divide the gradient by the remaining number of nodes. This
           ensures parity with training on a smaller "world_size"
           although it also means the uneven inputs would contribute
           more towards the global gradient. Typically, you would want
           to set this to "True" for cases where the last few inputs
           of your training job are uneven. In extreme cases, where
           there is a large discrepancy in the number of inputs,
           setting this to "False" might provide better results.
     * **enable** (*bool*) -- Whether to enable uneven input
       detection or not. Pass in "enable=False" to disable in
       cases where you know that inputs are even across
       participating processes. Default is "True".

     * **throw_on_early_termination** (*bool*) -- Whether to throw
       an error or continue training when at least one rank has
       exhausted inputs. If "True", will throw upon the first rank
