title: Azure Machine Learning Service - Environment variables defined in Environment not accessible from init() method in entry_script
body: <p>I am deploying a model to AKS via AML using the python-sdk, and I am facing a problem accessing the environment variables defined for the <code>Environment</code> object <code>myenv</code>used for the deployment.</p>
  
  <pre><code># add environment variable
  myenv.environment_variables = {'SOME_ENV_VARIABLE': 'ABC'}
  # register to workspace
  myenv.register(ws)
  </code></pre>
  
  <p>This environment object is stated in the inference configuration for the deployment:</p>
  
  <pre><code>myenv = Environment.get(workspace=ws,name="myenv")
  inference_config = InferenceConfig(entry_script='score.py',
                                        source_directory=os.path.abspath(__file__ + "//.."),
                                        environment=myenv,
                                        enable_gpu=True,
                                        description="...")
  </code></pre>
  
  <p>When the model executes, the init() method in the entry_script <code>score.py</code> should be able to access these environment variables by calling <code>os.environ['SOME_ENV_VARIABLE']</code>. However, that is not working. The conda and pip packages defined in <code>myenv</code> are present in the image.</p>
  
  <p>Shouldn't it be possible to access these env variables from the entry_script?</p>