import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


__lowercase							 =					get_logger(__name__)


class 	lowerCamelCase_     (   enum.Enum ):






    '''simple docstring'''






    a__	:						Union[str, Any]						=      """all_checks"""
    a__	:						List[Any]						=      """basic_checks"""
    a__	:						List[Any]						=      """no_checks"""


class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''








class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''








class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''








class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''









def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE=None	):
    '''simple docstring'''







    if expected_checksums is None:
        logger.info('''Unable to verify checksums.'''	)
        return
    if len(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	) > 0:
        raise ExpectedMoreDownloadedFiles(str(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	)	)
    if len(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	) > 0:
        raise UnexpectedDownloadedFile(str(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	)	)
    __UpperCamelCase     :int			  =		[url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
    __UpperCamelCase     :Any			  =		''' for ''' + verification_name if verification_name is not None else ''''''
    if len(SCREAMING_SNAKE_CASE	) > 0:
        raise NonMatchingChecksumError(
            f"""Checksums didn't match{for_verification_name}:\n"""
            f"""{bad_urls}\n"""
            '''Set `verification_mode=\'no_checks\'` to skip checksums verification and ignore this error'''	)
    logger.info('''All the checksums matched successfully''' + for_verification_name	)


class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''








class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''








class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''








class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''









def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    if expected_splits is None:
        logger.info('''Unable to verify splits sizes.'''	)
        return
    if len(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	) > 0:
        raise ExpectedMoreSplits(str(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	)	)
    if len(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	) > 0:
        raise UnexpectedSplits(str(set(SCREAMING_SNAKE_CASE	) - set(SCREAMING_SNAKE_CASE	)	)	)
    __UpperCamelCase     :Union[str, Any]			  =		[
        {'''expected''': expected_splits[name], '''recorded''': recorded_splits[name]}
        for name in expected_splits
        if expected_splits[name].num_examples != recorded_splits[name].num_examples
    ]
    if len(SCREAMING_SNAKE_CASE	) > 0:
        raise NonMatchingSplitsSizesError(str(SCREAMING_SNAKE_CASE	)	)
    logger.info('''All the splits matched successfully.'''	)



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE = True	):
    '''simple docstring'''







    if record_checksum:
        __UpperCamelCase     :List[Any]			  =		shaaaa()
        with open(SCREAMING_SNAKE_CASE  ,			'''rb'''	) as f:
            for chunk in iter(lambda: f.read(1 << 20	)  ,			B''''''	):
                m.update(SCREAMING_SNAKE_CASE	)
            __UpperCamelCase     :List[Any]			  =		m.hexdigest()
    else:
        __UpperCamelCase     :Optional[int]			  =		None
    return {"num_bytes": os.path.getsize(SCREAMING_SNAKE_CASE	), "checksum": checksum}



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    if dataset_size and config.IN_MEMORY_MAX_SIZE:
        return dataset_size < config.IN_MEMORY_MAX_SIZE
    else:
        return False










"""simple docstring"""
import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


_lowerCAmelCase    :int     =					['small', 'medium', 'large']

_lowerCAmelCase    :int     =					'lm_head.decoder.weight'
_lowerCAmelCase    :Dict     =					'lm_head.weight'





def  lowerCamelCase_						(UpperCamelCase__		:		str     ,       UpperCamelCase__		:		str							):
    _UpperCAmelCase							:  List[Any]											=    torch.load(UpperCamelCase__							)
    _UpperCAmelCase							:  List[str]											=    d.pop(UpperCamelCase__							)
    os.makedirs(UpperCamelCase__     ,       exist_ok=UpperCamelCase__							)
    torch.save(UpperCamelCase__     ,       os.path.join(UpperCamelCase__     ,       UpperCamelCase__							)							)


if __name__ == "__main__":
  _lowerCAmelCase    :Dict     =					argparse.ArgumentParser()
  parser.add_argument('--dialogpt_path', default='.', type=str)
  _lowerCAmelCase    :str     =					parser.parse_args()
  for MODEL in DIALOGPT_MODELS:
    _lowerCAmelCase    :Tuple     =					os.path.join(args.dialogpt_path, f"{MODEL}_ft.pkl")
    _lowerCAmelCase    :int     =					f"./DialoGPT-{MODEL}"
    convert_dialogpt_checkpoint(
        checkpoint_path,
        pytorch_dump_folder_path,
    )


