System Information

• Framework (e.g. TensorFlow) / Algorithm (e.g. KMeans): Scikit-Learn
• Framework Version: 0.20.0 (official sagemaker-scikit-learn-container)
• Python Version: 3.6
• CPU or GPU: CPU
• Python SDK Version: 1.26.0
• Are you using a custom image: No

Describe the problem

I'd like to send environment-variable(http_proxy) to docker container at the time of training, but there is no way. On the other hand, the env parameter is prepared for the transform method.

Minimal repro / logs

• Exact command to reproduce:

env = {'HTTP_PROXY': os.environ['HTTP_PROXY']}
 
sklearn = SKLearn(
    entry_point='scikit_learn_iris.py',
    train_instance_type="ml.c4.xlarge",
    role=role,
    sagemaker_session=sagemaker_session,
    hyperparameters={'max_leaf_nodes': 30}
    )

sklearn.fit({'train': train_input}, env=env)      # I want to input env paramater here