(d_model, d_ff, dropout, dropout_shared_axes,
                      mode, activation)
return [
      tl.Dense(d_ff),
      activation(),
      dropout,
      tl.Dense(d_model),
  ]
Returns a list of layers implementing a feed-forward block.

  Args:
    d_model: int:  depth of embedding
    d_ff: int: depth of feed-forward layer
    dropout: float: dropout rate (how much to drop out)
    dropout_shared_axes: list of integers, axes to share dropout mask
    mode: str: 'train' or 'eval'
    activation: the non-linearity in feed-forward layer

  Returns:
    A list of layers which maps vectors to vectors.
Returns a list of layers implementing a feed-forward block.
Returns a list of layers implementing a feed - forward block .
def _FeedForwardBlock(d_model, d_ff, dropout, dropout_shared_axes,
                      mode, activation):
  """Returns a list of layers implementing a feed-forward block.

  Args:
    d_model: int:  depth of embedding
    d_ff: int: depth of feed-forward layer
    dropout: float: dropout rate (how much to drop out)
    dropout_shared_axes: list of integers, axes to share dropout mask
    mode: str: 'train' or 'eval'
    activation: the non-linearity in feed-forward layer

  Returns:
    A list of layers which maps vectors to vectors.
  """
  dropout = tl.Dropout(
      rate=dropout, shared_axes=dropout_shared_axes, mode=mode)

  return [
      tl.Dense(d_ff),
      activation(),
      dropout,
      tl.Dense(d_model),
  ]
def _FeedForwardBlock ( d_model , d_ff , dropout , dropout_shared_axes , mode , activation ) : dropout = tl . Dropout ( rate = dropout , shared_axes = dropout_shared_axes , mode = mode ) return [ tl . Dense ( d_ff ) , activation ( ) , dropout , tl . Dense ( d_model ) , ]