class_docstr: A context manager for defining ops that creates variables (layers).
code: def __init__(
      self,
      name_or_scope,
      default_name=None,
      values=None,
      initializer=None,  # pylint: disable=unused-argument
      regularizer=None,
      caching_device=None,
      partitioner=None,  # pylint: disable=unused-argument
      custom_getter=None,
      reuse=None,
      dtype=None,
      use_resource=None,  # pylint: disable=unused-argument
      constraint=None,
      auxiliary_name_scope=True,
  ):  # pylint: disable=unused-argument
      self._caching_device = None
  
imports: import collections
  import contextlib
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import _utils
  from tensorflow_probability.python.internal.backend.numpy import initializers
  from tensorflow_probability.python.internal.backend.numpy import linalg_impl
  from tensorflow_probability.python.internal.backend.numpy import numpy_logging
  from tensorflow_probability.python.internal.backend.numpy.gen.tensor_shape import Dimension
  from tensorflow_probability.python.internal.backend.numpy.numpy_array import *
  from tensorflow_probability.python.internal.backend.numpy.ops import convert_to_tensor
  from tensorflow_probability.python.internal.backend.numpy.ops import Module
  from tensorflow_probability.python.internal.backend.numpy.ops import name_scope
  from tensorflow_probability.python.internal.backend.numpy.ops import Variable
  from tensorflow_probability.python.internal.backend.numpy.random_generators import set_seed
  from tensorflow_probability.python.internal.backend.numpy.tensor_array_ops import TensorArray
label_desc: Use image node_id 1 to create a new variable_scope object from inherited base classes: object with example: obj = variable_scope(name_or_scope, default_name, values, initializer, regularizer, caching_device, partitioner, custom_getter, reuse, dtype, use_resource, constraint, auxiliary_name_scope)