parameters: (self, buffer_size, seed=None)
return_statement: return ShuffleDataset(self, buffer_size, seed)
docstring: Randomly shuffles the elements of this dataset.
  
      Args:
        buffer_size: A `tf.int64` scalar `tf.Tensor`, representing the
          number of elements from this dataset from which the new
          dataset will sample.
        seed: (Optional.) A `tf.int64` scalar `tf.Tensor`, representing the
          random seed that will be used to create the distribution. See
          @{tf.set_random_seed} for behavior.
  
      Returns:
        A `Dataset`.
docstring_summary: Randomly shuffles the elements of this dataset.
docstring_tokens: Randomly shuffles the elements of this dataset .
function: def shuffle(self, buffer_size, seed=None):
      """Randomly shuffles the elements of this dataset.
  
      Args:
        buffer_size: A `tf.int64` scalar `tf.Tensor`, representing the
          number of elements from this dataset from which the new
          dataset will sample.
        seed: (Optional.) A `tf.int64` scalar `tf.Tensor`, representing the
          random seed that will be used to create the distribution. See
          @{tf.set_random_seed} for behavior.
  
      Returns:
        A `Dataset`.
      """
      return ShuffleDataset(self, buffer_size, seed)
function_tokens: def shuffle ( self , buffer_size , seed = None ) : return ShuffleDataset ( self , buffer_size , seed )