code: def _get_variable(  # pylint: disable=unused-argument,redefined-outer-name
      name,
      shape=None,
      dtype=None,
      initializer=None,
      regularizer=None,
      trainable=None,
      collections=None,
      caching_device=None,
      partitioner=None,
      validate_shape=True,
      use_resource=None,
      custom_getter=None,
      constraint=None,
      synchronization=None,
      aggregation=None,
  ):
      if callable(initializer):
          initial_value = initializer(shape)
      else:
          initial_value = initializer
      return Variable(
          initial_value=initial_value,
          trainable=trainable,
          validate_shape=validate_shape,
          caching_device=caching_device,
          name=name,
          variable_def=None,
          dtype=dtype,
          import_scope=None,
          constraint=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 2 for calling a global function with example usage: _get_variable(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter, constraint, synchronization, aggregation) and returns: Variable