Traceback (most recent call last):


 "E:\dl_projects\tvm\get_started.py", line 196, in <module>

cc.create_shared(temp.relpath("myadd.so"), [temp.relpath("myadd.o")])


 "C:\Users\Phenix\AppData\Roaming\Python\Python36\site-packages\tvm-0.4.0-py3.6-win-amd64.egg\tvm\contrib\cc.py", line 35, in create_shared

_windows_shared(output, objects, options)


 "C:\Users\Phenix\AppData\Roaming\Python\Python36\site-packages\tvm-0.4.0-py3.6-win-amd64.egg\tvm\contrib\cc.py", line 120, in _windows_shared

raise RuntimeError(msg)
RuntimeError: Compilation error:

Traceback (most recent call last):


 "/opt/conda/lib/python3.7/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 231, in _start_fn

fn(gindex, *args)


 "<ipython-input-28-84688a965284>", line 8, in _mp_fn

a = run_training()


 "<ipython-input-18-37d2de31a633>", line 76, in run_training

fitter.fit(train_loader, val_loader)


 "<ipython-input-15-07cadfe426a7>", line 40, in fit

summary_loss = self.train_one_epoch(train_loader)


 "<ipython-input-15-07cadfe426a7>", line 106, in train_one_epoch

loss, _, _ = self.model(images, boxes, labels)


 "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 577, in __call__

result = self.forward(*input, **kwargs)


 "../input/timm-efficientdet-pytorch/effdet/bench.py", line 93, in forward

gt_class_out, gt_box_out, num_positive = self.anchor_labeler.label_anchors(gt_boxes[i], gt_labels[i])


 "../input/timm-efficientdet-pytorch/effdet/anchors.py", line 343, in label_anchors

cls_targets, _, box_targets, _, matches = self.target_assigner.assign(anchor_box_list, gt_box_list, gt_labels)


 "../input/timm-efficientdet-pytorch/effdet/object_detection/target_assigner.py", line 140, in assign

match = self._matcher.match(match_quality_matrix, **params)


 "../input/timm-efficientdet-pytorch/effdet/object_detection/matcher.py", line 212, in match

return Match(self._match(similarity_matrix, **params))


 "../input/timm-efficientdet-pytorch/effdet/object_detection/argmax_matcher.py", line 155, in _match

return _match_when_rows_are_non_empty()


 "../input/timm-efficientdet-pytorch/effdet/object_detection/argmax_matcher.py", line 144, in _match_when_rows_are_non_empty

force_match_column_indicators = one_hot(force_match_column_ids, similarity_matrix.shape[1])
RuntimeError: Class values must be non-negative.