tensorflow_ranking/python/keras/losses.py [211:239]:
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  def __init__(self,
               reduction=tf.losses.Reduction.AUTO,
               name=None,
               lambda_weight=None,
               temperature=1.0,
               ragged=False,
               **kwargs):
    super().__init__(reduction, name, ragged)
    self._lambda_weight = lambda_weight
    self._temperature = temperature

  def get_config(self):
    config = super().get_config()
    config.update({
        'lambda_weight':
            tf.keras.utils.serialize_keras_object(self._lambda_weight),
        'temperature':
            self._temperature,
    })
    return config

  @classmethod
  def from_config(cls, config, custom_objects=None):
    config = config.copy()
    config.update({
        'lambda_weight':
            tf.keras.utils.deserialize_keras_object(config['lambda_weight']),
    })
    return cls(**config)
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tensorflow_ranking/python/keras/losses.py [458:486]:
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  def __init__(self,
               reduction=tf.losses.Reduction.AUTO,
               name=None,
               lambda_weight=None,
               temperature=1.0,
               ragged=False,
               **kwargs):
    super().__init__(reduction, name, ragged)
    self._lambda_weight = lambda_weight
    self._temperature = temperature

  def get_config(self):
    config = super().get_config()
    config.update({
        'lambda_weight':
            tf.keras.utils.serialize_keras_object(self._lambda_weight),
        'temperature':
            self._temperature,
    })
    return config

  @classmethod
  def from_config(cls, config, custom_objects=None):
    config = config.copy()
    config.update({
        'lambda_weight':
            tf.keras.utils.deserialize_keras_object(config['lambda_weight']),
    })
    return cls(**config)
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