Fix docs for HelloWorld (#360)

* Fix docs for HellowWorld

* Fix docs for HellowWorld

* Add more details

InnerEye/ML/configs/segmentation/HelloWorld.py

@@ -26,9 +26,13 @@ class HelloWorld(SegmentationModelBase):
     2) Configure the UNet3D implemented in this package
     3) Configure Azure HyperDrive based parameter search
 
-    - This model can be trained from the commandline: ../InnerEye/runner.py --model=HelloWorld
+    * This model can be trained from the commandline: python InnerEye/runner.py --model=HelloWorld
+
+    * If you want to test that your AzureML workspace is working:
+        - Upload to datasets storage account for your AzureML workspace: Test/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:
-    ../InnerEye/runner.py --model=HelloWorld --hyperdrive=True
+        python InnerEye/ML/ runner.py --model=HelloWorld --azureml=True --hyperdrive=True
 
     In this example, the model is trained on 2 input image channels channel1 and channel2, and
     predicts 2 foreground classes region, region_1.
@@ -39,7 +43,7 @@ class HelloWorld(SegmentationModelBase):
         super().__init__(
             # Data definition - in this section we define where to load the dataset from
             local_dataset=full_ml_test_data_path(),
-
+            azure_dataset_id="hello_world",
             # Model definition - in this section we define what model to use and some related configurations
             architecture="UNet3D",
             feature_channels=[4],

docs/hello_world_model.md

@@ -7,6 +7,9 @@ We have created this file to demonstrate how to:
 1. Configure the UNet3D implemented in this package
 1. Configure Azure HyperDrive based parameter search
 
-- This model can be trained from the commandline: ../InnerEye/runner.py --model=HelloWorld
-- If you have set up AzureML then parameter search can be performed for this model by running:
-../InnerEye/runner.py --model=HelloWorld --hyperdrive=True
+* 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:
+    * Upload to datasets storage account for your AzureML workspace: `Test/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:
+    `python InnerEye/ML/ runner.py --model=HelloWorld --azureml=True --hyperdrive=True`