Wicked_Chicken

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Everything posted by Wicked_Chicken

  1. I'm suddenly having an issue with this, getting the following from my logs: Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 109, in emit self.flush() File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 68, in flush self.stream.flush() OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected Traceback (most recent call last): File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 102, in emit self.stream.write(msg) OSError: [Errno 107] Transport endpoint is not connected OSError: [Errno 107] Transport endpoint is not connected During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/bin/supervisord", line 33, in <module> sys.exit(load_entry_point('supervisor==4.2.5', 'console_scripts', 'supervisord')()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/lib/python3.11/site-packages/supervisor/supervisord.py", line 361, in main options.close_logger() File "/usr/lib/python3.11/site-packages/supervisor/options.py", line 1250, in close_logger self.logger.close() File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 311, in close handler.close() File "/usr/lib/python3.11/site-packages/supervisor/loggers.py", line 86, in close self.stream.close() OSError: [Errno 107] Transport endpoint is not connected 2023-08-09 15:29:07,428 DEBG 'watchdog-script' stderr output: sed: can't read /config/qBittorrent/config/qBittorrent.conf: Transport endpoint is not connected 2023-08-09 15:29:31,452 WARN received SIGTERM indicating exit request 2023-08-09 15:29:31,452 DEBG killing watchdog-script (pid 301) with signal SIGTERM 2023-08-09 15:29:31,452 INFO waiting for start-script, watchdog-script to die 2023-08-09 15:29:31,453 DEBG fd 11 closed, stopped monitoring <POutputDispatcher at 23441593907920 for <Subprocess at 23441593916432 with name watchdog-script in state STOPPING> (stdout)> 2023-08-09 15:29:31,453 DEBG fd 15 closed, stopped monitoring <POutputDispatcher at 23441592009040 for <Subprocess at 23441593916432 with name watchdog-script in state STOPPING> (stderr)> 2023-08-09 15:29:31,453 WARN stopped: watchdog-script (exit status 143) 2023-08-09 15:29:31,453 DEBG received SIGCHLD indicating a child quit 2023-08-09 15:29:31,454 DEBG killing start-script (pid 300) with signal SIGTERM 2023-08-09 15:29:32,457 DEBG fd 8 closed, stopped monitoring <POutputDispatcher at 23441593901904 for <Subprocess at 23441593998288 with name start-script in state STOPPING> (stdout)> 2023-08-09 15:29:32,457 DEBG fd 10 closed, stopped monitoring <POutputDispatcher at 23441608411088 for <Subprocess at 23441593998288 with name start-script in state STOPPING> (stderr)> 2023-08-09 15:29:32,457 WARN stopped: start-script (terminated by SIGTERM) 2023-08-09 15:29:32,457 DEBG received SIGCHLD indicating a child quit Any thoughts? Thank you!
  2. Hello, I recent had an UD disc share disappear from windows, and I cannot seem to get it to reappear even if I reset the share in UD within Unraid. I have a single UD drive I want to share, and it appears correctly within Unraid, but I still cannot get windows to find it. Any assistance is greatly appreciated. unraid-diagnostics-20220714-2003.zip
  3. Hello, I seem to be having issues pulling files from the array in a timely fashion, and Windows is reporting my copy speed is ~3-4MB/s. I am not sure why, however. Any help is greatly appreciated as my attempts to speed things up and solve common problems has not yet been successful. unraid-diagnostics-20220522-2215.zip
  4. Hello, I am having difficulty with with a drive that was previously working with UD. Here's the log I'm getting. Mar 24 18:25:21 UNRAID emhttpd: read SMART /dev/sdb Mar 24 21:11:08 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 24 21:11:08 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 12:31:23 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 12:31:23 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 12:32:38 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 12:32:38 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 12:33:31 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 12:33:31 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 12:35:00 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 12:35:00 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 14:10:50 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 14:10:50 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 14:11:45 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 14:11:45 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 14:12:06 UNRAID unassigned.devices: Warning: Cannot change the disk label on device 'sdb1'. Mar 26 14:12:08 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 14:12:08 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Mar 26 14:14:48 UNRAID sudo: root : TTY=pts/1 ; PWD=/root ; USER=root ; COMMAND=/sbin/fsck -N /dev/sdb Mar 26 14:15:33 UNRAID emhttpd: spinning down /dev/sdb Mar 26 14:16:06 UNRAID unassigned.devices: Partition 'sdb1' does not have a file system and cannot be mounted. Mar 26 14:16:06 UNRAID unassigned.devices: Error: Device '/dev/sdb2' mount point 'Media' - name is reserved, used in the array or by an unassigned device. Any help is greatly appreciated!
  5. Edit: Issue was confirmed as insufficient CUDA memory. https://imgur.com/a/tvN804n So it appears each custom model essentially runs as an independent process. I did not realize this, and am going to have to do some testing with with Yolov5s models to see if I can get decent models to lower GPU headroom, consider changing my GPU in the server, or offloading deepstack to my main PC with a far better GPU. @ndetar, you are a rockstar for helping me figure this out.
  6. So that's interesting. https://imgur.com/a/1uCqaWG I stripped the image and reinstalled, and it appears the GPU is now being taxed per nvidia-smi. What's funny, however, is that as soon as I try to load any custom models, it fails entirely. I expect I have headroom based on the ram utilization of 625mb/2000mb for the base models on high, but cannot actually recall how I pulled that more detailed log which suggested a CUDA memory issue. Correction, I found the command: Here it is: And the log: Traceback (most recent call last): File "/usr/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap self.run() File "/usr/lib/python3.7/multiprocessing/process.py", line 99, in run self._target(*self._args, **self._kwargs) File "/app/intelligencelayer/shared/detection.py", line 69, in objectdetection detector = YOLODetector(model_path, reso, cuda=CUDA_MODE) File "/app/intelligencelayer/shared/./process.py", line 36, in __init__ self.model = attempt_load(model_path, map_location=self.device) File "/app/intelligencelayer/shared/./models/experimental.py", line 159, in attempt_load torch.load(w, map_location=map_location)["model"].float().fuse().eval() File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 584, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 842, in _load result = unpickler.load() File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 834, in persistent_load load_tensor(data_type, size, key, _maybe_decode_ascii(location)) File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 823, in load_tensor loaded_storages[key] = restore_location(storage, location) File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 803, in restore_location return default_restore_location(storage, str(map_location)) File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 174, in default_restore_location result = fn(storage, location) File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 156, in _cuda_deserialize return obj.cuda(device) File "/usr/local/lib/python3.7/dist-packages/torch/_utils.py", line 77, in _cuda return new_type(self.size()).copy_(self, non_blocking) File "/usr/local/lib/python3.7/dist-packages/torch/cuda/__init__.py", line 480, in _lazy_new return super(_CudaBase, cls).__new__(cls, *args, **kwargs) RuntimeError: CUDA error: out of memory Same CUDA error. I'll fiddle with this to see if I can get any custom models to run. It'll be really disappointing for 2gb isn't enough for any.
  7. That was a good idea. I tried loading object detection only, but when checking nvidia-smi I'm still not seeing any GPU use. I'm wondering if the GPU isn't visible which is why its reading no ram.
  8. Hey @ndetar! Thanks for responding! I have loved your container and hope we can figure this out. I really appreciate your time and assistance. Screenshots: http://imgur.com/a/nkxBZcz Logs: Blockquoteroot@UNRAID:~# sudo docker exec -it DeepstackGPUOfficial /bin/bash root@ed10552468a7:/app/server# cat …/logs/stderr.txt Process Process-1: Traceback (most recent call last): File “/usr/lib/python3.7/multiprocessing/process.py”, line 297, in _bootstrap self.run() File “/usr/lib/python3.7/multiprocessing/process.py”, line 99, in run self._target(*self._args, **self._kwargs) File “/app/intelligencelayer/shared/detection.py”, line 69, in objectdetection detector = YOLODetector(model_path, reso, cuda=CUDA_MODE) File “/app/intelligencelayer/shared/./process.py”, line 36, in init self.model = attempt_load(model_path, map_location=self.device) File “/app/intelligencelayer/shared/./models/experimental.py”, line 159, in attempt_load torch.load(w, map_location=map_location)[“model”].float().fuse().eval() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 584, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 842, in _load result = unpickler.load() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 834, in persistent_load load_tensor(data_type, size, key, _maybe_decode_ascii(location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 823, in load_tensor loaded_storages[key] = restore_location(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 803, in restore_location return default_restore_location(storage, str(map_location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 174, in default_restore_location result = fn(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 156, in _cuda_deserialize return obj.cuda(device) File “/usr/local/lib/python3.7/dist-packages/torch/_utils.py”, line 77, in cuda return new_type(self.size()).copy(self, non_blocking) File “/usr/local/lib/python3.7/dist-packages/torch/cuda/init.py”, line 480, in _lazy_new return super(_CudaBase, cls).new(cls, *args, **kwargs) RuntimeError: CUDA error: out of memory Process Process-1: Traceback (most recent call last): File “/usr/lib/python3.7/multiprocessing/process.py”, line 297, in _bootstrap self.run() File “/usr/lib/python3.7/multiprocessing/process.py”, line 99, in run self._target(*self._args, **self._kwargs) File “/app/intelligencelayer/shared/detection.py”, line 69, in objectdetection detector = YOLODetector(model_path, reso, cuda=CUDA_MODE) File “/app/intelligencelayer/shared/./process.py”, line 36, in init self.model = attempt_load(model_path, map_location=self.device) File “/app/intelligencelayer/shared/./models/experimental.py”, line 159, in attempt_load torch.load(w, map_location=map_location)[“model”].float().fuse().eval() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 584, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 842, in _load result = unpickler.load() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 834, in persistent_load load_tensor(data_type, size, key, _maybe_decode_ascii(location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 823, in load_tensor loaded_storages[key] = restore_location(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 803, in restore_location return default_restore_location(storage, str(map_location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 174, in default_restore_location result = fn(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 156, in _cuda_deserialize return obj.cuda(device) File “/usr/local/lib/python3.7/dist-packages/torch/_utils.py”, line 77, in cuda return new_type(self.size()).copy(self, non_blocking) File “/usr/local/lib/python3.7/dist-packages/torch/cuda/init.py”, line 480, in _lazy_new return super(_CudaBase, cls).new(cls, *args, **kwargs) RuntimeError: CUDA error: out of memory Process Process-1: Traceback (most recent call last): File “/usr/lib/python3.7/multiprocessing/process.py”, line 297, in _bootstrap self.run() File “/usr/lib/python3.7/multiprocessing/process.py”, line 99, in run self._target(*self._args, **self._kwargs) File “/app/intelligencelayer/shared/detection.py”, line 69, in objectdetection detector = YOLODetector(model_path, reso, cuda=CUDA_MODE) File “/app/intelligencelayer/shared/./process.py”, line 36, in init self.model = attempt_load(model_path, map_location=self.device) File “/app/intelligencelayer/shared/./models/experimental.py”, line 159, in attempt_load torch.load(w, map_location=map_location)[“model”].float().fuse().eval() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 584, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 842, in _load result = unpickler.load() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 834, in persistent_load load_tensor(data_type, size, key, _maybe_decode_ascii(location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 823, in load_tensor loaded_storages[key] = restore_location(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 803, in restore_location return default_restore_location(storage, str(map_location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 174, in default_restore_location result = fn(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 156, in _cuda_deserialize return obj.cuda(device) File “/usr/local/lib/python3.7/dist-packages/torch/_utils.py”, line 77, in cuda return new_type(self.size()).copy(self, non_blocking) File “/usr/local/lib/python3.7/dist-packages/torch/cuda/init.py”, line 480, in _lazy_new return super(_CudaBase, cls).new(cls, *args, **kwargs) RuntimeError: CUDA error: out of memory Process Process-2: Traceback (most recent call last): File “/usr/lib/python3.7/multiprocessing/process.py”, line 297, in _bootstrap self.run() File “/usr/lib/python3.7/multiprocessing/process.py”, line 99, in run self._target(*self._args, **self._kwargs) File “/app/intelligencelayer/shared/face.py”, line 73, in face cuda=SharedOptions.CUDA_MODE, File “/app/intelligencelayer/shared/./recognition/process.py”, line 31, in init self.model = self.model.cuda() File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 458, in cuda return self._apply(lambda t: t.cuda(device)) File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 354, in _apply module._apply(fn) File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 354, in _apply module._apply(fn) File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 376, in _apply param_applied = fn(param) File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 458, in return self._apply(lambda t: t.cuda(device)) RuntimeError: CUDA error: out of memory Process Process-1: Traceback (most recent call last): File “/usr/lib/python3.7/multiprocessing/process.py”, line 297, in _bootstrap self.run() File “/usr/lib/python3.7/multiprocessing/process.py”, line 99, in run self._target(*self._args, **self._kwargs) File “/app/intelligencelayer/shared/scene.py”, line 65, in scenerecognition SharedOptions.CUDA_MODE, File “/app/intelligencelayer/shared/scene.py”, line 38, in init self.model = self.model.cuda() File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 458, in cuda return self._apply(lambda t: t.cuda(device)) File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 354, in _apply module._apply(fn) File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 376, in _apply param_applied = fn(param) File “/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py”, line 458, in return self._apply(lambda t: t.cuda(device)) RuntimeError: CUDA error: out of memory Process Process-1: Traceback (most recent call last): File “/usr/lib/python3.7/multiprocessing/process.py”, line 297, in _bootstrap self.run() File “/usr/lib/python3.7/multiprocessing/process.py”, line 99, in run self._target(*self._args, **self._kwargs) File “/app/intelligencelayer/shared/detection.py”, line 69, in objectdetection detector = YOLODetector(model_path, reso, cuda=CUDA_MODE) File “/app/intelligencelayer/shared/./process.py”, line 36, in init self.model = attempt_load(model_path, map_location=self.device) File “/app/intelligencelayer/shared/./models/experimental.py”, line 159, in attempt_load torch.load(w, map_location=map_location)[“model”].float().fuse().eval() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 584, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 842, in _load result = unpickler.load() File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 834, in persistent_load load_tensor(data_type, size, key, _maybe_decode_ascii(location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 823, in load_tensor loaded_storages[key] = restore_location(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 803, in restore_location return default_restore_location(storage, str(map_location)) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 174, in default_restore_location result = fn(storage, location) File “/usr/local/lib/python3.7/dist-packages/torch/serialization.py”, line 156, in _cuda_deserialize return obj.cuda(device) File “/usr/local/lib/python3.7/dist-packages/torch/_utils.py”, line 77, in cuda return new_type(self.size()).copy(self, non_blocking) File “/usr/local/lib/python3.7/dist-packages/torch/cuda/init.py”, line 480, in _lazy_new return super(_CudaBase, cls).new(cls, *args, **kwargs) RuntimeError: CUDA error: out of memory DeepStack: Version 2021.09.01 v1/vision/custom/dark v1/vision/custom/poolcam v1/vision/custom/unagi /v1/vision/face /v1/vision/face/recognize /v1/vision/face/register /v1/vision/face/match /v1/vision/face/list /v1/vision/face/delete /v1/vision/detection /v1/vision/scene p v1/restore Timeout Log: [GIN] 2021/10/01 - 19:46:30 | 500 | 1m0s | 54.86.50.139 | POST “/v1/vision/detection” [GIN] 2021/10/01 - 19:46:30 | 500 | 1m0s | 54.86.50.139 | POST “/v1/vision/detection”
  9. Has anyone recently had any luck using Deepstack with a GPU within Unraid? I've been using the CPU version of @ndetar's which has been working wonderfully, but I have been unable to get either his (which has great instructions for converting it to GPU) or the officially documented Deepstack Docker GPU image here working correctly. It does appear that Deepstack released a new version of GPU three days ago, but I have still not had luck either with the latest version or the second-most recent revision. I have nvidia-drivers up and running with a recommended device, but am still getting timeouts for some reason despite being able to confirm deepstacks activation. Any help is much appreciated!
  10. Turning off Docker in Settings does in fact resolve the issue, but I don't know how I might narrow it down more than that.
  11. Things seem to run fine until I start the array. I believe the issue is docker-related, though there have been no significant changes there and the system has otherwise been incredibly stable. As soon as I start the array, however, inevitably lose access to the webGUI and Putty will not respond. unraid-diagnostics-20210928-2114.zip
  12. Disregard. It appears excluding those discs from my shares helped.
  13. Is there a specific way to do that, or should I just spin down the discs?
  14. I'm getting extremely slow speeds on a parity rebuild as I put in a bigger drive. It seems to be getting progressively slower. Total size:2 TB Elapsed time:22 hours, 18 minutes Current position:1.88 TB (94.2 %) Estimated speed:2.5 MB/sec Estimated finish:12 hours, 57 minutes Sync errors corrected: I've attached my diagnostics file. Any help is much appreciated. unraid-diagnostics-20210928-0912.zip
  15. LIkewise. Fans set to PWM mode in BIOS but still can't be found.
  16. Hello, Unraid Community. Over the past 2-3 days, Unraid has suddenly become unstable and stops responding after the array is mounted. No significant changes to hardware or software have been made. The array did become close to full yesterday, which I resolved by deleted unneeded files, which appeared to resolve the issue at the time. This morning, unfortunately, Unraid was again unresponsive. I've attached the diagnostics file. Any assistance is greatly appreciated! -WC unraid-diagnostics-20210927-0757.zip
  17. That makes sense, Lol. I appreciate the response and your work as a dev!!! I'll see if I can't snag something more recent for this project.
  18. I have a old Geforce 520 I want to dedicate to Deepstack processing.
  19. Hello. I've been having problems with this freezing/not responding and it does not appear that updating the app (BlueIris) works. Can this be resolved. So happy BI is in a docker! Thank you!
  20. I have successfully mounted a drive using "Unassigned Devices", which I can see and read from, but when trying to copy files to that drive I now get errors from windows telling me the drive is "write protected". I have ensured "read only" is not checked and have tried both authenticated SMB mode as well as public settings, both of which still result in the same error. Any assistance is greatly appreciated!
  21. Having an issue with the docker. Log as as such: at com.tplink.omada.start.task.MetaDataInitTask.a(SourceFile:51) at com.tplink.omada.start.task.f.a(SourceFile:13) at com.tplink.omada.start.OmadaBootstrap.f(SourceFile:321) at com.tplink.omada.start.OmadaLinuxMain.b(SourceFile:87) at com.tplink.omada.start.OmadaLinuxMain.main(SourceFile:25) Caused by: java.io.IOException: No space left on device at java.io.FileOutputStream.writeBytes(Native Method) at java.io.FileOutputStream.write(FileOutputStream.java:326) at org.apache.logging.log4j.core.appender.OutputStreamManager.writeToDestination(OutputStreamManager.java:256) ... 27 more 2021-05-08 11:07:18,740 main ERROR Unable to write to stream ../logs/server.log for appender RollingFile: org.apache.logging.log4j.core.appender.AppenderLoggingException: Error writing to stream ../logs/server.log 2021-05-08 11:07:18,740 main ERROR An exception occurred processing Appender RollingFile org.apache.logging.log4j.core.appender.AppenderLoggingException: Error writing to stream ../logs/server.log at org.apache.logging.log4j.core.appender.OutputStreamManager.writeToDestination(OutputStreamManager.java:258) at org.apache.logging.log4j.core.appender.FileManager.writeToDestination(FileManager.java:177) at org.apache.logging.log4j.core.appender.rolling.RollingFileManager.writeToDestination(RollingFileManager.java:185) at org.apache.logging.log4j.core.appender.OutputStreamManager.flushBuffer(OutputStreamManager.java:288) at org.apache.logging.log4j.core.appender.OutputStreamManager.flush(OutputStreamManager.java:297) at org.apache.logging.log4j.core.appender.AbstractOutputStreamAppender.directEncodeEvent(AbstractOutputStreamAppender.java:179) at org.apache.logging.log4j.core.appender.AbstractOutputStreamAppender.tryAppend(AbstractOutputStreamAppender.java:170) at org.apache.logging.log4j.core.appender.AbstractOutputStreamAppender.append(AbstractOutputStreamAppender.java:161) at org.apache.logging.log4j.core.appender.RollingFileAppender.append(RollingFileAppender.java:268) at org.apache.logging.log4j.core.config.AppenderControl.tryCallAppender(AppenderControl.java:156) at org.apache.logging.log4j.core.config.AppenderControl.callAppender0(AppenderControl.java:129) at org.apache.logging.log4j.core.config.AppenderControl.callAppenderPreventRecursion(AppenderControl.java:120) at org.apache.logging.log4j.core.config.AppenderControl.callAppender(AppenderControl.java:84) at org.apache.logging.log4j.core.config.LoggerConfig.callAppenders(LoggerConfig.java:448) at org.apache.logging.log4j.core.config.LoggerConfig.processLogEvent(LoggerConfig.java:433) at org.apache.logging.log4j.core.config.LoggerConfig.log(LoggerConfig.java:417) at org.apache.logging.log4j.core.config.LoggerConfig.log(LoggerConfig.java:403) at org.apache.logging.log4j.core.config.AwaitCompletionReliabilityStrategy.log(AwaitCompletionReliabilityStrategy.java:63) at org.apache.logging.log4j.core.Logger.logMessage(Logger.java:146) at org.apache.logging.log4j.spi.AbstractLogger.logMessageSafely(AbstractLogger.java:2091) at org.apache.logging.log4j.spi.AbstractLogger.logMessage(AbstractLogger.java:1993) at org.apache.logging.log4j.spi.AbstractLogger.logIfEnabled(AbstractLogger.java:1852) at org.apache.logging.slf4j.Log4jLogger.error(Log4jLogger.java:299) at com.tplink.omada.start.task.FailExitTask.a(SourceFile:18) at com.tplink.omada.start.task.f.a(SourceFile:13) at com.tplink.omada.start.OmadaBootstrap.f(SourceFile:321) at com.tplink.omada.start.OmadaLinuxMain.b(SourceFile:87) at com.tplink.omada.start.OmadaLinuxMain.main(SourceFile:25) Caused by: java.io.IOException: No space left on device at java.io.FileOutputStream.writeBytes(Native Method) at java.io.FileOutputStream.write(FileOutputStream.java:326) at org.apache.logging.log4j.core.appender.OutputStreamManager.writeToDestination(OutputStreamManager.java:256) ... 27 more Failed to start omada controller, going to exit 2021-05-08 11:07:18 [main] [ERROR]-[SourceFile:51] - Failed to get WebApplicationContext, Met2021-05-08 11:07:19 [nioEventLoopGroup-5-1] [INFO]-[SourceFile:50] - Omada Controller isn't prepared to handle event 2021-05-08 11:07:27 [nioEventLoopGroup-5-1] [INFO]-[SourceFile:50] - Omada Controller isn't prepared to handle event ShutdownHook: service stopped.
  22. Negative. How would I assess port access? I did scan my LAN and can see Unraid associated with its correct IP, and it does seem to be acting as the workgroup master.