parameters: (packed_sequences)
return_statement: return unpacked_sequences
docstring: r"""Unpacks PackedSequence into a list of variable length Tensors
  
      ``packed_sequences`` should be a PackedSequence object.
  
  
      Example:
          >>> from torch.nn.utils.rnn import pack_sequence, unpack_sequence
          >>> a = torch.tensor([1,2,3])
          >>> b = torch.tensor([4,5])
          >>> c = torch.tensor([6])
          >>> sequences = [a, b, c]
          [tensor([ 1,  2,  3]), tensor([ 4,  5]), tensor([ 6])]
          >>> packed_sequences = pack_sequence(sequences)
          PackedSequence(data=tensor([ 1,  4,  6,  2,  5,  3]), batch_sizes=tensor([ 3,  2,  1]))
          >>> unpacked_sequences = unpack_sequence(packed_sequences)
          [tensor([ 1,  2,  3]), tensor([ 4,  5]), tensor([ 6])]
  
  
      Args:
          packed_sequences (PackedSequence): A PackedSequence object.
  
      Returns:
          a list of :class:`Tensor` objects
docstring_summary: r"""Unpacks PackedSequence into a list of variable length Tensors
docstring_tokens: r Unpacks PackedSequence into a list of variable length Tensors
function: def unpack_sequence(packed_sequences):
      # type: (PackedSequence) -> List[Tensor]
      r"""Unpacks PackedSequence into a list of variable length Tensors
  
      ``packed_sequences`` should be a PackedSequence object.
  
  
      Example:
          >>> from torch.nn.utils.rnn import pack_sequence, unpack_sequence
          >>> a = torch.tensor([1,2,3])
          >>> b = torch.tensor([4,5])
          >>> c = torch.tensor([6])
          >>> sequences = [a, b, c]
          [tensor([ 1,  2,  3]), tensor([ 4,  5]), tensor([ 6])]
          >>> packed_sequences = pack_sequence(sequences)
          PackedSequence(data=tensor([ 1,  4,  6,  2,  5,  3]), batch_sizes=tensor([ 3,  2,  1]))
          >>> unpacked_sequences = unpack_sequence(packed_sequences)
          [tensor([ 1,  2,  3]), tensor([ 4,  5]), tensor([ 6])]
  
  
      Args:
          packed_sequences (PackedSequence): A PackedSequence object.
  
      Returns:
          a list of :class:`Tensor` objects
      """
  
      padded_sequences, lengths = pad_packed_sequence(packed_sequences, batch_first=True)
      unpacked_sequences = unpad_sequence(padded_sequences, lengths, batch_first=True)
      return unpacked_sequences
function_tokens: def unpack_sequence ( packed_sequences ) : # type: (PackedSequence) -> List[Tensor] padded_sequences , lengths = pad_packed_sequence ( packed_sequences , batch_first = True ) unpacked_sequences = unpad_sequence ( padded_sequences , lengths , batch_first = True ) return unpacked_sequences