train error RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory

[HBing110]

2022-08-17 18:04:11,080 - pytorch_lightning.utilities.seed - INFO - Global seed set to 42 2022-08-17 18:04:19,450 - anomalib.data - INFO - Loading the datamodule 2022-08-17 18:05:06,595 - anomalib.models - INFO - Loading the model. 2022-08-17 18:07:20,438 - anomalib.models.components.base.anomaly_module - INFO - Initializing PadimLightning model. F:\ProgramData\Anaconda3\envs\anoma\lib\site-packages\torchmetrics\utilities\prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called full_state_update that has not been set for this class (AdaptiveThreshold). The property determines if update by default needs access to the full metric state. If this is not the case, significant speedups can be achieved and we recommend setting this to False. We provide an checking function from torchmetrics.utilities import check_forward_no_full_state that can be used to check if the full_state_update=True (old and potential slower behaviour, default for now) or if full_state_update=False can be used safely.

warnings.warn(*args, *kwargs) F:\ProgramData\Anaconda3\envs\anoma\lib\site-packages\torchmetrics\utilities\prints.py:36: UserWarning: Metric PrecisionRecallCurve will save all targets and predictions in buffer. For large datasets this may lead to large memory footprint. warnings.warn(args, **kwargs) F:\ProgramData\Anaconda3\envs\anoma\lib\site-packages\torchmetrics\utilities\prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called full_state_update that has not been set for this class (AnomalyScoreDistribution). The property determines if update by default needs access to the full metric state. If this is not the case, significant speedups can be achieved and we recommend setting this to False. We provide an checking function from torchmetrics.utilities import check_forward_no_full_state that can be used to check if the full_state_update=True (old and potential slower behaviour, default for now) or if full_state_update=False can be used safely.

warnings.warn(*args, **kwargs) F:\ProgramData\Anaconda3\envs\anoma\lib\site-packages\torchmetrics\utilities\prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called full_state_update that has not been set for this class (MinMax). The property determines if update by default needs access to the full metric state. If this is not the case, significant speedups can be achieved and we recommend setting this to False. We provide an checking function from torchmetrics.utilities import check_forward_no_full_state that can be used to check if the full_state_update=True (old and potential slower behaviour, default for now) or if full_state_update=False can be used safely.

warnings.warn(*args, **kwargs) Traceback (most recent call last): File "F:\ProgramData\Anaconda3\envs\anoma\lib\site-packages\torch\serialization.py", line 705, in load with _open_zipfile_reader(opened_file) as opened_zipfile: File "F:\ProgramData\Anaconda3\envs\anoma\lib\site-packages\torch\serialization.py", line 243, in init super(_open_zipfile_reader, self).init(torch._C.PyTorchFileReader(name_or_buffer)) RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory python-BaseException

Process finished with exit code 1

[djdameln]

Hi, are you still experiencing this issue? Could you maybe provide some more details so we can try to replicate the error?

• Which version of Anomalib did you use and how did you install Anomalib?
• What are the contents of your config.yaml file?
• Which commands did you use to run Anomalib?
• Some information about your system configuration would also be useful, such as which operating system and GPU.

[djdameln]

Closing this issue due to inactivity. Feel free to re-open if the problem persists.