code: def adaptive_avg_pool1d(input, output_size):
      return torch.nn.functional.adaptive_avg_pool1d(input, output_size)
  
imports: from typing import Optional, Union, Tuple, List, Literal, Sequence, Callable
  import torch
  import math
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  from ivy.functional.ivy.layers import _handle_padding, _get_num_padded_values, _validate_max_pool_params, _depth_max_pooling_helper
  from ivy.functional.ivy.experimental.layers import _padding_ceil_mode, _broadcast_pooling_helper
label_desc: Use image node_id 22 for calling a global function with example usage: adaptive_avg_pool1d(input, output_size) and returns: torch