Fix for invalid path_on_compute problem

CHANGELOG.md

@@ -55,6 +55,7 @@ gets uploaded to AzureML, by skipping all test folders.
 - ([#572](https://github.com/microsoft/InnerEye-DeepLearning/pull/572)) Updated to new version of hi-ml package
 
 ### Fixed
+- ([#593](https://github.com/microsoft/InnerEye-DeepLearning/pull/593)) Bug fix for hi-ml 0.1.11 issue (#130): empty mount point is turned into ".", which fails the AML job
 - ([#587](https://github.com/microsoft/InnerEye-DeepLearning/pull/587)) Bug fix for regression in AzureML's handling of environments: upgrade to hi-ml 0.1.11
 - ([#537](https://github.com/microsoft/InnerEye-DeepLearning/pull/537)) Print warning if inference is disabled but comparison requested.
 - ([#567](https://github.com/microsoft/InnerEye-DeepLearning/pull/567)) fix pillow version.

InnerEye/Azure/azure_runner.py

@@ -111,7 +111,9 @@ def create_dataset_configs(azure_config: AzureConfig,
     for i, (dataset_id, mount_point) in enumerate(zip(all_azure_dataset_ids, all_dataset_mountpoints)):
         if dataset_id:
             datasets.append(DatasetConfig(name=dataset_id,
-                                          target_folder=mount_point,
+                                          # Workaround for a bug in hi-ml 0.1.11: mount_point=="" creates invalid jobs,
+                                          # setting to None works.
+                                          target_folder=mount_point or None,
                                           use_mounting=azure_config.use_dataset_mount,
                                           datastore=azure_config.azureml_datastore))
         elif mount_point:

InnerEye/Common/fixed_paths.py

@@ -33,7 +33,6 @@ def repository_root_directory(path: Optional[PathOrString] = None) -> Path:
 DEFAULT_RESULT_IMAGE_NAME = "segmentation.nii.gz"
 # Default filename if scoring produces a zipped DICOM-RT file.
 DEFAULT_RESULT_ZIP_DICOM_NAME = "segmentation.dcm.zip"
-DEFAULT_AML_LOGS_DIR = "azureml-logs"
 
 DEFAULT_LOGS_DIR_NAME = "logs"
 

InnerEye/ML/visualizers/plot_cross_validation.py

@@ -49,7 +49,6 @@
 RUN_DICTIONARY_NAME = "RunDictionary.txt"
 
 MAX_STRUCTURES_PER_PLOT = 7
-DRIVER_LOG_BASENAME = "70_driver_log.txt"
 RUN_RECOVERY_ID_KEY = 'run_recovery_id'
 WILCOXON_RESULTS_FILE = "CrossValidationWilcoxonSignedRankTestResults.txt"
 MANN_WHITNEY_RESULTS_FILE = "CrossValidationMannWhitneyTestResults.txt"

Tests/AfterTraining/test_after_training.py

@@ -29,7 +29,7 @@
 from InnerEye.Common import common_util, fixed_paths, fixed_paths_for_tests
 from InnerEye.Common.common_util import BEST_EPOCH_FOLDER_NAME, CROSSVAL_RESULTS_FOLDER, ENSEMBLE_SPLIT_NAME, \
     get_best_epoch_results_path
-from InnerEye.Common.fixed_paths import (DEFAULT_AML_LOGS_DIR, DEFAULT_RESULT_IMAGE_NAME, DEFAULT_RESULT_ZIP_DICOM_NAME,
+from InnerEye.Common.fixed_paths import (DEFAULT_RESULT_IMAGE_NAME, DEFAULT_RESULT_ZIP_DICOM_NAME,
                                          PYTHON_ENVIRONMENT_NAME, repository_root_directory)
 from InnerEye.Common.fixed_paths_for_tests import full_ml_test_data_path
 from InnerEye.Common.output_directories import OutputFolderForTests
@@ -50,7 +50,7 @@
 from InnerEye.Scripts import submit_for_inference
 from Tests.ML.util import assert_nifti_content, get_default_azure_config, get_default_workspace, get_nifti_shape
 
-FALLBACK_SINGLE_RUN = "refs_pull_545_merge:refs_pull_545_merge_1626538212_d2b07afd"
+FALLBACK_SINGLE_RUN = "refs_pull_593_merge_1637188926_7ba554ba"
 FALLBACK_ENSEMBLE_RUN = "refs_pull_545_merge:HD_caea82ae-9603-48ba-8280-7d2bc6272411"
 FALLBACK_2NODE_RUN = "refs_pull_545_merge:refs_pull_545_merge_1626538178_9f3023b2"
 FALLBACK_CV_GLAUCOMA = "refs_pull_545_merge:HD_72ecc647-07c3-4353-a538-620346114ebd"
@@ -200,10 +200,16 @@ def test_check_dataset_mountpoint(test_output_dirs: OutputFolderForTests) -> Non
     """
     run = get_most_recent_run(fallback_run_id_for_local_execution=FALLBACK_SINGLE_RUN)
     files = run.get_file_names()
-    driver_log = f"{DEFAULT_AML_LOGS_DIR}/70_driver_log.txt"
-    assert driver_log in files
-    downloaded = test_output_dirs.root_dir / "70_driver_log.txt"
-    run.download_file(driver_log, output_file_path=str(downloaded))
+
+    # Account for old and new job runtime: log files live in different places
+    driver_log_files = ["azureml-logs/70_driver_log.txt", "user_logs/std_log.txt"]
+    downloaded = test_output_dirs.root_dir / "driver_log.txt"
+    for f in driver_log_files:
+        if f in files:
+            run.download_file(f, output_file_path=str(downloaded))
+            break
+    else:
+        raise ValueError("The run does not contain any of the driver log files")
     logs = downloaded.read_text()
     expected_mountpoint = BasicModel2Epochs().dataset_mountpoint
     assert f"local_dataset                           : {expected_mountpoint}" in logs