Fix skipped InnerEye dataset tests

Tests/ML/datasets/test_dataset.py

@@ -8,7 +8,7 @@
 import pandas as pd
 import pytest
 import torch
-from pytorch_lightning.core.step_result import Result
+from pytorch_lightning.utilities.data import extract_batch_size
 
 from InnerEye.Common import common_util
 from InnerEye.ML.config import PaddingMode, SegmentationModelBase
@@ -502,7 +502,7 @@ def test_sample_metadata_field() -> None:
  assert SAMPLE_METADATA_FIELD in fields
  # Lightning attempts to determine the batch size by trying to find a tensor field in the sample.
  # This only works if any field other than Metadata is first.
- assert Result.unpack_batch_size(fields) == batch_size
+ assert extract_batch_size(fields) == batch_size
 
 
 def test_custom_collate() -> None:

pytest.ini

@@ -1,6 +1,6 @@
 [pytest]
 testpaths=Tests TestsOutsidePackage TestSubmodule
-norecursedirs=azure-pipelines docs datasets sphinx-docs InnerEye logs outputs test_data
+norecursedirs=azure-pipelines docs sphinx-docs InnerEye logs outputs test_data
 addopts=--strict-markers
 markers=
  gpu: Test needs a GPU to run