Setup loss_type in config at model init time

[ChanderG]

ensures no additional graph break introduced when torch.compile'ed

fixes #34615

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Fixes # (issue)

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[ChanderG]

If this approach is fine - I will extend the PR to cover a wide set of models.

[qubvel]

Hi @ChanderG! Thanks for opening an issue and PR! Nice catch with the graph breaks!
Re the PR it is usually not the best decision to modify class attribute inplace, however this pattern is widely used across classification models losses

if self.num_labels == 1:
    self.config.problem_type = "regression"
elif self.num_labels > 1 and (labels.dtype == torch.long or labels.dtype == torch.int):
    self.config.problem_type = "single_label_classification"
else:
    self.config.problem_type = "multi_label_classification"

do you have other ideas on how to handle it without modifying the config attribute? Is there a way to fix re.findall instead of introducing the change for all models?

Alternatively we can have a model attribute, smth like

self.loss_type = "ForCausalLM" if self.config.loss_type is None else self.config.loss_type

but not feel strong re this :)