class_docstr: Parent class for 1D pooling layers with adaptive kernel size.
  
  This class only exists for code reuse. It will never be an exposed API.
  
  Args:
    reduce_function: The reduction method to apply, e.g. `tf.reduce_max`.
    output_size: An integer or tuple/list of a single integer, specifying pooled_features.
      The new size of output channels.
    data_format: A string,
      one of `channels_last` (default) or `channels_first`.
      The ordering of the dimensions in the inputs.
      `channels_last` corresponds to inputs with shape
      `(batch, steps, features)` while `channels_first`
      corresponds to inputs with shape
      `(batch, features, steps)`.
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code: def get_config(self):
      config = {
          "output_size": self.output_size,
          "data_format": self.data_format,
      }
      base_config = super().get_config()
      return {**base_config, **config}
  
imports: import tensorflow
  import tensorflow_addons.utils.keras_utils
  from typeguard import typechecked
  from typing import Union, Callable, Iterable
label_desc: Use image node_id 4 for calling the AdaptivePooling1D obj's underlying member method code with example usage: obj.get_config() and returns: dict