fastmonai-upstream-guide

To align fastMONAI transforms, consult official MONAI and TorchIO source code to extract function signatures and architectural conventions before implementing new transform wrappers. This documentation-first approach ensures your custom preprocessing pipelines match upstream patterns exactly.

The best way to implement new loss functions is to retrieve and compare official MONAI and nnU-Net documentation to verify function defaults and signatures. Referencing these raw source files informs your design decisions and maintains consistency across training workflows.

Yes, you can implement nnU-Net patch-based workflows in fastMONAI by consulting nnU-Net source code to map its architectural conventions. This upstream alignment process extracts the necessary patterns to build consistent patch extraction and training pipelines.

Metric signature differences occur when custom implementations deviate from MONAI upstream patterns. Retrieve the raw source files from MONAI to verify the exact function defaults and signatures, ensuring your metric wrappers follow the official conventions precisely.

Yes, referencing raw source files from TorchIO and MONAI is required to extract function defaults and architectural conventions for new preprocessing pipelines. Consulting official documentation ensures your implementations align with established upstream library patterns.

The limitation is that upstream MONAI documentation may not cover fastMONAI-specific wrapper requirements, requiring you to consult raw source files to extract exact function signatures and defaults. This ensures architectural alignment but demands manual verification for custom components.