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refactor to avoid NoneType in optimize_for_inference #384

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Merged
merged 1 commit into from
Oct 15, 2025
Merged

refactor to avoid NoneType in optimize_for_inference #384

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3 changes: 2 additions & 1 deletion rfdetr/detr.py
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Original file line number Diff line number Diff line change
Expand Up @@ -319,8 +319,9 @@ def predict(
predictions = {
"pred_logits": predictions[1],
"pred_boxes": predictions[0],
"pred_masks": predictions[2]
}
if len(predictions) == 3:
predictions["pred_masks"] = predictions[2]
target_sizes = torch.tensor(orig_sizes, device=self.model.device)
results = self.model.postprocess(predictions, target_sizes=target_sizes)

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5 changes: 4 additions & 1 deletion rfdetr/models/lwdetr.py
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Expand Up @@ -244,7 +244,10 @@ def forward_export(self, tensors):
if self.segmentation_head is not None:
outputs_masks = self.segmentation_head(srcs[0], [hs_enc,], tensors.shape[-2:], skip_blocks=True)[0]

return outputs_coord, outputs_class, outputs_masks
if outputs_masks is not None:
return outputs_coord, outputs_class, outputs_masks
else:
return outputs_coord, outputs_class

@torch.jit.unused
def _set_aux_loss(self, outputs_class, outputs_coord, outputs_masks):
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