0.39.0

This is a promotion of 0.39.0rc1

Changed

• BREAKING: Input and output of aggregate tasks are now shared_state. It provides more flexibility to link different type of tasks with each other. To use
  download_aggregate_shared_state on experiments launched before this commit, you can use the following code as a replacement of the function
  (#142).

import tempfile
from substrafl.model_loading import _download_task_output_files
from substrafl.model_loading import _load_from_files
with tempfile.TemporaryDirectory() as temp_folder:
    _download_task_output_files(
        client=<client>,
        compute_plan_key=<compute_plan_key>,
        dest_folder=temp_folder,
        round_idx=<round_idx>,
        rank_idx=<rank_idx>,
        task_type="aggregate",
        identifier="model",
    )
    aggregated_state = _load_from_files(input_folder=temp_folder, remote=True)

Removed

• Function wait in utils. You can use substra.Client.wait_task & substra.Client.wait_compute_plan instead. (#147)

Fixed

• Compatibility with GPU devices when running torch based experiments (#154)
• Pin pydantic to >=1.9.0 & <2.0.0 as pydantic v 2.0.0 has been released with a lot of non backward compatible changes. (#148)