yeandy commented on code in PR #22795:
URL: https://github.com/apache/beam/pull/22795#discussion_r950466702
##########
sdks/python/apache_beam/ml/inference/pytorch_inference.py:
##########
@@ -40,11 +41,30 @@
def _load_model(
model_class: torch.nn.Module, state_dict_path, device, **model_params):
model = model_class(**model_params)
+
+ if device == torch.device('cuda') and not torch.cuda.is_available():
+ logging.warning(
+ "Specified 'GPU', but could not find device. Switching to CPU.")
+ device = torch.device('cpu')
+
+ try:
+ logging.info("Reading state_dict_path %s onto %s", state_dict_path, device)
+ file = FileSystems.open(state_dict_path, 'rb')
+ state_dict = torch.load(file, map_location=device)
+ except RuntimeError as e:
Review Comment:
The type of the exception so we can't go more specific than that.
```
RuntimeError: Attempting to deserialize object on a CUDA device but
torch.cuda.is_available() is False. If you are running on a CPU-only machine,
please use torch.load with map_location=torch.device('cpu') to map your
storages to the CPU.
```
Yes, I can change to just have the `torch.load()` line in the block.
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