
'''simple docstring'''




from dataclasses import dataclass, field
from typing import Optional

from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser





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







def 		lowerCAmelCase_				(   ):




    '''simple docstring'''



    A       :   str					=						HfArgumentParser((ModelArguments,)						)
    ((A			),  			)       :   Optional[Any]					=						parser.parse_args_into_dataclasses()

    # Load pretrained model and tokenizer

    # Use explicit specified encoder config
    if model_args.encoder_config_name:
        A       :   List[Any]					=						AutoConfig.from_pretrained(model_args.encoder_config_name						)
    # Use pretrained encoder model's config
    else:
        A       :   Tuple					=						AutoConfig.from_pretrained(model_args.encoder_model_name_or_path						)

    # Use explicit specified decoder config
    if model_args.decoder_config_name:
        A       :   Union[str, Any]					=						AutoConfig.from_pretrained(model_args.decoder_config_name						)
    # Use pretrained decoder model's config
    else:
        A       :   Optional[int]					=						AutoConfig.from_pretrained(model_args.decoder_model_name_or_path						)

    # necessary for `from_encoder_decoder_pretrained` when `decoder_config` is passed
    A       :   Dict					=						True
    A       :   int					=						True

    A       :   Optional[int]					=						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=a__		,				decoder_config=a__		,				)

    # GPT2 only has bos/eos tokens but not decoder_start/pad tokens
    A       :   Union[str, Any]					=						decoder_config.decoder_start_token_id
    A       :   str					=						decoder_config.pad_token_id
    if decoder_start_token_id is None:
        A       :   Any					=						decoder_config.bos_token_id
    if pad_token_id is None:
        A       :   Dict					=						decoder_config.eos_token_id

    # This is necessary to make Flax's generate() work
    A       :   List[str]					=						decoder_config.eos_token_id
    A       :   List[str]					=						decoder_start_token_id
    A       :   List[Any]					=						pad_token_id

    A       :   Any					=						AutoImageProcessor.from_pretrained(model_args.encoder_model_name_or_path						)

    A       :   List[str]					=						AutoTokenizer.from_pretrained(model_args.decoder_model_name_or_path						)
    A       :   Optional[int]					=						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'''



# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse

from ...utils.dataclasses import (
    ComputeEnvironment,
    DistributedType,
    DynamoBackend,
    PrecisionType,
    SageMakerDistributedType,
)
from ..menu import BulletMenu


UpperCAmelCase :       Any			   =     [
    'EAGER',
    'AOT_EAGER',
    'INDUCTOR',
    'NVFUSER',
    'AOT_NVFUSER',
    'AOT_CUDAGRAPHS',
    'OFI',
    'FX2TRT',
    'ONNXRT',
    'IPEX',
]







def    a__       (  a__      ,    a__=None      ,    a__=None      ,    a__=None						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      True
     while ask_again:
          __SCREAMING_SNAKE_CASE     =      input(a__						)
          try:
               if default is not None and len(a__						) == 0:
                    return default
               return convert_value(a__						) if convert_value is not None else result
          except Exception:
               if error_message is not None:
                    print(a__						)







def    a__       (  a__      ,    a__=[]      ,    a__=None      ,    a__=0						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      BulletMenu(a__      ,    a__						)
     __SCREAMING_SNAKE_CASE     =      menu.run(default_choice=a__						)
     return convert_value(a__						) if convert_value is not None else result







def    a__       (  a__						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      int(a__						)
     return ComputeEnvironment(["""LOCAL_MACHINE""", """AMAZON_SAGEMAKER"""][value]						)







def    a__       (  a__						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      int(a__						)
     return DistributedType(["""NO""", """MULTI_CPU""", """MULTI_XPU""", """MULTI_GPU""", """MULTI_NPU""", """TPU"""][value]						)







def    a__       (  a__						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      int(a__						)
     return DynamoBackend(DYNAMO_BACKENDS[value]						).value







def    a__       (  a__						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      int(a__						)
     return PrecisionType(["""no""", """fp16""", """bf16""", """fp8"""][value]						)







def    a__       (  a__						):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE     =      int(a__						)
     return SageMakerDistributedType(["""NO""", """DATA_PARALLEL""", """MODEL_PARALLEL"""][value]						)







def    a__       (  a__						):




     """simple docstring"""


     return {"yes": True, "no": False}[value.lower()]







class 						lowerCAmelCase__   (      argparse.RawDescriptionHelpFormatter					):



 """simple docstring"""



 def       UpperCAmelCase__		(		self					:       str					,							__SCREAMING_SNAKE_CASE					:       Optional[Any]					,							__SCREAMING_SNAKE_CASE					:       Dict					,							__SCREAMING_SNAKE_CASE					:       Optional[int]					,							__SCREAMING_SNAKE_CASE					:       List[Any]			)  -> Dict:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE     =      super()._format_usage(__SCREAMING_SNAKE_CASE					,							__SCREAMING_SNAKE_CASE					,							__SCREAMING_SNAKE_CASE					,							__SCREAMING_SNAKE_CASE			)
      __SCREAMING_SNAKE_CASE     =      usage.replace("""<command> [<args>] """					,							""""""			)
      return usage






