
'''simple docstring'''







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


_lowercase				:						str												= get_logger(__name__)
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				Optional[int]   ,   __SCREAMING_SNAKE_CASE      :				Tuple							):



						"""simple docstring"""





						if text.startswith(__snake_case							):
												return text[len(__snake_case							) :]
						return text  # or whatever
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				Union[str, Any]							):



						"""simple docstring"""





						return {remove_prefix(__snake_case   ,   '''model.'''							): v for k, v in sd.items()}
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				str							):



						"""simple docstring"""





						lowercase_			:  Dict									= {}
						for k in state_dicts[0].keys():
												lowercase_			:  Dict									= [sd[k] for sd in state_dicts]
												lowercase_			:  List[Any]									= sum(__snake_case							) / len(__snake_case							)
												assert isinstance(__snake_case   ,   torch.Tensor							)
												lowercase_			:  Optional[int]									= new_t
						return new_sd
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				Union[str, Any]   ,   __SCREAMING_SNAKE_CASE      :				str   ,   __SCREAMING_SNAKE_CASE      :				Optional[Any]							):



						"""simple docstring"""





						lowercase_			:  Dict									= AutoModelForSeqaSeqLM.from_pretrained(__snake_case							)
						if os.path.isfile(__snake_case							):
												lowercase_			:  Union[str, Any]									= [pl_ckpt_path]
						else:
												assert os.path.isdir(__snake_case							)
												lowercase_			:  List[Any]									= list(Path(__snake_case							).glob('''*.ckpt'''							)							)
												assert ckpt_files, F'''could not find any ckpt files inside the {pl_ckpt_path} directory'''

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

						lowercase_			:  List[Any]									= [sanitize(torch.load(__snake_case   ,   map_location='''cpu'''							)['''state_dict''']							) for x in ckpt_files]
						lowercase_			:  Any									= average_state_dicts(__snake_case							)

						lowercase_		,				lowercase_			:  Union[str, Any]									= hf_model.load_state_dict(__snake_case   ,   strict=__snake_case							)
						assert not missing, F'''missing keys: {missing}'''
						hf_model.save_pretrained(__snake_case							)
						try:
												lowercase_			:  Optional[int]									= AutoTokenizer.from_pretrained(__snake_case							)
												tok.save_pretrained(__snake_case							)
						except Exception:
												pass
												# dont copy tokenizer if cant


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





'''simple docstring'''







import math
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int							):



						"""simple docstring"""





						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5   ,   int(math.sqrt(__SCREAMING_SNAKE_CASE							) + 1							)   ,   6							):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int = 600851475143							):



						"""simple docstring"""





						try:
												lowercase_			:  List[str]									= int(__SCREAMING_SNAKE_CASE							)
						except (TypeError, ValueError):
												raise TypeError('''Parameter n must be int or castable to int.'''							)
						if n <= 0:
												raise ValueError('''Parameter n must be greater than or equal to one.'''							)
						lowercase_			:  Tuple									= 0
						if is_prime(__SCREAMING_SNAKE_CASE							):
												return n
						while n % 2 == 0:
												n //= 2
						if is_prime(__SCREAMING_SNAKE_CASE							):
												return n
						for i in range(3   ,   int(math.sqrt(__SCREAMING_SNAKE_CASE							)							) + 1   ,   2							):
												if n % i == 0:
																		if is_prime(n // i							):
																								lowercase_			:  str									= n // i
																								break
																		elif is_prime(__SCREAMING_SNAKE_CASE							):
																								lowercase_			:  Optional[Any]									= i
						return max_number


if __name__ == "__main__":
							print(f"""{solution() = }""")



