Fix RuntimeError in DataAnalyzer (#7310)

Fixes #7309

### Description

`DataAnalyzer` only catch error when data is on GPU, add catching error
when data is on CPU.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>

monai/apps/auto3dseg/data_analyzer.py

@@ -28,7 +28,7 @@
 from monai.data import DataLoader, Dataset, partition_dataset
 from monai.data.utils import no_collation
 from monai.transforms import Compose, EnsureTyped, LoadImaged, Orientationd
-from monai.utils import StrEnum, min_version, optional_import
+from monai.utils import ImageMetaKey, StrEnum, min_version, optional_import
 from monai.utils.enums import DataStatsKeys, ImageStatsKeys
 
 
@@ -343,19 +343,25 @@ def _get_all_case_stats(
  d = summarizer(batch_data)
  except BaseException as err:
  if "image_meta_dict" in batch_data.keys():
- filename = batch_data["image_meta_dict"]["filename_or_obj"]
+ filename = batch_data["image_meta_dict"][ImageMetaKey.FILENAME_OR_OBJ]
  else:
- filename = batch_data[self.image_key].meta["filename_or_obj"]
+ filename = batch_data[self.image_key].meta[ImageMetaKey.FILENAME_OR_OBJ]
  logger.info(f"Unable to process data {filename} on {device}. {err}")
  if self.device.type == "cuda":
  logger.info("DataAnalyzer `device` set to GPU execution hit an exception. Falling back to `cpu`.")
- batch_data[self.image_key] = batch_data[self.image_key].to("cpu")
- if self.label_key is not None:
- label = batch_data[self.label_key]
- if not _label_argmax:
- label = torch.argmax(label, dim=0) if label.shape[0] > 1 else label[0]
- batch_data[self.label_key] = label.to("cpu")
- d = summarizer(batch_data)
+ try:
+ batch_data[self.image_key] = batch_data[self.image_key].to("cpu")
+ if self.label_key is not None:
+ label = batch_data[self.label_key]
+ if not _label_argmax:
+ label = torch.argmax(label, dim=0) if label.shape[0] > 1 else label[0]
+ batch_data[self.label_key] = label.to("cpu")
+ d = summarizer(batch_data)
+ except BaseException as err:
+ logger.info(f"Unable to process data {filename} on {device}. {err}")
+ continue
+ else:
+ continue
 
  stats_by_cases = {
  DataStatsKeys.BY_CASE_IMAGE_PATH: d[DataStatsKeys.BY_CASE_IMAGE_PATH],

monai/auto3dseg/analyzer.py

@@ -460,7 +460,7 @@ def __call__(self, data: Mapping[Hashable, MetaTensor]) -> dict[Hashable, MetaTe
  torch.set_grad_enabled(False)
 
  ndas: list[MetaTensor] = [d[self.image_key][i] for i in range(d[self.image_key].shape[0])] # type: ignore
- ndas_label: MetaTensor = d[self.label_key] # (H,W,D)
+ ndas_label: MetaTensor = d[self.label_key].astype(torch.int8) # (H,W,D)
 
  if ndas_label.shape != ndas[0].shape:
  raise ValueError(f"Label shape {ndas_label.shape} is different from image shape {ndas[0].shape}")