class_docstr: Univariate scorer using GAM.
  
  The scorer implements Neural Generalized Additive Ranking Model, which is an
  additive ranking model.
  See the [paper](https://arxiv.org/abs/2005.02553) for more details.
  
  Example usage:
  
  ```python
  scorer=GAMScorer(hidden_layer_dims=[16])
  ```
docstr: Initializes the instance.
  
  Args:
    **gam_kwargs: A dict of keyward arguments for GAM layers. Please see
      `tfr.keras.layers.GAMlayer` for specific list of keyword arguments.
docstr_tok: ["Initializes","the","instance",".","Args",":","*","*","gam_kwargs",":","A","dict","of","keyward","arguments","for","GAM","layers",".","Please","see","`","tfr.keras.layers.GAMlayer","`","for","specific","list","of","keyword","arguments","."]
code: def __init__(self, **gam_kwargs):
      """Initializes the instance.
  
      Args:
        **gam_kwargs: A dict of keyward arguments for GAM layers. Please see
          `tfr.keras.layers.GAMlayer` for specific list of keyword arguments.
      """
      self._gam_kwargs = gam_kwargs
  
imports: import abc
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  from absl import logging
  import tensorflow
  from tensorflow_ranking.python.keras import feature
  from tensorflow_ranking.python.keras import layers
label_desc: Use image node_id 1 to create a new GAMScorer object from inherited base classes: UnivariateScorer with example: obj = GAMScorer()