from dataclasses import dataclass, field
from typing import Optional

from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class    A_ :
  _SCREAMING_SNAKE_CASE    				=			field(
      metadata={"""help""": """The output directory where the model will be written."""}			,       )
  _SCREAMING_SNAKE_CASE    				=			field(
      metadata={
          """help""": (
              """The encoder model checkpoint for weights initialization."""
              """Don\'t set if you want to train an encoder model from scratch."""
          )
      }			,       )
  _SCREAMING_SNAKE_CASE    				=			field(
      metadata={
          """help""": (
              """The decoder model checkpoint for weights initialization."""
              """Don\'t set if you want to train a decoder model from scratch."""
          )
      }			,       )
  _SCREAMING_SNAKE_CASE    				=			field(
      default=a_			,       metadata={"""help""": """Pretrained encoder config name or path if not the same as encoder_model_name"""}			)
  _SCREAMING_SNAKE_CASE    				=			field(
      default=a_			,       metadata={"""help""": """Pretrained decoder config name or path if not the same as decoder_model_name"""}			)



def   __A		(			):



 """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=__lowerCAmelCase							,				decoder_config=__lowerCAmelCase							,				)

 # 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()



import os
import sys
from contextlib import contextmanager


# Windows only
if os.name == "nt":
  import ctypes
  import msvcrt  # noqa
  class    A_ (       ctypes.Structure ):
    # _fields is a specific attr expected by ctypes
    _SCREAMING_SNAKE_CASE    				=			[("""size""", ctypes.c_int), ("""visible""", ctypes.c_byte)]



def   __A		(			):



 """simple docstring"""


 if os.name == "nt":
  __a       =  CursorInfo()
  __a       =  ctypes.windll.kernelaa.GetStdHandle(-11					)
  ctypes.windll.kernelaa.GetConsoleCursorInfo(_A							,				ctypes.byref(_A					)					)
  __a       =  False
  ctypes.windll.kernelaa.SetConsoleCursorInfo(_A							,				ctypes.byref(_A					)					)
 elif os.name == "posix":
  sys.stdout.write("\033[?25l"					)
  sys.stdout.flush()



def   __A		(			):



 """simple docstring"""


 if os.name == "nt":
  __a       =  CursorInfo()
  __a       =  ctypes.windll.kernelaa.GetStdHandle(-11					)
  ctypes.windll.kernelaa.GetConsoleCursorInfo(_A							,				ctypes.byref(_A					)					)
  __a       =  True
  ctypes.windll.kernelaa.SetConsoleCursorInfo(_A							,				ctypes.byref(_A					)					)
 elif os.name == "posix":
  sys.stdout.write("\033[?25h"					)
  sys.stdout.flush()






@contextmanager
def   __A		(			):



 """simple docstring"""


 try:
  hide_cursor()
  yield
 finally:
  show_cursor()


