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[trainer] fix: handle empty tensors in extract_multi_modal_inputs #4705

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[trainer] fix: handle empty tensors in extract_multi_modal_inputs #4705

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18 changes: 14 additions & 4 deletions verl/utils/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -724,12 +724,22 @@
if "image_bound" in inputs:
has_image_bound = True
for key, value in inputs.items():
if value is not None:
if key not in multi_modal_inputs_collected:
multi_modal_inputs_collected[key] = []
multi_modal_inputs_collected[key].append(value)
# Skip None values and empty tensors/lists to handle text-only samples
# in mixed text/multi-modal batches
if value is None:
continue
if isinstance(value, torch.Tensor) and value.numel() == 0:
continue
if isinstance(value, (list, tuple)) and len(value) == 0:

Check failure on line 733 in verl/utils/model.py

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Ruff (UP038) 

verl/utils/model.py:733:16: UP038 Use `X | Y` in `isinstance` call instead of `(X, Y)`
continue
if key not in multi_modal_inputs_collected:
multi_modal_inputs_collected[key] = []
multi_modal_inputs_collected[key].append(value)

for key, values in multi_modal_inputs_collected.items():
# Skip if no valid tensors were collected for this key
if not values:
continue
if has_image_bound: # minicpm-o logic
multi_modal_inputs[key] = values
else:
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