Environment and hello_world_model documentation updated

CHANGELOG.md

@@ -34,6 +34,7 @@ gets uploaded to AzureML, by skipping all test folders.
 
 ### Fixed
 - ([#537](https://github.com/microsoft/InnerEye-DeepLearning/pull/537)) Print warning if inference is disabled but comparison requested.
+- ([#546](https://github.com/microsoft/InnerEye-DeepLearning/pull/546)) Environment and hello_world_model documentation updated
 - ([#525](https://github.com/microsoft/InnerEye-DeepLearning/pull/525)) Enable --store_dataset_sample
 - ([#495](https://github.com/microsoft/InnerEye-DeepLearning/pull/495)) Fix model comparison.
 - ([#482](https://github.com/microsoft/InnerEye-DeepLearning/pull/482)) Check bool parameter is either true or false.

InnerEye/Azure/azure_config.py

@@ -251,8 +251,8 @@ def get_or_create_dataset(self, azure_dataset_id: str) -> FileDataset:
             raise ValueError("No value set for 'azureml_datastore' (name of the datastore in the AzureML workspace)")
         if not azure_dataset_id:
             raise ValueError("No dataset ID provided.")
-        logging.info(f"Retrieving datastore '{self.azureml_datastore}' from AzureML workspace")
         workspace = self.get_workspace()
+        logging.info(f"Retrieving datastore '{self.azureml_datastore}' from AzureML workspace {workspace.name}")
         datastore = Datastore.get(workspace, self.azureml_datastore)
         try:
             logging.info(f"Trying to retrieve AzureML Dataset '{azure_dataset_id}'")

docs/WSL.md

@@ -63,11 +63,6 @@ Start the Windows Terminal app, create an Ubuntu tab. In the shell, run the foll
 - Close your WSL shell and re-start it
 - Clone repo or access your repos via /mnt/c/...
 - Create conda environment: `conda env create --file environment.yml`
-- Create a file in the top level directory of the repository, named `InnerEyeTestVariables.txt`, with one line:
-```
-APPLICATION_KEY=<app key for your AML workspace>
-```
-This will enable you to run tests that require authentication to Azure.
 - Clean your pyc files (in case you have some left from Windows):
 ```
 find * -name '*.pyc' | xargs -d'\n' rm`

docs/environment.md

@@ -14,9 +14,8 @@ submodule. We only recommended that if you are very handy with Python. More deta
 
 ## Windows Subsystem for Linux Setup
 When developing on a Windows machine, we recommend using [the Windows Subsystem for Linux, WSL2](https://docs.microsoft.com/en-us/windows/wsl/about).
-That's because PyTorch has better support for Linux.
-
-If you want to use WSL, please follow [these instructions](/docs/WSL.md)
+That's because PyTorch has better support for Linux.  If you want to use WSL2, please follow 
+[these instructions](/docs/WSL.md) , that correspond to the manual installation in the official docs.
 
 ## Installing Conda or Miniconda
 You can skip this step if you have installed WSL as per the previous item.
@@ -125,9 +124,9 @@ point, if you want to dig deeper into the code.
 Our team uses [PyCharm](https://www.jetbrains.com/pycharm/) for development, but any good editor 
 ([VSCode](https://code.visualstudio.com/) for example) will do as well.
 
-This repository already contains a PyCharm configuration file in `.idea/InnerEye-DeepLearning.iml`. It will pick the
-WSL Python interpreter (see [WSL.md](WSL.md)) as the default - based on your configuration, you will need to adjust 
-that as described [here](https://www.jetbrains.com/help/pycharm/configuring-python-interpreter.html).
+This repository already contains a PyCharm configuration file in `.idea/InnerEye-DeepLearning.iml`. It should 
+automatically pick the WSL Python interpreter (see [WSL.md](WSL.md)) as the default (no need to import the settings file)
+- if it doesn't happen you will need to adjust that as described [here](https://www.jetbrains.com/help/pycharm/configuring-python-interpreter.html).
 
 
 ## How to manually set up flake8 as a PyCharm external tool

docs/hello_world_model.md

@@ -9,6 +9,8 @@ We have created this file to demonstrate how to:
 
 * This model can be trained from the commandline, from the root of the repo: `python InnerEye/runner.py --model=HelloWorld`
 * If you want to test your AzureML workspace with the HelloWorld model:
+    * Make sure your AzureML workspace has been set up. You should have inside the folder InnerEye a settings.yml file
+      that specifies the datastore, the resource group, and the workspace on which to run
     * Upload to datasets storage account for your AzureML workspace: `Tests/ML/test_data/dataset.csv` and
     `Test/ML/test_data/train_and_test_data` and name the folder "hello_world"   
     * If you have set up AzureML then parameter search can be performed for this model by running: