diff --git a/CHANGELOG.md b/CHANGELOG.md index 35f86f040..6f15d4523 100644 --- a/CHANGELOG.md +++ b/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. diff --git a/InnerEye/Azure/azure_config.py b/InnerEye/Azure/azure_config.py index 336b29e56..3c32e2a04 100755 --- a/InnerEye/Azure/azure_config.py +++ b/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}'") diff --git a/docs/WSL.md b/docs/WSL.md index 9a3ccc355..c0b581ec6 100644 --- a/docs/WSL.md +++ b/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= -``` -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` diff --git a/docs/environment.md b/docs/environment.md index be17b507b..afce4c595 100644 --- a/docs/environment.md +++ b/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 diff --git a/docs/hello_world_model.md b/docs/hello_world_model.md index 6b5c873cc..10cb56ab4 100644 --- a/docs/hello_world_model.md +++ b/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: