Formatting changes

    import torch

    return torch.nn.L1Loss(reduction='none')

class HuberLoss(Loss):

  """Smoothened version of L1 loss.

  Less sensitive to small errors than L1, becomes linear in error for larger errors.

  When delta = 1.0 (default), this loss is equivalent to SmoothL1Loss.

  """

  def _compute_tf_loss(self, output, labels):

    import tensorflow as tf

    output, labels = _make_tf_shapes_consistent(output, labels)

    return tf.keras.losses.Huber(reduction="none")(labels, output)

  def _create_pytorch_loss(self):

    import torch

    return torch.nn.SmoothL1Loss(reduction='none')

class L2Loss(Loss):

  """The squared difference between the true and predicted values."""