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Hey, We Are Using Clearml 1.9.0 With Transformers 4.25.1… And We Started Getting Errors That Do Not Reproduce In Earlier Versions (Only Works In 1.7.2 All 1.8.X Don’T Work):

Hey,
We are using clearml 1.9.0 with transformers 4.25.1… and we started getting errors that do not reproduce in earlier versions (only works in 1.7.2 all 1.8.x don’t work):

File "/tmp/tmp0you5mai.py", line 29, in train_entity_exraction_model train(source=source_path.absolute(), output=model_output_path.absolute(), seed=seed, **entity_extraction_trainer) File "/usr/src/lib/entity_extractions/train.py", line 74, in train trainer.train() File "/opt/conda/lib/python3.10/site-packages/transformers/trainer.py", line 1527, in train return inner_training_loop( File "/opt/conda/lib/python3.10/site-packages/transformers/trainer.py", line 1704, in _inner_training_loop self.control = self.callback_handler.on_train_begin(args, self.state, self.control) File "/opt/conda/lib/python3.10/site-packages/transformers/trainer_callback.py", line 353, in on_train_begin return self.call_event("on_train_begin", args, state, control) File "/opt/conda/lib/python3.10/site-packages/transformers/trainer_callback.py", line 397, in call_event result = getattr(callback, event)( File "/opt/conda/lib/python3.10/site-packages/transformers/integrations.py", line 1355, in on_train_begin self.setup(args, state, model, tokenizer, **kwargs) File "/opt/conda/lib/python3.10/site-packages/transformers/integrations.py", line 1345, in setup self._clearml_task.connect(args, "Args") File "/opt/conda/lib/python3.10/site-packages/clearml/task.py", line 1480, in connect return method(mutable, name=name) File "/opt/conda/lib/python3.10/site-packages/clearml/task.py", line 3449, in _connect_object a_dict = self._connect_dictionary(a_dict, name) File "/opt/conda/lib/python3.10/site-packages/clearml/task.py", line 3413, in _connect_dictionary flat_dict = self._arguments.copy_to_dict(flat_dict, prefix=name) File "/opt/conda/lib/python3.10/site-packages/clearml/backend_interface/task/args.py", line 508, in copy_to_dict self._task.set_parameter((prefix or '') + k, v) File "/opt/conda/lib/python3.10/site-packages/clearml/backend_interface/task/task.py", line 1281, in set_parameter self._set_parameters( File "/opt/conda/lib/python3.10/site-packages/clearml/backend_interface/task/task.py", line 1246, in _set_parameters description=create_description(), File "/opt/conda/lib/python3.10/site-packages/clearml/backend_interface/task/task.py", line 1237, in create_description created_description += "Values:\n" + ",\n".join( TypeError: unsupported operand type(s) for +=: 'NoneType' and 'str'

  
  
Posted one year ago
Votes Newest

Answers 62


i’ll try to work on something that works on 1.7.2

  
  
Posted one year ago

thank Lior

  
  
Posted one year ago

of course

  
  
Posted one year ago

@<1523701435869433856:profile|SmugDolphin23>
Hey 🙂
Any update?

We are having more issues with transformers and clearml in their new version.
The step that has transformers 4.25.1 isn’t able to upload artifacts.
If we downgrade transformers==4.21.3 it works

  
  
Posted one year ago

will check

  
  
Posted one year ago

Hi @<1523701949617147904:profile|PricklyRaven28> sorry that this is happening. I tried to run your minimal example, but get a IndexError: Invalid key: 5872 is out of bounds for size 0 error. That said, I get the same error without the code running in a pipeline. There seems to be no difference between simply running the code and the pipeline (for me). Do you have an updated example, maybe also including getting a local copy of an artifact, so I can check?

  
  
Posted one year ago

Hey 🙂 Thanks for the update!

what i’m missing the is the point where you report to clearml between cast and casting back 🤔

  
  
Posted one year ago

The version is v1.9.1

  
  
Posted one year ago

Nothing that i think is relevant, I'm using latest from master. It might be a new bug on their side, wasn't sure.

  
  
Posted one year ago

Hey @<1523701949617147904:profile|PricklyRaven28> , about the S3 loading issue. The path to the model in the artifact tab, is it an S3 bucket or a local path?

  
  
Posted one year ago

SmugDolphin23 BTW, this is using clearml and huggingface’s automatic logging… didn’t log something manual

  
  
Posted one year ago

@<1523701435869433856:profile|SmugDolphin23> @<1523701087100473344:profile|SuccessfulKoala55> Yes, the second issue still consists, currently breaking our pipeline

  
  
Posted one year ago

yeah, it gets to that error because the previous issue is saved…i’ll try to work on a new example

  
  
Posted one year ago

I'm getting really weird behavior now, the task seems to report correctly with the patch... but the step doesn't say "uploading" when finished... there is a "return" artifact but it doesn't exist on S3 (our file server configuration)

  
  
Posted one year ago

Hi @<1523701949617147904:profile|PricklyRaven28> just letting you know I still have this on my TODO, I'll update you as soon as I have something!

  
  
Posted one year ago

i believe this is because of transformer’s integration:

Automatic ClearML logging enabled.
ClearML Task has been initialized.

when a task already exists

  
  
Posted one year ago

@<1523701949617147904:profile|PricklyRaven28> Please use this patch instead of the one previously shared. It excludes the dict hack :)

  
  
Posted one year ago

However, I actually do think I can already open the Huggingface PR in the meantime. It has actually relatively little to do with the second bug.

  
  
Posted one year ago

We'll check it out 👍

  
  
Posted one year ago

I tried to work on a reproducible script but then i get errors that my clearml task is already initialized (also doesn’t happen on 1.7.2)

  
  
Posted one year ago

It should, but please check first. This is some code I quickly made for myself. It did make tests for it, but it would be nice to hear from someone else that it worked (as evidenced by the error above 😅 )

  
  
Posted one year ago

sounds good 🙂 I’ll soon check if this fixes our issue and update you

  
  
Posted one year ago

Good to hear 🙏

  
  
Posted one year ago

Hey @<1523701949617147904:profile|PricklyRaven28> I'm checking! Have you updated anything else and on which exact commit of transformers are you now?

  
  
Posted one year ago

Hi PricklyRaven28 ! What dict do you connect? Do you have a small script we could use to reproduce?

  
  
Posted one year ago

This is the next step not being able to find the output of the last step

ValueError: Could not retrieve a local copy of artifact return_object, failed downloading 
  
  
Posted one year ago

Now worries! Just so I understand fully though: you were already using the patch with success from my branch. Now that it has been merged into transformers main branch you installed it from there and that's when you started having issues with not saving models? Then installing transformers 4.21.3 fixes it (which should have the old clearml integration even before the patch?)

  
  
Posted one year ago

Yes, and the old version only works without the patch.
I see the model on the artifacts tab, but it's not actually uploaded.

  
  
Posted one year ago

It's been accepted in master, but was not released yet indeed!

As for the other issue, it seems like we won't be adding support for non-string dict keys anytime soon. I'm thinking of adding a specific example/tutorial on how to work with Huggingface + ClearML so people can do it themselves.

For now (using the patch) the only thing you need to be careful about is to not connect a dict or object with ints as keys. If you do need to (e.g. ususally huggingface models need the id2label dict somewhere) just make sure to cast it to string before connecting it to ClearML and casting it back to int directly after. So that when ClearML changes the value, it's properly taken care of 🙂 My previous sample code is still valid!

  
  
Posted one year ago

Allright, a bit of searching later and I've found 2 things:

  • You were right about the task! I've staged a fix here . It basically detects whether a task is already running (e.g. from the pipelinedecorator component) and if so, uses that task instead. We should probably do this for all of our integrations.
  • But then I found another bug. Basically the pipeline decorator task would mess up the internal nested dict of the label mapping inside of the model config. You will probably have the same issue if you run the pipeline with my fix above.
    So for now, we're looking into the 2nd bug, because it breaks with Hugging Face models in a pipeline. Until we sort that out, I'm going to hold off on opening a PR to HF with the first fix. Makes sense?

Thanks a lot for the example, it helped tons to be able to reproduce!

  
  
Posted one year ago
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