ds

游雁

2024-05-20 bbd300a91184d09dec56a3b06734051dbd5812e4

 funasr/train_utils/average_nbest_models.py

@@ -16,7 +16,7 @@
from functools import cmp_to_key


def _get_checkpoint_paths(output_dir: str, last_n: int = 5):
def _get_checkpoint_paths(output_dir: str, last_n: int = 5, use_deepspeed=False, **kwargs):
    """
    Get the paths of the last 'last_n' checkpoints by parsing filenames
    in the output directory.
@@ -29,7 +29,13 @@
        sorted_items = (
            sorted_items[:last_n] if avg_keep_nbest_models_type == "acc" else sorted_items[-last_n:]
        )
        checkpoint_paths = [os.path.join(output_dir, key) for key, value in sorted_items[:last_n]]
        checkpoint_paths = []
        for key, value in sorted_items[:last_n]:
            if not use_deepspeed:
                ckpt = os.path.join(output_dir, key)
            else:
                ckpt = os.path.join(output_dir, key, "mp_rank_00_model_states.pt")

    except:
        print(f"{checkpoint} does not exist, avg the lastet checkpoint.")
        # List all files in the output directory
@@ -49,7 +55,7 @@
    Average the last 'last_n' checkpoints' model state_dicts.
    If a tensor is of type torch.int, perform sum instead of average.
    """
    checkpoint_paths = _get_checkpoint_paths(output_dir, last_n)
    checkpoint_paths = _get_checkpoint_paths(output_dir, last_n, **kwargs)
    print(f"average_checkpoints: {checkpoint_paths}")
    state_dicts = []