class_docstr: Module that has a scope to capture vars/losses made by `get_variable`.
code: def get_regularization_losses(self):
      # TODO(kaftan): Consider adding a regex scope like the collection access.
      # But, < 40-50 usages of get_regularization_loss(es) with `scope`
      # & possible to do manually?
      losses = {}
      for (
          var_name,
          regularizer,
      ) in (
          self._var_store._regularizers.items()
      ):  # pylint: disable=protected-access
          losses[var_name] = regularizer()
      return losses
  
imports: import functools
  from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.keras.engine import base_layer
  from tensorflow.python.keras.utils import tf_contextlib
  from tensorflow.python.keras.utils import tf_inspect
  from tensorflow.python.module import module
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import tf_decorator
label_desc: Use image node_id 4 for calling the VariableAndLossTracker obj's underlying member method code with example usage: obj.get_regularization_losses() and returns: losses