Update setup logic in model and datamodule

[djdameln]

📝 Description

Minor change in how we check if self._setup should be called in setup. The change is repeated in both the datamodule and the anomaly module. This is mainly to ensure that we can use the modules in a standalone fashion, without/before being attached to a trainer. For example, we could use the following to quickly inspect the images in our datamodule.

>>> from anomalib.data import MVTec
>>>
>>> datamodule = MVTec(image_size=(512, 512))
>>> datamodule.setup()
>>>
>>> sample = next(iter(datamodule.train_dataloader()))
>>> sample["image"].shape
torch.Size([32, 3, 512, 512])

Similarly, we could inspect the structure of the torch model of a given Lightning model after invoking setup:

>>> from anomalib.models import Ganomaly
>>>
>>> model = Ganomaly()
>>> model.setup()
>>>
>>> model.model.generator.encoder1.input_layers
Sequential(
  (initial-conv-3-64): Conv2d(3, 64, kernel_size=(4, 4), stride=(2, 2), padding=(4, 4), bias=False)
  (initial-relu-64): LeakyReLU(negative_slope=0.2, inplace=True)
)

Without the current change, this would lead to problems downstream when the entrypoints of the engine are called.

✨ Changes

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• 🐞 Bug fix (non-breaking change which fixes an issue)
• 🔨 Refactor (non-breaking change which refactors the code base)
• 🚀 New feature (non-breaking change which adds functionality)
• 💥 Breaking change (fix or feature that would cause existing functionality to not work as expected)
• 📚 Documentation update
• 🔒 Security update

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[samet-akcay]

Thanks, only a single comment...

[samet-akcay]

Great, thanks!