def get_default_conda_env(include_cloudpickle=False, keras_module=None):
    '\n    :return: The default Conda environment for MLflow Models produced by calls to\n             :func:`save_model()` and :func:`log_model()`.\n    '
    import tensorflow as tf
    conda_deps = []
    pip_deps = []
    if (keras_module is None):
        import keras
        keras_module = keras
    if (keras_module.__name__ == 'keras'):
        if (LooseVersion(keras_module.__version__) < LooseVersion('2.3.1')):
            conda_deps.append('keras=={}'.format(keras_module.__version__))
        else:
            pip_deps.append('keras=={}'.format(keras_module.__version__))
    if include_cloudpickle:
        import cloudpickle
        pip_deps.append('cloudpickle=={}'.format(cloudpickle.__version__))
    if (LooseVersion(tf.__version__) <= LooseVersion('1.13.2')):
        conda_deps.append('tensorflow=={}'.format(tf.__version__))
    else:
        pip_deps.append('tensorflow=={}'.format(tf.__version__))
    return _mlflow_conda_env(additional_conda_deps=conda_deps, additional_pip_deps=pip_deps, additional_conda_channels=None)
:return: The default Conda environment for MLflow Models produced by calls to
         :func:`save_model()` and :func:`log_model()`.
def get_default_conda_env(include_cloudpickle=False, keras_module=None):
    '\n    :return: The default Conda environment for MLflow Models produced by calls to\n             :func:`save_model()` and :func:`log_model()`.\n    '
    import tensorflow as tf
    conda_deps = []
    pip_deps = []
    if (keras_module is None):
        import keras
        keras_module = keras
    if (keras_module.__name__ == 'keras'):
        if (LooseVersion(keras_module.__version__) < LooseVersion('2.3.1')):
            conda_deps.append('keras=={}'.format(keras_module.__version__))
        else:
            pip_deps.append('keras=={}'.format(keras_module.__version__))
    if include_cloudpickle:
        import cloudpickle
        pip_deps.append('cloudpickle=={}'.format(cloudpickle.__version__))
    if (LooseVersion(tf.__version__) <= LooseVersion('1.13.2')):
        conda_deps.append('tensorflow=={}'.format(tf.__version__))
    else:
        pip_deps.append('tensorflow=={}'.format(tf.__version__))
    return _mlflow_conda_env(additional_conda_deps=conda_deps, additional_pip_deps=pip_deps, additional_conda_channels=None)