(inputs, pad_idx)
return pad_mask
get padding mask from the input token idx
  inputs: [batch_size, time_steps]
  mask: [batch_size, time_steps, 1]
get padding mask from the input token idx
  inputs: [batch_size, time_steps]
  mask: [batch_size, time_steps, 1]
get padding mask from the input token idx inputs : [ batch_size time_steps ] mask : [ batch_size time_steps 1 ]
def get_expand_pad_mask(inputs, pad_idx):
  """
  get padding mask from the input token idx
  inputs: [batch_size, time_steps]
  mask: [batch_size, time_steps, 1]
  """
  pad_mask = tf.cast(tf.math.greater(inputs, pad_idx), tf.float32)
  pad_mask = tf.expand_dims(pad_mask, -1)
  return pad_mask
def get_expand_pad_mask ( inputs , pad_idx ) : pad_mask = tf . cast ( tf . math . greater ( inputs , pad_idx ) , tf . float32 ) pad_mask = tf . expand_dims ( pad_mask , - 1 ) return pad_mask