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When training without providing the mixed_precision argument to FSDP, there is an error related to dtype mismatch in dinov2/layers/block.py. Is this expected?
Full stacktrace:
File "/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl | Link
-- | --
| | 2023-10-12T17:54:11.976-06:00 | [3]: return forward_call(*args, **kwargs) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py", line 748, in forward | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: output = self._fsdp_wrapped_module(*args, **kwargs) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: return forward_call(*args, **kwargs) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: ret = self.forward_features(*args, **kwargs) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/dinov2/models/vision_transformer.py", line 207, in forward_features_list | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: x = blk(x) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py", line 748, in forward | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: output = self._fsdp_wrapped_module(*args, **kwargs) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/dinov2/layers/block.py", line 258, in forward | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: return self.forward_nested(x_or_x_list) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/dinov2/layers/block.py", line 226, in forward_nested | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: x_list = drop_add_residual_stochastic_depth_list( | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/dinov2/layers/block.py", line 200, in drop_add_residual_stochastic_depth_list | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: attn_bias, x_cat = get_attn_bias_and_cat(x_list, branges) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: File "/.venv/lib/python3.10/site-packages/dinov2/layers/block.py", line 180, in get_attn_bias_and_cat | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: cat_tensors = index_select_cat([x.flatten(1) for x in x_list], branges).view(1, -1, x_list[0].shape[-1]) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: return _IndexSelectCat.apply(*sources, *indices) | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]: IndexSelect.OPERATOR( | Link
| | 2023-10-12T17:54:11.976-06:00 | [3]:RuntimeError: Expected output.scalar_type() == at::ScalarType::Half to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)
The text was updated successfully, but these errors were encountered:
When training without providing the
mixed_precision
argument to FSDP, there is an error related to dtype mismatch indinov2/layers/block.py
. Is this expected?Full stacktrace:
The text was updated successfully, but these errors were encountered: