chore(utils): add type annotations to public functions in utils.py#2237
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nuthalapativarun wants to merge 3 commits into
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chore(utils): add type annotations to public functions in utils.py#2237nuthalapativarun wants to merge 3 commits into
nuthalapativarun wants to merge 3 commits into
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Add Python 3.10+ style type annotations to 13 public and semi-public functions in litgpt/utils.py that were missing parameter or return type annotations: - choose_logger: add -> Any return type - get_argument_names: add cls: type param and -> set[str] return type - instantiate_bnb_optimizer: add optimizer: str | dict, model_parameters: Any, -> Any - instantiate_torch_optimizer: add optimizer: str | dict, model_parameters: Any, **kwargs: Any, -> torch.optim.Optimizer - check_file_size_on_cpu_and_warn: add checkpoint_path: Path | str, device: torch.device | str, size_limit: int, -> float - auto_download_checkpoint: add model_name: str, access_token: str | None, ignore_tokenizer_files: bool, -> Path - check_nvlink_connectivity: add fabric: L.Fabric | None, -> None - _check_nvidia_connectivity: add custom_print: Any, -> None - _check_amd_connectivity: add custom_print: Any, -> None - fix_and_load_json: add s: str, -> Any - create_finetuning_performance_report: add training_time: float, token_counts: dict[str, int], device_type: str, -> str - select_sft_generate_example: add eval: Any, data: Any, -> str - kill_process_tree: add -> None - _RunIf: add **kwargs: Any, -> Any
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What does this PR do?
Adds Python 3.10+ style type annotations to 13 functions in
litgpt/utils.pythat were missing parameter or return type annotations. This follows the pattern established in #2221 (which bumped the rufftarget-versiontopy310and updated type annotations across the codebase).Functions annotated
choose_logger-> Anyget_argument_namescls: type,-> set[str]instantiate_bnb_optimizeroptimizer: str | dict,model_parameters: Any,-> Anyinstantiate_torch_optimizeroptimizer: str | dict,model_parameters: Any,**kwargs: Any,-> torch.optim.Optimizercheck_file_size_on_cpu_and_warncheckpoint_path: Path | str,device: torch.device | str,size_limit: int,-> floatauto_download_checkpointmodel_name: str,access_token: str | None,ignore_tokenizer_files: bool,-> Pathcheck_nvlink_connectivityfabric: L.Fabric | None,-> None_check_nvidia_connectivitycustom_print: Any,-> None_check_amd_connectivitycustom_print: Any,-> Nonefix_and_load_jsons: str,-> Anycreate_finetuning_performance_reporttraining_time: float,token_counts: dict[str, int],device_type: str,-> strselect_sft_generate_exampleeval: Any,data: Any,-> strkill_process_tree-> None_RunIf**kwargs: Any,-> AnyNo new imports were needed. All existing tests pass.