



'''simple docstring'''


import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union

from .. import config
from .filelock import FileLock
from .logging import get_logger


_lowerCamelCase	:       Optional[int]      	=	get_logger(__name__)

class  SCREAMING_SNAKE_CASE :






    """simple docstring"""





    def __init__(  self      :					Dict  ,						UpperCamelCase__      :					List[Any] = None ):


       """simple docstring"""







       UpperCamelCase					=  (
           os.path.join(SCREAMING_SNAKE_CASE_  ,						config.EXTRACTED_DATASETS_DIR ) if cache_dir else config.EXTRACTED_DATASETS_PATH
       )
       UpperCamelCase					=  Extractor






    def  A       (  self      :					Union[str, Any]  ,						UpperCamelCase__      :					Tuple ):


       """simple docstring"""







       from .file_utils import hash_url_to_filename

       # Path where we extract compressed archives
       # We extract in the cache dir, and get the extracted path name by hashing the original path"
       UpperCamelCase					=  os.path.abspath(SCREAMING_SNAKE_CASE_ )
       return os.path.join(self.extract_dir  ,						hash_url_to_filename(SCREAMING_SNAKE_CASE_ ) )






    def  A       (  self      :					Optional[Any]  ,						UpperCamelCase__      :					Optional[int]  ,						UpperCamelCase__      :					Optional[Any] ):


       """simple docstring"""







       return force_extract or (
           not os.path.isfile(SCREAMING_SNAKE_CASE_ ) and not (os.path.isdir(SCREAMING_SNAKE_CASE_ ) and os.listdir(SCREAMING_SNAKE_CASE_ ))
       )






    def  A       (  self      :					str  ,						UpperCamelCase__      :					Dict  ,						UpperCamelCase__      :					int = False ):


       """simple docstring"""







       UpperCamelCase					=  self.extractor.infer_extractor_format(SCREAMING_SNAKE_CASE_ )
       if not extractor_format:
          return input_path
       UpperCamelCase					=  self._get_output_path(SCREAMING_SNAKE_CASE_ )
       if self._do_extract(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ ):
          self.extractor.extract(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )
       return output_path

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    @classmethod
    @abstractmethod
    def  A       (  cls      :					Optional[Any]  ,						UpperCamelCase__      :					List[str]  ,						**UpperCamelCase__      :					Any ):


       """simple docstring"""







       ...






    @staticmethod
    @abstractmethod
    def  A       (  UpperCamelCase__      :					Dict  ,						UpperCamelCase__      :					int ):


       """simple docstring"""







       ...

class  SCREAMING_SNAKE_CASE (  a__   ,						a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  []






    @staticmethod
    def  A       (  UpperCamelCase__      :					Optional[Any]  ,						UpperCamelCase__      :					List[Any] ):


       """simple docstring"""







       with open(SCREAMING_SNAKE_CASE_  ,						'rb' ) as f:
          return f.read(SCREAMING_SNAKE_CASE_ )






    @classmethod
    def  A       (  cls      :					Union[str, Any]  ,						UpperCamelCase__      :					Any  ,						UpperCamelCase__      :					Optional[Any] = b"" ):


       """simple docstring"""







       if not magic_number:
          UpperCamelCase					=  max(len(SCREAMING_SNAKE_CASE_ ) for cls_magic_number in cls.magic_numbers )
          try:
             UpperCamelCase					=  cls.read_magic_number(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )
          except OSError:
             return False
       return any(magic_number.startswith(SCREAMING_SNAKE_CASE_ ) for cls_magic_number in cls.magic_numbers )

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    @classmethod
    def  A       (  cls      :					List[Any]  ,						UpperCamelCase__      :					Optional[Any]  ,						**UpperCamelCase__      :					List[str] ):


       """simple docstring"""







       return tarfile.is_tarfile(SCREAMING_SNAKE_CASE_ )






    @staticmethod
    def  A       (  UpperCamelCase__      :					List[Any]  ,						UpperCamelCase__      :					int ):


       """simple docstring"""







       def resolved(UpperCamelCase__      :					Optional[int] ) -> str:
          return os.path.realpath(os.path.abspath(SCREAMING_SNAKE_CASE_ ) )

       def badpath(UpperCamelCase__      :					str  ,						UpperCamelCase__      :					Union[str, Any] ) -> bool:
          # joinpath will ignore base if path is absolute
          return not resolved(os.path.join(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ ) ).startswith(SCREAMING_SNAKE_CASE_ )

       def badlink(UpperCamelCase__      :					List[str]  ,						UpperCamelCase__      :					Union[str, Any] ) -> bool:
          # Links are interpreted relative to the directory containing the link
          UpperCamelCase					=  resolved(os.path.join(SCREAMING_SNAKE_CASE_  ,						os.path.dirname(info.name ) ) )
          return badpath(info.linkname  ,						base=SCREAMING_SNAKE_CASE_ )

       UpperCamelCase					=  resolved(SCREAMING_SNAKE_CASE_ )

       for finfo in members:
          if badpath(finfo.name  ,						SCREAMING_SNAKE_CASE_ ):
             logger.error(f"""Extraction of {finfo.name} is blocked (illegal path)""" )
          elif finfo.issym() and badlink(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ ):
             logger.error(f"""Extraction of {finfo.name} is blocked: Symlink to {finfo.linkname}""" )
          elif finfo.islnk() and badlink(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ ):
             logger.error(f"""Extraction of {finfo.name} is blocked: Hard link to {finfo.linkname}""" )
          else:
             yield finfo






    @staticmethod
    def  A       (  UpperCamelCase__      :					List[str]  ,						UpperCamelCase__      :					List[str] ):


       """simple docstring"""







       os.makedirs(SCREAMING_SNAKE_CASE_  ,						exist_ok=SCREAMING_SNAKE_CASE_ )
       UpperCamelCase					=  tarfile.open(SCREAMING_SNAKE_CASE_ )
       tar_file.extractall(SCREAMING_SNAKE_CASE_  ,						members=TarExtractor.safemembers(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ ) )
       tar_file.close()

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [b"\x1F\x8B"]






    @staticmethod
    def  A       (  UpperCamelCase__      :					Dict  ,						UpperCamelCase__      :					Tuple ):


       """simple docstring"""







       with gzip.open(SCREAMING_SNAKE_CASE_  ,						'rb' ) as gzip_file:
          with open(SCREAMING_SNAKE_CASE_  ,						'wb' ) as extracted_file:
             shutil.copyfileobj(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [
        b"PK\x03\x04",
        b"PK\x05\x06",  # empty archive
        b"PK\x07\x08",  # spanned archive
    ]






    @classmethod
    def  A       (  cls      :					int  ,						UpperCamelCase__      :					Any  ,						UpperCamelCase__      :					int = b"" ):


       """simple docstring"""







       if super().is_extractable(SCREAMING_SNAKE_CASE_  ,						magic_number=SCREAMING_SNAKE_CASE_ ):
          return True
       try:
          # Alternative version of zipfile.is_zipfile that has less false positives, but misses executable zip archives.
          # From: https://github.com/python/cpython/pull/5053
          from zipfile import (
              _CD_SIGNATURE,
              _ECD_DISK_NUMBER,
              _ECD_DISK_START,
              _ECD_ENTRIES_TOTAL,
              _ECD_OFFSET,
              _ECD_SIZE,
              _EndRecData,
              sizeCentralDir,
              stringCentralDir,
              structCentralDir,
          )

          with open(SCREAMING_SNAKE_CASE_  ,						'rb' ) as fp:
             UpperCamelCase					=  _EndRecData(SCREAMING_SNAKE_CASE_ )
             if endrec:
                if endrec[_ECD_ENTRIES_TOTAL] == 0 and endrec[_ECD_SIZE] == 0 and endrec[_ECD_OFFSET] == 0:
                   return True  # Empty zipfiles are still zipfiles
                elif endrec[_ECD_DISK_NUMBER] == endrec[_ECD_DISK_START]:
                   fp.seek(endrec[_ECD_OFFSET] )  # Central directory is on the same disk
                   if fp.tell() == endrec[_ECD_OFFSET] and endrec[_ECD_SIZE] >= sizeCentralDir:
                      UpperCamelCase					=  fp.read(SCREAMING_SNAKE_CASE_ )  # CD is where we expect it to be
                      if len(SCREAMING_SNAKE_CASE_ ) == sizeCentralDir:
                         UpperCamelCase					=  struct.unpack(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )  # CD is the right size
                         if centdir[_CD_SIGNATURE] == stringCentralDir:
                            return True  # First central directory entry  has correct magic number
          return False
       except Exception:  # catch all errors in case future python versions change the zipfile internals
          return False






    @staticmethod
    def  A       (  UpperCamelCase__      :					Any  ,						UpperCamelCase__      :					str ):


       """simple docstring"""







       os.makedirs(SCREAMING_SNAKE_CASE_  ,						exist_ok=SCREAMING_SNAKE_CASE_ )
       with zipfile.ZipFile(SCREAMING_SNAKE_CASE_  ,						'r' ) as zip_file:
          zip_file.extractall(SCREAMING_SNAKE_CASE_ )
          zip_file.close()

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [b"\xFD\x37\x7A\x58\x5A\x00"]






    @staticmethod
    def  A       (  UpperCamelCase__      :					List[Any]  ,						UpperCamelCase__      :					Optional[int] ):


       """simple docstring"""







       with lzma.open(SCREAMING_SNAKE_CASE_ ) as compressed_file:
          with open(SCREAMING_SNAKE_CASE_  ,						'wb' ) as extracted_file:
             shutil.copyfileobj(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [b"Rar!\x1a\x07\x00", b"Rar!\x1a\x07\x01\x00"]  # RAR_ID  # RAR5_ID






    @staticmethod
    def  A       (  UpperCamelCase__      :					int  ,						UpperCamelCase__      :					Tuple ):


       """simple docstring"""







       if not config.RARFILE_AVAILABLE:
          raise ImportError('Please pip install rarfile' )
       import rarfile

       os.makedirs(SCREAMING_SNAKE_CASE_  ,						exist_ok=SCREAMING_SNAKE_CASE_ )
       UpperCamelCase					=  rarfile.RarFile(SCREAMING_SNAKE_CASE_ )
       rf.extractall(SCREAMING_SNAKE_CASE_ )
       rf.close()

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [b"\x28\xb5\x2F\xFD"]






    @staticmethod
    def  A       (  UpperCamelCase__      :					Dict  ,						UpperCamelCase__      :					Dict ):


       """simple docstring"""







       if not config.ZSTANDARD_AVAILABLE:
          raise ImportError('Please pip install zstandard' )
       import zstandard as zstd

       UpperCamelCase					=  zstd.ZstdDecompressor()
       with open(SCREAMING_SNAKE_CASE_  ,						'rb' ) as ifh, open(SCREAMING_SNAKE_CASE_  ,						'wb' ) as ofh:
          dctx.copy_stream(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [b"\x42\x5A\x68"]






    @staticmethod
    def  A       (  UpperCamelCase__      :					str  ,						UpperCamelCase__      :					str ):


       """simple docstring"""







       with bza.open(SCREAMING_SNAKE_CASE_  ,						'rb' ) as compressed_file:
          with open(SCREAMING_SNAKE_CASE_  ,						'wb' ) as extracted_file:
             shutil.copyfileobj(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [b"\x37\x7A\xBC\xAF\x27\x1C"]






    @staticmethod
    def  A       (  UpperCamelCase__      :					Union[str, Any]  ,						UpperCamelCase__      :					str ):


       """simple docstring"""







       if not config.PY7ZR_AVAILABLE:
          raise ImportError('Please pip install py7zr' )
       import pyazr

       os.makedirs(SCREAMING_SNAKE_CASE_  ,						exist_ok=SCREAMING_SNAKE_CASE_ )
       with pyazr.SevenZipFile(SCREAMING_SNAKE_CASE_  ,						'r' ) as archive:
          archive.extractall(SCREAMING_SNAKE_CASE_ )

class  SCREAMING_SNAKE_CASE (  a__		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  [b"\x04\x22\x4D\x18"]






    @staticmethod
    def  A       (  UpperCamelCase__      :					Any  ,						UpperCamelCase__      :					List[Any] ):


       """simple docstring"""







       if not config.LZ4_AVAILABLE:
          raise ImportError('Please pip install lz4' )
       import lza.frame

       with lza.frame.open(SCREAMING_SNAKE_CASE_  ,						'rb' ) as compressed_file:
          with open(SCREAMING_SNAKE_CASE_  ,						'wb' ) as extracted_file:
             shutil.copyfileobj(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )

class  SCREAMING_SNAKE_CASE :






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  {
        "tar": TarExtractor,
        "gzip": GzipExtractor,
        "zip": ZipExtractor,
        "xz": XzExtractor,
        "rar": RarExtractor,
        "zstd": ZstdExtractor,
        "bz2": BzipaExtractor,
        "7z": SevenZipExtractor,  # <Added version="2.4.0"/>
        "lz4": LzaExtractor,  # <Added version="2.4.0"/>
    }






    @classmethod
    def  A       (  cls      :					Optional[int] ):


       """simple docstring"""







       return max(
           len(SCREAMING_SNAKE_CASE_ )
           for extractor in cls.extractors.values()
           if issubclass(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )
           for extractor_magic_number in extractor.magic_numbers )






    @staticmethod
    def  A       (  UpperCamelCase__      :					Tuple  ,						UpperCamelCase__      :					int ):


       """simple docstring"""







       try:
          return MagicNumberBaseExtractor.read_magic_number(SCREAMING_SNAKE_CASE_  ,						magic_number_length=SCREAMING_SNAKE_CASE_ )
       except OSError:
          return b""






    @classmethod
    def  A       (  cls      :					Dict  ,						UpperCamelCase__      :					Tuple  ,						UpperCamelCase__      :					Tuple = False ):


       """simple docstring"""







       warnings.warn(
           'Method \'is_extractable\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '
           'Use \'infer_extractor_format\' instead.'  ,						category=SCREAMING_SNAKE_CASE_  ,						)
       UpperCamelCase					=  cls.infer_extractor_format(SCREAMING_SNAKE_CASE_ )
       if extractor_format:
          return True if not return_extractor else (True, cls.extractors[extractor_format])
       return False if not return_extractor else (False, None)






    @classmethod
    def  A       (  cls      :					List[Any]  ,						UpperCamelCase__      :					Any ):  # <Added version="2.4.0"/>


       """simple docstring"""







       UpperCamelCase					=  cls._get_magic_number_max_length()
       UpperCamelCase					=  cls._read_magic_number(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )
       for extractor_format, extractor in cls.extractors.items():
          if extractor.is_extractable(SCREAMING_SNAKE_CASE_  ,						magic_number=SCREAMING_SNAKE_CASE_ ):
             return extractor_format






    @classmethod
    def  A       (  cls      :					List[str]  ,						UpperCamelCase__      :					Union[str, Any]  ,						UpperCamelCase__      :					List[Any]  ,						UpperCamelCase__      :					Optional[int] = None  ,						UpperCamelCase__      :					Optional[int] = "deprecated"  ,						):


       """simple docstring"""







       os.makedirs(os.path.dirname(SCREAMING_SNAKE_CASE_ )  ,						exist_ok=SCREAMING_SNAKE_CASE_ )
       # Prevent parallel extractions
       UpperCamelCase					=  str(Path(SCREAMING_SNAKE_CASE_ ).with_suffix('.lock' ) )
       with FileLock(SCREAMING_SNAKE_CASE_ ):
          shutil.rmtree(SCREAMING_SNAKE_CASE_  ,						ignore_errors=SCREAMING_SNAKE_CASE_ )
          if extractor_format or extractor != "deprecated":
             if extractor != "deprecated" or not isinstance(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ ):  # passed as positional arg
                warnings.warn(
                    'Parameter \'extractor\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '
                    'Use \'extractor_format\' instead.'  ,						category=SCREAMING_SNAKE_CASE_  ,						)
                UpperCamelCase					=  extractor if extractor != 'deprecated' else extractor_format
             else:
                UpperCamelCase					=  cls.extractors[extractor_format]
             return extractor.extract(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )
          else:
             warnings.warn(
                 'Parameter \'extractor_format\' was made required in version 2.4.0 and not passing it will raise an '
                 'exception in 3.0.0.'  ,						category=SCREAMING_SNAKE_CASE_  ,						)
             for extractor in cls.extractors.values():
                if extractor.is_extractable(SCREAMING_SNAKE_CASE_ ):
                   return extractor.extract(SCREAMING_SNAKE_CASE_  ,						SCREAMING_SNAKE_CASE_ )






import argparse
import os
from pathlib import Path

import fairseq
import torch
from packaging import version
from torch import nn

from transformers import (
    BartConfig,
    BartForConditionalGeneration,
    BartForSequenceClassification,
    BartModel,
    BartTokenizer,
)
from transformers.utils import logging


__UpperCAmelCase          =       ['''bart.large''', '''bart.large.mnli''', '''bart.large.cnn''', '''bart_xsum/model.pt''']
__UpperCAmelCase          =       {'''bart.large''': BartModel, '''bart.large.mnli''': BartForSequenceClassification}
if version.parse(fairseq.__version__) < version.parse('''0.9.0'''):
    raise Exception('''requires fairseq >= 0.9.0''')


logging.set_verbosity_info()
__UpperCAmelCase          =       logging.get_logger(__name__)

__UpperCAmelCase          =       ''' Hello world! cécé herlolip'''

__UpperCAmelCase          =       [
    ('''model.classification_heads.mnli.dense.weight''', '''classification_head.dense.weight'''),
    ('''model.classification_heads.mnli.dense.bias''', '''classification_head.dense.bias'''),
    ('''model.classification_heads.mnli.out_proj.weight''', '''classification_head.out_proj.weight'''),
    ('''model.classification_heads.mnli.out_proj.bias''', '''classification_head.out_proj.bias'''),
]
def 		UpperCamelCase	(   snake_case__       :    Union[str, Any]	)	->     List[str]:
   UpperCamelCase    :  int							=	[
       'encoder.version',
       'decoder.version',
       'model.encoder.version',
       'model.decoder.version',
       '_float_tensor',
   ]
   for k in ignore_keys:
      state_dict.pop(snake_case__       ,     snake_case__	)
def 		UpperCamelCase	(   snake_case__       :    int       ,     snake_case__       :    List[str]       ,     snake_case__       :    int	)	->     Any:
   UpperCamelCase    :  Dict							=	dct.pop(snake_case__	)
   UpperCamelCase    :  Optional[Any]							=	val
def 		UpperCamelCase	(   snake_case__       :    Dict	)	->     Tuple:
   UpperCamelCase    :  int							=	torch.load(snake_case__       ,     map_location='cpu'	)
   UpperCamelCase    :  Dict							=	torch.hub.load('pytorch/fairseq'       ,     'bart.large.cnn'	).eval()
   hub_interface.model.load_state_dict(sd['model']	)
   return hub_interface
def 		UpperCamelCase	(   snake_case__       :    List[str]	)	->     Dict:
   UpperCamelCase	,     UpperCamelCase    :  str							=	emb.weight.shape
   UpperCamelCase    :  Optional[int]							=	nn.Linear(snake_case__       ,     snake_case__       ,     bias=snake_case__	)
   UpperCamelCase    :  List[str]							=	emb.weight.data
   return lin_layer
@torch.no_grad()
def 		UpperCamelCase	(   snake_case__       :    Optional[int]       ,     snake_case__       :    Optional[int]       ,     snake_case__       :    str=None	)	->     Optional[Any]:
   if not os.path.exists(snake_case__	):
      UpperCamelCase    :  List[str]							=	torch.hub.load('pytorch/fairseq'       ,     snake_case__	).eval()
   else:
      UpperCamelCase    :  int							=	load_xsum_checkpoint(snake_case__	)

   bart.model.upgrade_state_dict(bart.model.state_dict()	)
   if hf_checkpoint_name is None:
      UpperCamelCase    :  Tuple							=	checkpoint_path.replace('.'       ,     '-'	)
   UpperCamelCase    :  Optional[int]							=	BartConfig.from_pretrained(snake_case__	)
   UpperCamelCase    :  Optional[Any]							=	bart.encode(snake_case__	).unsqueeze(0	)
   UpperCamelCase    :  Any							=	BartTokenizer.from_pretrained(snake_case__	).encode(snake_case__       ,     return_tensors='pt'	).unsqueeze(0	)
   if not torch.eq(snake_case__       ,     snake_case__	).all():
      raise ValueError(
          F"""converted tokenizer and pretrained tokenizer returned different output: {tokens} != {tokensa}"""	)

   if checkpoint_path == "bart.large.mnli":
      UpperCamelCase    :  Union[str, Any]							=	bart.state_dict()
      remove_ignore_keys_(snake_case__	)
      UpperCamelCase    :  int							=	state_dict['model.decoder.embed_tokens.weight']
      for src, dest in mnli_rename_keys:
         rename_key(snake_case__       ,     snake_case__       ,     snake_case__	)
      UpperCamelCase    :  Any							=	BartForSequenceClassification(snake_case__	).eval()
      model.load_state_dict(snake_case__	)
      UpperCamelCase    :  Any							=	bart.predict('mnli'       ,     snake_case__       ,     return_logits=snake_case__	)
      UpperCamelCase    :  Tuple							=	model(snake_case__	)[0]  # logits
   else:  # no classification heads to worry about
      UpperCamelCase    :  List[str]							=	bart.model.state_dict()
      remove_ignore_keys_(snake_case__	)
      UpperCamelCase    :  List[str]							=	state_dict['decoder.embed_tokens.weight']
      UpperCamelCase    :  Union[str, Any]							=	bart.extract_features(snake_case__	)
      if hf_checkpoint_name == "facebook/bart-large":
         UpperCamelCase    :  List[str]							=	BartModel(snake_case__	).eval()
         model.load_state_dict(snake_case__	)
         UpperCamelCase    :  Optional[int]							=	model(snake_case__	).model[0]
      else:
         UpperCamelCase    :  Union[str, Any]							=	BartForConditionalGeneration(snake_case__	).eval()  # an existing summarization ckpt
         model.model.load_state_dict(snake_case__	)
         if hasattr(snake_case__       ,     'lm_head'	):
            UpperCamelCase    :  Optional[int]							=	make_linear_from_emb(model.model.shared	)
         UpperCamelCase    :  Dict							=	model.model(snake_case__	)[0]

    # Check results
   if fairseq_output.shape != new_model_outputs.shape:
      raise ValueError(
          F"""`fairseq_output` shape and `new_model_output` shape are different: {fairseq_output.shape=}, {new_model_outputs.shape}"""	)
   if (fairseq_output != new_model_outputs).any().item():
      raise ValueError('Some values in `fairseq_output` are different from `new_model_outputs`'	)
   Path(snake_case__	).mkdir(exist_ok=snake_case__	)
   model.save_pretrained(snake_case__	)


if __name__ == "__main__":
    __UpperCAmelCase          =       argparse.ArgumentParser()
    # Required parameters
    parser.add_argument(
        '''fairseq_path''', type=str, help='''bart.large, bart.large.cnn or a path to a model.pt on local filesystem.'''
    )
    parser.add_argument('''pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model.''')
    parser.add_argument(
        '''--hf_config''', default=None, type=str, help='''Which huggingface architecture to use: bart-large-xsum'''
    )
    __UpperCAmelCase          =       parser.parse_args()
    convert_bart_checkpoint(args.fairseq_path, args.pytorch_dump_folder_path, hf_checkpoint_name=args.hf_config)



