class_docstr: A mock class with implementation of abstract methods for testing.
code: def __init__(
      self,
      use_mock_loss_op: bool = False,
      feature_weight: Optional[Sequence[float]] = None,
      loss_weight: Optional[loss_functions.PerceptualLossWeight] = None,
  ):
      super().__init__(
          feature_weight=feature_weight, loss_weight=loss_weight
      )
      if use_mock_loss_op:
          self._loss_op = lambda x, y: tf.math.reduce_mean(x - y)
  
imports: import math
  import tempfile
  from typing import Dict, Optional, Sequence
  from unittest import mock
  from absl.testing import parameterized
  import tensorflow
  from mediapipe.model_maker.python.core.utils import loss_functions
label_desc: Use image node_id 1 to create a new MockPerceptualLoss object from inherited base classes: loss_functions with example: obj = MockPerceptualLoss(use_mock_loss_op, feature_weight, loss_weight)