code: def ShiftRight(n_positions=1, mode="train"):
      """Returns a layer that can insert padding to shift the input sequence.
  
      Args:
        n_positions: Number of positions to shift the input sequence rightward;
            initial positions freed by the shift get padded with zeros. Applies
            only if layer is created in a non-``'eval'`` mode.
        mode: One of ``'train'``, ``'eval'``, or ``'predict'``.
      """
  
      # TODO(jonni): Include pad arg, like PaddingMask, to allow non-default pads?
      def f(x):
          if mode == "predict":
              return x
          padded = _zero_pad(x, (n_positions, 0), 1)
          return padded[:, :-n_positions]
  
      return Fn(f"ShiftRight({n_positions})", f)
  
imports: import numpy
  from trax import fastmath
  from trax.fastmath import numpy
  from trax.layers import base
  from trax.layers import combinators
  from trax.layers import convolution
  from trax.layers import core
  from trax.layers import initializers
  from trax.layers.assert_shape import assert_shape
  from trax.layers.base import Fn
  from trax.layers.research import sparsity
label_desc: Use image node_id 9 for calling a global function with example usage: ShiftRight(n_positions, mode) and returns: Fn, padded, x