





'''simple docstring'''





from __future__ import annotations


def        __snake_case       (						lowerCAmelCase_   ,       lowerCAmelCase_  )							->	List[str]:
    SCREAMING_SNAKE_CASE__       							= 0
    SCREAMING_SNAKE_CASE__       							= len(_A  ) - 1
    while left <= right:
        SCREAMING_SNAKE_CASE__       							= (left + right) // 2
        if left == right:
            if sorted_list[middle] < item:
                SCREAMING_SNAKE_CASE__       							= middle + 1
            break
        elif sorted_list[middle] < item:
            SCREAMING_SNAKE_CASE__       							= middle + 1
        else:
            SCREAMING_SNAKE_CASE__       							= middle - 1
    sorted_list.insert(_A   ,       _A  )
    return sorted_list


def        __snake_case       (						lowerCAmelCase_   ,       lowerCAmelCase_  )							->	Optional[int]:
    SCREAMING_SNAKE_CASE__       							= []
    while left and right:
        if left[0][0] < right[0][0]:
            result.append(left.pop(0  )  )
        else:
            result.append(right.pop(0  )  )
    return result + left + right


def        __snake_case       (						lowerCAmelCase_  )							->	int:
    SCREAMING_SNAKE_CASE__       							= len(_A  )
    if length <= 1:
        return list_ad
    SCREAMING_SNAKE_CASE__       							= length // 2
    return merge(sortlist_ad(list_ad[:middle]  )   ,       sortlist_ad(list_ad[middle:]  )  )


def        __snake_case       (						lowerCAmelCase_  )							->	Tuple:


    if len(_A  ) <= 1:
        return collection
    SCREAMING_SNAKE_CASE__       							= []
    SCREAMING_SNAKE_CASE__       							= False
    for i in range(0   ,       len(_A  )   ,       2  ):
        if i == len(_A  ) - 1:
            SCREAMING_SNAKE_CASE__       							= True
        else:
            if collection[i] < collection[i + 1]:
                two_paired_list.append([collection[i], collection[i + 1]]  )
            else:
                two_paired_list.append([collection[i + 1], collection[i]]  )
    SCREAMING_SNAKE_CASE__       							= sortlist_ad(_A  )
    SCREAMING_SNAKE_CASE__       							= [i[0] for i in sorted_list_ad]
    result.append(sorted_list_ad[-1][1]  )
    if has_last_odd_item:
        SCREAMING_SNAKE_CASE__       							= collection[-1]
        SCREAMING_SNAKE_CASE__       							= binary_search_insertion(_A   ,       _A  )
    SCREAMING_SNAKE_CASE__       							= False
    for i in range(len(_A  ) - 1  ):
        if result[i] == collection[-1] and has_last_odd_item:
            SCREAMING_SNAKE_CASE__       							= True
        SCREAMING_SNAKE_CASE__       							= sorted_list_ad[i][1]
        # If last_odd_item is inserted before the item's index,
        # you should forward index one more.
        if is_last_odd_item_inserted_before_this_index:
            SCREAMING_SNAKE_CASE__       							= result[: i + 2] + binary_search_insertion(result[i + 2 :]   ,       _A  )
        else:
            SCREAMING_SNAKE_CASE__       							= result[: i + 1] + binary_search_insertion(result[i + 1 :]   ,       _A  )

    return result


if __name__ == "__main__":
  _A				:							int							= input("""Enter numbers separated by a comma:\n""").strip()
  _A				:							Tuple							= [int(item) for item in user_input.split(""",""")]
  print(merge_insertion_sort(unsorted))







import os
from pathlib import Path
from typing import Dict, List

import fire
import torch

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.utils.logging import get_logger


_A				:							Any							= get_logger(__name__)


def        __snake_case       (						lowerCAmelCase_   ,       lowerCAmelCase_  )							->	str:
    if text.startswith(lowerCAmelCase_  ):
        return text[len(lowerCAmelCase_  ) :]
    return text  # or whatever


def        __snake_case       (						lowerCAmelCase_  )							->	Union[str, Any]:
    return {remove_prefix(lowerCAmelCase_   ,       '''model.'''  ): v for k, v in sd.items()}


def        __snake_case       (						lowerCAmelCase_  )							->	Optional[int]:
    SCREAMING_SNAKE_CASE__       							= {}
    for k in state_dicts[0].keys():
        SCREAMING_SNAKE_CASE__       							= [sd[k] for sd in state_dicts]
        SCREAMING_SNAKE_CASE__       							= sum(lowerCAmelCase_  ) / len(lowerCAmelCase_  )
        assert isinstance(lowerCAmelCase_   ,       torch.Tensor  )
        SCREAMING_SNAKE_CASE__       							= new_t
    return new_sd


def        __snake_case       (						lowerCAmelCase_   ,       lowerCAmelCase_   ,       lowerCAmelCase_  )							->	None:
    SCREAMING_SNAKE_CASE__       							= AutoModelForSeqaSeqLM.from_pretrained(lowerCAmelCase_  )
    if os.path.isfile(lowerCAmelCase_  ):
        SCREAMING_SNAKE_CASE__       							= [pl_ckpt_path]
    else:
        assert os.path.isdir(lowerCAmelCase_  )
        SCREAMING_SNAKE_CASE__       							= list(Path(lowerCAmelCase_  ).glob('''*.ckpt'''  )  )
        assert ckpt_files, f'''could not find any ckpt files inside the {pl_ckpt_path} directory'''

    if len(lowerCAmelCase_  ) > 1:
        logger.info(f'''averaging the weights of {ckpt_files}'''  )

    SCREAMING_SNAKE_CASE__       							= [sanitize(torch.load(lowerCAmelCase_   ,       map_location='''cpu'''  )['''state_dict''']  ) for x in ckpt_files]
    SCREAMING_SNAKE_CASE__       							= average_state_dicts(lowerCAmelCase_  )

    SCREAMING_SNAKE_CASE__							,		SCREAMING_SNAKE_CASE__       							= hf_model.load_state_dict(lowerCAmelCase_   ,       strict=lowerCAmelCase_  )
    assert not missing, f'''missing keys: {missing}'''
    hf_model.save_pretrained(lowerCAmelCase_  )
    try:
        SCREAMING_SNAKE_CASE__       							= AutoTokenizer.from_pretrained(lowerCAmelCase_  )
        tok.save_pretrained(lowerCAmelCase_  )
    except Exception:
        pass
        # dont copy tokenizer if cant


if __name__ == "__main__":
  fire.Fire(convert_pl_to_hf)
