code: def concat_from_sequence(
      input_sequence: Union[Tuple[torch.Tensor], List[torch.Tensor]],
      /,
      *,
      new_axis: int = 0,
      axis: int = 0,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      is_tuple = type(input_sequence) is tuple
      if is_tuple:
          input_sequence = list(input_sequence)
      if new_axis == 0:
          ret = torch.cat(input_sequence, dim=axis)
          return ret
      elif new_axis == 1:
          ret = torch.stack(input_sequence, dim=axis)
          return ret
  
imports: from typing import Iterable, Optional, Union, Sequence, Tuple, NamedTuple, List, Literal, Callable, Any
  from numbers import Number
  from collections import namedtuple
  import torch
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from ..None import backend_version
  import ivy
  from ivy.functional.ivy.experimental.manipulation import _to_tf_padding, _check_paddle_pad, _to_paddle_padding
label_desc: Use image node_id 26 for calling a global function with example usage: concat_from_sequence() and returns: ret, ret