New Features and Improvements
- Add support for decorated pipeline steps (#1154)
- Improve
torch.distributed
behavior and auto-detect Huggingfaceaccelerate
distributed execution - Improve
jsonargparse
integration:allow_config_file_override_from_ui
argument added for enabling/disabling overriding configuration file entries - Add
raise_on_error
parameter toModel.update_weights()
andModel.update_weights_package()
- Add HPO multi-objective optimization support by specifying multiple optimization objectives to the
HyperParameterOptimizer
class - Improve pipelines from functions: libraries used by pipeline steps no longer have to be imported in the step itself and can be imported globally instead
- Support clearing repository details in
task.set_repo()
- Auto detect
tensorflow-intel
astensorflow
- Add support for auto detecting torch and transformers accelerate distributed execution
- Add tabular data multi-stage pipeline process example
Bug Fixes
- Fix
langchain
integration (#1124, #1126) - Fix using
target_project
withTaskScheduler.add_task()
corrupts project if used with pipelines (#1137) - Fix
PipelineController.add_function_step()
fails when adding custom decorated step (#1154) - Fix
jsonargparse
binding does not capture parameters beforeTask.init()
is called (#1164) - Fix invalid
jsonargparse
arguments should be deleted - Fix handling of appended parameters to Hydra defaults list
- Fix
Task.set_repo()
andTask.set_packages()
do not wait for automatic asynchronous repository detection - Fix active GPU filtering in resource monitor to support GPU ID and not just GPU idx
- Fix misleading error raised when using the SDK with no configuration file or an invalid configuration file
- Fix process sometimes hangs issue by improving exit and exception handlers, unregistering signal handling in child processes except for the
BackgroundMonitor