Put row lengths on the same device on gpu #113
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merlin/dataloader/torch.py
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| @@ -141,7 +141,7 @@ def _row_lengths_to_offsets(self, row_lengths): | |||
| zero_value = torch.tensor([0], device=self.device, dtype=row_lengths.dtype) | |||
| if len(row_lengths.shape) == 2: | |||
| zero_value = zero_value.view(-1, 1) | |||
| return torch.cat((zero_value, torch.cumsum(row_lengths, 0))) | |||
| return torch.cat((zero_value, torch.cumsum(row_lengths, 0).to(device=self.device))) | |||
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assuming torch.cat preserves the device of the values being concatented, maybe an alternative to this would be to change the line where zero_value is defined to use row_lengths.device instead of self.device?
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that might make the row_lengths to offsets method more robust, but fact that the error is showing up suggests that even with this fix we might end up with a mismatch between the loader.device attribute and the output tensor device?
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Thanks for the suggestion. Honestly I'm not sure which option is best, but it also works, and I think your suggestion is better. Changed in de593b2.
oliverholworthy
approved these changes
Mar 22, 2023
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In a multi-gpu setting, tensors may be generated on different devices. This PR forces
torch.cumsum(row_lengths, 0)to be on the same device as thezero_valuetensor. If they are on different devices,torch.cat()can't concatenate them, e.g.,