class_docstr: Compute the quantile regression loss for the distributional TD error.
docstr: Initializes the module.
  
  Args:
    huber_param: The point where the huber loss function changes from a
      quadratic to linear.
    name: name to use for grouping operations.
code: def __init__(
      self, huber_param: float = 0.0, name: str = "NUQuantileRegression"
  ):
      """Initializes the module.
  
      Args:
        huber_param: The point where the huber loss function changes from a
          quadratic to linear.
        name: name to use for grouping operations.
      """
      super().__init__(name=name)
      self._huber_param = huber_param
  
file_path: acme/acme/tf/losses/quantile.py
imports: from typing import NamedTuple
  from .huber import huber
  import sonnet
  import tensorflow
label_desc: Use image node_id 1 to create a new NonUniformQuantileRegression object from inherited base classes: snt with example: obj = NonUniformQuantileRegression(huber_param, name)