How to use the mleap.version.__version__ function in mleap

import sys
from setuptools import setup, find_packages

if sys.version_info < (2, 7):
    print("Python versions prior to 2.7 are not supported for pip installed MLeap.",
          file=sys.stderr)
    exit(-1)

try:
    exec(open('mleap/version.py').read())
except IOError:
    print("Failed to load MLeap version file for packaging. You must be in MLeap's python directory.",
          file=sys.stderr)
    sys.exit(-1)

VERSION = __version__

numpy_version = "1.8.2"

REQUIRED_PACKAGES = [
      'numpy >= %s' % numpy_version,
      'six >= 1.10.0',
      'scipy>=0.13.0b1',
      'pandas>=0.18.1',
      'scikit-learn>=0.18.dev0',
      'nose-exclude>=0.5.0'
]

setup(name='mleap',
      version=VERSION,
      description='MLeap Python API',
      author='MLeap Developers',

def get_bundle(transformer):
        js = {
          "name": transformer.name,
          "format": "json",
          "version": __version__,
          "timestamp": datetime.datetime.now().isoformat(),
          "uid": "{}".format(uuid.uuid4())
        }
        return js

path=mleap_path_full))
    os.makedirs(mleap_path_full)

    dataset = spark_model.transform(sample_input)
    model_path = "file:{mp}".format(mp=mleap_datapath_full)
    try:
        spark_model.serializeToBundle(path=model_path,
                                      dataset=dataset)
    except Py4JError:
        _handle_py4j_error(
                MLeapSerializationException,
                "MLeap encountered an error while serializing the model. Ensure that the model is"
                " compatible with MLeap (i.e does not contain any custom transformers).")

    mlflow_model.add_flavor(FLAVOR_NAME,
                            mleap_version=mleap.version.__version__,
                            model_data=mleap_datapath_sub)