def __init__(self, alpha=2.0, beta=4.0, sigmoid_clip_value=1e-4):
    """Constructor.

    Args:
      alpha: Focussing parameter of the focal loss. Increasing this will
        decrease the loss contribution of the well classified examples.
      beta: The local penalty reduction factor. Increasing this will decrease
        the contribution of loss due to negative pixels near the keypoint.
      sigmoid_clip_value: The sigmoid operation used internally will be clipped
        between [sigmoid_clip_value, 1 - sigmoid_clip_value)
    """
    self._alpha = alpha
    self._beta = beta
    self._sigmoid_clip_value = sigmoid_clip_value
    super(PenaltyReducedLogisticFocalLoss, self).__init__()
Constructor.

    Args:
      alpha: Focussing parameter of the focal loss. Increasing this will
        decrease the loss contribution of the well classified examples.
      beta: The local penalty reduction factor. Increasing this will decrease
        the contribution of loss due to negative pixels near the keypoint.
      sigmoid_clip_value: The sigmoid operation used internally will be clipped
        between [sigmoid_clip_value, 1 - sigmoid_clip_value)
    
inference_api/src/main/object_detection/core/losses.py