code: def avg_pool1d(
      x,
      kernel_size,
      stride=None,
      padding=0,
      exclusive=True,
      ceil_mode=False,
      name=None,
  ):
      data_format = "NCW"
      exclusive = not exclusive
      if stride is None:
          stride = kernel_size
      kernel_size = _broadcast_pooling_helper(
          kernel_size, "1d", name="kernel_size"
      )
      padding = _broadcast_pooling_helper(padding, "1d", name="padding")
      # Figure out padding string
      if all(
          pad == ivy.ceil((kernel - 1) / 2)
          for kernel, pad in zip(kernel_size, padding)
      ):
          padding = "SAME"
      else:
          padding = "VALID"
  
      return ivy.avg_pool1d(
          x,
          kernel_size,
          stride,
          padding,
          count_include_pad=exclusive,
          ceil_mode=ceil_mode,
          data_format=data_format,
      )
  
file_path: ivy/ivy/functional/frontends/paddle/nn/functional/pooling.py
imports: import ivy
  from ivy.func_wrapper import with_supported_dtypes
  from ivy.functional.frontends.paddle.func_wrapper import to_ivy_arrays_and_back
  from ivy.functional.ivy.experimental.layers import _broadcast_pooling_helper
  from ivy.func_wrapper import with_unsupported_dtypes
label_desc: Use image node_id 5 for calling a global function with example usage: avg_pool1d(x, kernel_size, stride, padding, exclusive, ceil_mode, name) and returns: ivy