perceiver-io 0.7b1

Data preprocessing and documentation enhancements, major refactorings

Functional enhancements:

• Support for static word masking in addition to dynamic word masking.
• Support for individual token masking in addition to whole word masking.
• Task-specific data preprocessing for all supported text datasets.
• Constant learning rate scheduler with warmup now used by default.

Documentation enhancements:

• All training examples now provided as command line and Python script.
• Better overview of official models and example training checkpoints.
• Example training checkpoints can now be downloaded individually.
• Minor enhancements to all other documentation sections.

Refactorings and breaking changes:

• Rename image package to vision.
• TextDataModule base class now implements complete preprocessing logic.
• TextDataModule subclasses only convert source dataset to a common structure.
• Abstraction over cross-attention query creation (QueryProvider).
• Decouple OutputAdapter interface from trainable cross-attention query.
• Implement learned positions encodings as nn.Embedding.
• Move adapters to separate perceiver.model.core.adapter module.
• Rename PerceiverConfig to PerceiverIOConfig
• Rename LitModel base class to LitPerceiverIO.
• LitClassifier.forward now behaves like the wrapped model's forward.
• Object-oriented design of conversion from Hugging Face Perceiver models.
• Major refactoring of PerceiverAR and CausalLanguageModel.
• Move FourierPositionEncoding to perceiver.model.core.position` module.