is
                                    None, only the op-tree will be returned.
            keepdims (bool, optional): Keep the axes being computed over in the
                                       output (with size 1), instead of
                                       collapsing.  Defaults to True.

        Returns:
            OpTreeNode: the resulting op-tree
        """
        if binary:
            def self_shift(x):
                return self.shift(x, x)
            op = self_shift
        else:
            op = self.square

        if axis is None:
            return self.mean(op(a - self.mean(a)), out=out)
        return self.mean(op(a - self.mean(a, axis=axis)), axis=axis, out=out)
def var ( self , a , axis = None , partial = None , out = None , keepdims = True , binary = False ) : if binary : def self_shift ( x ) : return self . shift ( x , x ) op = self_shift else : op = self . square if axis is None : return self . mean ( op ( a - self . mean ( a ) ) , out = out ) return self . mean ( op ( a - self . mean ( a , axis = axis ) ) , axis = axis , out = out )