model training with custom dataset

Hello, When I am starting the training model with custom dataset , I got this problem. I face this issue first time. Can you help me?

thanks,

(env) (base) zeynep_automi_ai@anomalib:~/zeynep/anomalib$ python tools/train.py --config anomalib/models/padim/config_orange.yaml /home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/pytorch_lightning/utilities/cli.py:95: LightningDeprecationWarning: LightningCLI’s registries were deprecated in v1.7 and will be removed in v1.9. Now any imported subclass is automatically available by name in LightningCLI without any need to explicitly register it. rank_zero_deprecation(_deprecate_registry_message) /home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/pytorch_lightning/utilities/cli.py:95: LightningDeprecationWarning: LightningCLI’s registries were deprecated in v1.7 and will be removed in v1.9. Now any imported subclass is automatically available by name in LightningCLI without any need to explicitly register it. rank_zero_deprecation(_deprecate_registry_message) 2022-08-03 12:40:42,241 - pytorch_lightning.utilities.seed - INFO - Global seed set to 42 2022-08-03 12:40:42,242 - anomalib.data - INFO - Loading the datamodule 2022-08-03 12:40:42,244 - anomalib.models - INFO - Loading the model. 2022-08-03 12:40:42,389 - torch.distributed.nn.jit.instantiator - INFO - Created a temporary directory at /tmp/tmpm7a9yqli 2022-08-03 12:40:42,390 - torch.distributed.nn.jit.instantiator - INFO - Writing /tmp/tmpm7a9yqli/_remote_module_non_sriptable.py 2022-08-03 12:40:42,400 - anomalib.models.components.base.anomaly_module - INFO - Initializing PadimLightning model. /home/zeynep_automi_ai/zeynep/env/lib/python3.9/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) /home/zeynep_automi_ai/zeynep/env/lib/python3.9/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) /home/zeynep_automi_ai/zeynep/env/lib/python3.9/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) /home/zeynep_automi_ai/zeynep/env/lib/python3.9/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) 2022-08-03 12:40:42,931 - anomalib.utils.loggers - INFO - Loading the experiment logger(s) 2022-08-03 12:40:42,932 - anomalib.utils.callbacks - INFO - Loading the callbacks /home/zeynep_automi_ai/zeynep/anomalib/anomalib/utils/callbacks/init.py:162: UserWarning: log_images_to parameter is deprecated and will be removed in version 0.3.4. Please use the visualization.log_images and visualization.save_images parameters instead. warnings.warn( Traceback (most recent call last): File “/home/zeynep_automi_ai/zeynep/anomalib/tools/train.py”, line 82, in <module> train() File “/home/zeynep_automi_ai/zeynep/anomalib/tools/train.py”, line 67, in train callbacks = get_callbacks(config) File “/home/zeynep_automi_ai/zeynep/anomalib/anomalib/utils/callbacks/init.py”, line 112, in get_callbacks add_visualizer_callback(callbacks, config) File “/home/zeynep_automi_ai/zeynep/anomalib/anomalib/utils/callbacks/init.py”, line 168, in add_visualizer_callback if “local” in config.project.log_images_to: File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/dictconfig.py”, line 357, in getattr self._format_and_raise( File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/base.py”, line 231, in _format_and_raise format_and_raise( File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/_utils.py”, line 873, in format_and_raise _raise(ex, cause) File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/_utils.py”, line 771, in _raise raise ex.with_traceback(sys.exc_info()[2]) # set env var OC_CAUSE=1 for full trace File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/dictconfig.py”, line 353, in getattr return self._get_impl( File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/dictconfig.py”, line 444, in _get_impl node = self._get_child( File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/basecontainer.py”, line 73, in _get_child child = self._get_node( File “/home/zeynep_automi_ai/zeynep/env/lib/python3.9/site-packages/omegaconf/dictconfig.py”, line 482, in _get_node raise ConfigKeyError(f"Missing key {key!s}") omegaconf.errors.ConfigAttributeError: Missing key log_images_to full_key: project.log_images_to object_type=dict

[ZeynepRuveyda]

thanks @ashwinvaidya17 and @samet-akcay

[ashwinvaidya17]

I think the issue you are facing is because the configuration for logging images has changed in this PR https://github.com/openvinotoolkit/anomalib/pull/390. Since you are using a custom configuration, you will have to update it to something similar

visualization:
  show_images: False # show images on the screen
  save_images: True # save images to the file system
  log_images: True # log images to the available loggers (if any)
  image_save_path: null # path to which images will be saved
  mode: full # options: ["full", "simple"]