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AMD and AMD + WSL
PDC CLI is for CPTAC data
So the user can pick one based on required profile
…ativebioinformatics/OncoLearn into feature-data-downloader
- Combines common docker configs - Faster building on WSL - Corrects dev-nvidia in the devcontainer
…ownloader Add cpu to dev containers & add toml extension
…loader [Feature] Data downloading scripts
- Added YAML error handling in XenaCohortBuilder to raise ValueError for invalid configurations. - Filtered empty cohort names in download script to prevent processing errors. - Initialized _full_dataset in ImageDataModule and ClinicalDataModule to improve data handling. - Updated PillowLoader to provide more informative error messages for image loading failures. - Improved dataset validation in MultimodalDataModule to ensure only valid labels are processed. - Enhanced encoder classes to conditionally freeze models based on configuration settings.
- Enhanced OncoTrainer to support hyperparameter optimization (HPO) using Optuna, including a new method to run HPO and apply best parameters to the training configuration. - Updated L1 regularization calculation in BaseOncoClassifier to only include parameters that require gradients. - Changed the registration string for GatedLateFusionConfig to include the full module path. - Adjusted gradient clipping value handling in OncoTrainer to ensure it is only applied when greater than zero. - Updated dependency management in `uv.lock` to include new packages: alembic, colorlog, greenlet, mako, optuna, and sqlalchemy, along with their respective versions and dependencies.
…ic assay data; enhance API client with retry logic
…zer and loss parameter handling in YAML and code
…function flexibility
…d later to "data/source"
- Introduced unit tests for the pipeline executor in `test_pipeline_executor.py`, covering various scenarios including loading data, joining datasets, and handling errors. - Added unit tests for pipeline nodes in `test_pipeline_nodes.py`, validating default behaviors and configurations for `DataSource`, `Load`, `Join`, `Sequence`, and modality classes. - Refactored image and multimodal data modules to improve structure and consistency in `test_image_e2e.py`, `test_multimodal_e2e.py`, and `test_tabular_e2e.py`. - Updated configuration tests in `test_config.py` to reflect changes in the pipeline-based schema and removed deprecated modality tests. - Consolidated data module tests in `test_datamodules.py` to focus on the new `ImageDataModule` and removed legacy tests for `GeneDataModule` and `ClinicalDataModule`. - Enhanced the dataset registry tests in `test_registry.py` to include dataset registration and retrieval functionalities.
…e labels; refactor data modules and add Log2Normalization support
- Created train and test split files for fold 0 to fold 4 in the PAM50 and stage datasets. - Implemented logging functionality to capture the KFold generation process, including patient counts and splits. - Updated Docker Compose configuration to mount the configs directory for easier access within containers. - Enhanced the kfold.py script to log output to a file while also displaying it in the console.
…metrics logging callback
…ctions and key capabilities section
…iomnics Refactor Multimodal
…iner Add linting arguments to dev containers
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