code: def _get_total_loss_tensor(self, activations):
      losses = []
      for activation in activations:
          losses.append(
              math_ops.reduce_mean(
                  math_ops.reduce_sum(
                      gen_math_ops.squared_difference(activation, 0),
                      axis=-1,
                  )
              )
          )
      total_loss = array_ops.expand_dims_v2(sum(losses), 0)
      return total_loss
  
imports: import os
  from typing import Tuple
  from absl import flags
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import tpu_strategy
  from tensorflow.python.distribute.cluster_resolver import tpu_cluster_resolver
  from tensorflow.python.eager import remote
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import init_ops_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
  from tensorflow.python.tpu import tpu_embedding_v2
  from tensorflow.python.tpu import tpu_embedding_v2_utils
  from tensorflow.python.util import nest
label_desc: Use image node_id 24 for calling the TPUEmbeddingBaseTest obj's underlying member method code with example usage: obj._get_total_loss_tensor(activations) and returns: total_loss