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This repository was archived by the owner on Nov 21, 2023. It is now read-only.
Please thoroughly read README.md, INSTALL.md, GETTING_STARTED.md, and FAQ.md
Please search existing open and closed issues in case your issue has already been reported
Please try to debug the issue in case you can solve it on your own before posting
After following steps 1-3 above and agreeing to provide the detailed information requested below, you may continue with posting your issue
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Expected results
What did you expect to see?
Actual results
What did you observe instead?
Detailed steps to reproduce
E.g.:
trainer.train()
W1126 12:36:11.825089 140613154027328 checkpoint.py:214] 'roi_heads.box_predictor.cls_score.weight' has shape (81, 1024) in the checkpoint but (22, 1024) in the model! Skipped.
W1126 12:36:11.826922 140613154027328 checkpoint.py:214] 'roi_heads.box_predictor.cls_score.bias' has shape (81,) in the checkpoint but (22,) in the model! Skipped.
W1126 12:36:11.827631 140613154027328 checkpoint.py:214] 'roi_heads.box_predictor.bbox_pred.weight' has shape (320, 1024) in the checkpoint but (84, 1024) in the model! Skipped.
W1126 12:36:11.828277 140613154027328 checkpoint.py:214] 'roi_heads.box_predictor.bbox_pred.bias' has shape (320,) in the checkpoint but (84,) in the model! Skipped.
W1126 12:36:11.829076 140613154027328 checkpoint.py:214] 'roi_heads.mask_head.predictor.weight' has shape (80, 256, 1, 1) in the checkpoint but (21, 256, 1, 1) in the model! Skipped.
W1126 12:36:11.829612 140613154027328 checkpoint.py:214] 'roi_heads.mask_head.predictor.bias' has shape (80,) in the checkpoint but (21,) in the model! Skipped.
~/repos/detectron2/detectron2/engine/defaults.py in train(self)
352 OrderedDict of results, if evaluation is enabled. Otherwise None.
353 """
--> 354 super().train(self.start_iter, self.max_iter)
355 if hasattr(self, "_last_eval_results") and comm.is_main_process():
356 verify_results(self.cfg, self._last_eval_results)
~/repos/detectron2/detectron2/engine/train_loop.py in train(self, start_iter, max_iter)
130 for self.iter in range(start_iter, max_iter):
131 self.before_step()
--> 132 self.run_step()
133 self.after_step()
134 finally:
~/repos/detectron2/detectron2/engine/train_loop.py in run_step(self)
210 If your want to do something with the losses, you can wrap the model.
211 """
--> 212 loss_dict = self.model(data)
213 losses = sum(loss for loss in loss_dict.values())
214 self._detect_anomaly(losses, loss_dict)
~/anaconda3/envs/detectron2_cuda_9_2/lib/python3.7/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
539 result = self._slow_forward(*input, **kwargs)
540 else:
--> 541 result = self.forward(*input, **kwargs)
542 for hook in self._forward_hooks.values():
543 hook_result = hook(self, input, result)
~/repos/detectron2/detectron2/modeling/meta_arch/rcnn.py in forward(self, batched_inputs)
80
81 if self.proposal_generator:
---> 82 proposals, proposal_losses = self.proposal_generator(images, features, gt_instances)
83 else:
84 assert "proposals" in batched_inputs[0]
~/anaconda3/envs/detectron2_cuda_9_2/lib/python3.7/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
539 result = self._slow_forward(*input, **kwargs)
540 else:
--> 541 result = self.forward(*input, **kwargs)
542 for hook in self._forward_hooks.values():
543 hook_result = hook(self, input, result)
~/repos/detectron2/detectron2/modeling/proposal_generator/rpn.py in forward(failed resolving arguments)
177 self.post_nms_topk[self.training],
178 self.min_box_side_len,
--> 179 self.training,
180 )
181 # For RPN-only models, the proposals are the final output and we return them in
~/repos/detectron2/detectron2/modeling/proposal_generator/rpn_outputs.py in find_top_rpn_proposals(proposals, pred_objectness_logits, images, nms_thresh, pre_nms_topk, post_nms_topk, min_box_side_len, training)
134 boxes, scores_per_img, lvl = boxes[keep], scores_per_img[keep], level_ids[keep]
135
--> 136 keep = batched_nms(boxes.tensor, scores_per_img, lvl, nms_thresh)
137 # In Detectron1, there was different behavior during training vs. testing.
138 # (#459)
~/repos/detectron2/detectron2/layers/nms.py in batched_nms(boxes, scores, idxs, iou_threshold)
15 # Investigate after having a fully-cuda NMS op.
16 if len(boxes) < 40000:
---> 17 return box_ops.batched_nms(boxes, scores, idxs, iou_threshold)
18
19 result_mask = scores.new_zeros(scores.size(), dtype=torch.bool)
gcc --version
gcc (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
The text was updated successfully, but these errors were encountered:
PLEASE FOLLOW THESE INSTRUCTIONS BEFORE POSTING
After following steps 1-3 above and agreeing to provide the detailed information requested below, you may continue with posting your issue
(Delete this line and the text above it.)
Expected results
What did you expect to see?
Actual results
What did you observe instead?
Detailed steps to reproduce
E.g.:
System information
nvidia-smi
butconda list | grep cuda
shows cudatoolkit=9.2PYTHONPATH
environment variable: ?python --version
output: 3.7.5RUnning on a Conda environment with Detectron2 installed
I downgraded from CUDA 10.1 to CUDA 9.2 to fix an earlier bug involved in
!nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.50 Driver Version: 430.50 CUDA Version: 10.1
gcc --version
gcc (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
The text was updated successfully, but these errors were encountered: