Traceback (most recent call last):


 "/tmp/sentry/.venv/lib/python3.7/site-packages/sentry_sdk/transport.py", line 296, in send_event_wrapper

self._send_event(event)


 "/tmp/sentry/.venv/lib/python3.7/site-packages/sentry_sdk/transport.py", line 217, in _send_event

headers={"Content-Type": "application/json", "Content-Encoding": "gzip"},


 "/tmp/sentry/.venv/lib/python3.7/site-packages/sentry_sdk/transport.py", line 164, in _send_request

"POST", str(self._auth.store_api_url), body=body, headers=headers


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/request.py", line 80, in request

method, url, fields=fields, headers=headers, **urlopen_kw


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/request.py", line 171, in request_encode_body

return self.urlopen(method, url, **extra_kw)


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/poolmanager.py", line 330, in urlopen

response = conn.urlopen(method, u.request_uri, **kw)


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/connectionpool.py", line 760, in urlopen

**response_kw


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/connectionpool.py", line 760, in urlopen

**response_kw


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/connectionpool.py", line 760, in urlopen

**response_kw


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/connectionpool.py", line 720, in urlopen

method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]


 "/tmp/sentry/.venv/lib/python3.7/site-packages/urllib3/util/retry.py", line 436, in increment

raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='mysite.com', port=443): Max retries exceeded with url: /api/123/store/ (Caused by NewConnectionError('<urllib3.connection.VerifiedHTTPSConnection object at 0x7f2c7c16b910>: Failed to establish a new connection: [Errno 111] Connection refused'))

Traceback (most recent call last):


 "tools/train_net.py", line 263, in <module>

args=(args,),


 "/home/ctjai/detectron2/detectron2/engine/launch.py", line 57, in launch

main_func(*args)


 "tools/train_net.py", line 251, in main

return trainer.train()


 "tools/train_net.py", line 126, in train

self.train_loop(self.start_iter, self.max_iter)


 "tools/train_net.py", line 115, in train_loop

self.run_step()


 "/home/ctjai/detectron2/detectron2/engine/train_loop.py", line 215, in run_step

loss_dict = self.model(data)


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/home/ctjai/ocr/文本检测/AdelaiDet/adet/modeling/one_stage_detector.py", line 113, in forward

features = self.backbone(images.tensor)


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/home/ctjai/detectron2/detectron2/modeling/backbone/fpn.py", line 123, in forward

bottom_up_features = self.bottom_up(x)


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/home/ctjai/detectron2/detectron2/modeling/backbone/resnet.py", line 427, in forward

x = stage(x)


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/container.py", line 100, in forward

input = module(input)


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/home/ctjai/detectron2/detectron2/modeling/backbone/resnet.py", line 201, in forward

out = self.conv3(out)


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/home/ctjai/detectron2/detectron2/layers/wrappers.py", line 96, in forward

x = self.norm(x)


 "/home/ctjai/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 550, in __call__

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


 "/home/ctjai/detectron2/detectron2/layers/batch_norm.py", line 53, in forward

return x * scale + bias
RuntimeError: CUDA out of memory. Tried to allocate 264.00 MiB (GPU 0; 7.93 GiB total capacity; 6.62 GiB already allocated; 64.12 MiB free; 6.77 GiB reserved in total by PyTorch)
