<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _td_array_cmp(cls, op):
 """ Wrap comparison operations to convert timedelta-like to timedelta64 """

    opname = '__{name}__'.format(name=op.__name__)
    nat_result = opname == '__ne__'

    def wrapper(self, other):
        if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
            return NotImplemented

        if _is_convertible_to_td(other) or other is NaT:
            try:
                other = Timedelta(other)
            except ValueError:
                # failed to parse as timedelta
                return ops.invalid_comparison(self, other, op)

            result = op(self.view('i8'), other.value)
            if isna(other):
                result.fill(nat_result)

        elif not is_list_like(other):
            return ops.invalid_comparison(self, other, op)

        elif len(other) != len(self):
            raise ValueError("Lengths must match")

        else:
            try:
                other = type(self)._from_sequence(other)._data
            except (ValueError, TypeError):
                return ops.invalid_comparison(self, other, op)

            result = op(self.view('i8'), other.view('i8'))
            result = com.values_from_object(result)

            o_mask = np.array(isna(other))
            if o_mask.any():
                result[o_mask] = nat_result

        if self._hasnans:
            result[self._isnan] = nat_result

        return result

    return compat.set_function_name(wrapper, opname, cls)