


'''simple docstring'''





from dataclasses import dataclass, field
from typing import Optional

from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class 						a__					:





			'''simple docstring'''

			A						:				str					      =			field(
			    metadata={'''help''': '''The output directory where the model will be written.'''}      ,  )
			A						:				str					      =			field(
			    metadata={
			        '''help''': (
			            '''The encoder model checkpoint for weights initialization.'''
			            '''Don\'t set if you want to train an encoder model from scratch.'''
			        )
			    }      ,  )
			A						:				str					      =			field(
			    metadata={
			        '''help''': (
			            '''The decoder model checkpoint for weights initialization.'''
			            '''Don\'t set if you want to train a decoder model from scratch.'''
			        )
			    }      ,  )
			A						:				Optional[str]					      =			field(
			    default=a_      ,  metadata={'''help''': '''Pretrained encoder config name or path if not the same as encoder_model_name'''}   )
			A						:				Optional[str]					      =			field(
			    default=a_      ,  metadata={'''help''': '''Pretrained decoder config name or path if not the same as decoder_model_name'''}   )






def 						UpperCAmelCase__(				):






			"""simple docstring"""




			__A=	HfArgumentParser((ModelArguments,) )
			((__A),	)=	parser.parse_args_into_dataclasses()

			# Load pretrained model and tokenizer

			# Use explicit specified encoder config
			if model_args.encoder_config_name:
						__A=	AutoConfig.from_pretrained(model_args.encoder_config_name )
			# Use pretrained encoder model's config
			else:
						__A=	AutoConfig.from_pretrained(model_args.encoder_model_name_or_path )

			# Use explicit specified decoder config
			if model_args.decoder_config_name:
						__A=	AutoConfig.from_pretrained(model_args.decoder_config_name )
			# Use pretrained decoder model's config
			else:
						__A=	AutoConfig.from_pretrained(model_args.decoder_model_name_or_path )

			# necessary for `from_encoder_decoder_pretrained` when `decoder_config` is passed
			__A=	True
			__A=	True

			__A=	FlaxVisionEncoderDecoderModel.from_encoder_decoder_pretrained(
			    encoder_pretrained_model_name_or_path=model_args.encoder_model_name_or_path,decoder_pretrained_model_name_or_path=model_args.decoder_model_name_or_path,encoder_config=_SCREAMING_SNAKE_CASE,decoder_config=_SCREAMING_SNAKE_CASE,)

			# GPT2 only has bos/eos tokens but not decoder_start/pad tokens
			__A=	decoder_config.decoder_start_token_id
			__A=	decoder_config.pad_token_id
			if decoder_start_token_id is None:
						__A=	decoder_config.bos_token_id
			if pad_token_id is None:
						__A=	decoder_config.eos_token_id

			# This is necessary to make Flax's generate() work
			__A=	decoder_config.eos_token_id
			__A=	decoder_start_token_id
			__A=	pad_token_id

			__A=	AutoImageProcessor.from_pretrained(model_args.encoder_model_name_or_path )

			__A=	AutoTokenizer.from_pretrained(model_args.decoder_model_name_or_path )
			__A=	tokenizer.convert_ids_to_tokens(model.config.pad_token_id )

			model.save_pretrained(model_args.output_dir )
			image_processor.save_pretrained(model_args.output_dir )
			tokenizer.save_pretrained(model_args.output_dir )


if __name__ == "__main__":
					main()







'''simple docstring'''





import re

from filelock import FileLock


try:
					import nltk

					UpperCAmelCase__  			=				True
except (ImportError, ModuleNotFoundError):
					UpperCAmelCase__  			=				False

if NLTK_AVAILABLE:
					with FileLock('''.lock''') as lock:
										nltk.download('''punkt''', quiet=True)






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: str ):






			"""simple docstring"""




			re.sub('<n>','',_SCREAMING_SNAKE_CASE )  # remove pegasus newline char
			assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
			return "\n".join(nltk.sent_tokenize(_SCREAMING_SNAKE_CASE ) )



