
'''simple docstring'''





from dataclasses import dataclass, field
from typing import Optional

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

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






def 		_UpperCAmelCase   (	):






	"""simple docstring"""


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

	# Load pretrained model and tokenizer

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

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

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

	__lowerCAmelCase         =							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=_snake_case			,							decoder_config=_snake_case			,							)

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

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

	__lowerCAmelCase         =							AutoImageProcessor.from_pretrained(model_args.encoder_model_name_or_path  )

	__lowerCAmelCase         =							AutoTokenizer.from_pretrained(model_args.decoder_model_name_or_path  )
	__lowerCAmelCase         =							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 pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


UpperCamelCase_   	=	pytest.mark.integration






@pytest.mark.parametrize("path"			,							["paws", "csv"]  )
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	inspect_dataset(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@pytest.mark.filterwarnings("ignore:inspect_metric is deprecated:FutureWarning"  )
@pytest.mark.filterwarnings("ignore:metric_module_factory is deprecated:FutureWarning"  )
@pytest.mark.parametrize("path"			,							["accuracy"]  )
def 		_UpperCAmelCase   (	UpperCamelCase:     List[Any]			,							UpperCamelCase:     Any  ):






	"""simple docstring"""


	inspect_metric(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@pytest.mark.parametrize(
    "path, config_name, expected_splits"			,							[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[Any]			,							UpperCamelCase:     int			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_info(UpperCamelCase			,							config_name=UpperCamelCase  )
	assert info.config_name == config_name
	assert list(info.splits.keys()  ) == expected_splits






@pytest.mark.parametrize(
    "path, config_name, expected_exception"			,							[
        ("paws", None, ValueError),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     Any			,							UpperCamelCase:     List[str]  ):






	"""simple docstring"""


	with pytest.raises(UpperCamelCase  ):
		get_dataset_config_info(UpperCamelCase			,							config_name=UpperCamelCase  )






@pytest.mark.parametrize(
    "path, expected"			,							[
        ("squad", "plain_text"),
        ("acronym_identification", "default"),
        ("lhoestq/squad", "plain_text"),
        ("lhoestq/test", "default"),
        ("lhoestq/demo1", "lhoestq--demo1"),
        ("dalle-mini/wit", "dalle-mini--wit"),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     List[str]			,							UpperCamelCase:     Optional[int]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_names(UpperCamelCase  )
	assert expected in config_names






@pytest.mark.parametrize(
    "path, expected_configs, expected_splits_in_first_config"			,							[
        ("squad", ["plain_text"], ["train", "validation"]),
        ("dalle-mini/wit", ["dalle-mini--wit"], ["train"]),
        ("paws", ["labeled_final", "labeled_swap", "unlabeled_final"], ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     str			,							UpperCamelCase:     Tuple			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert list(infos.keys()  ) == expected_configs
	__lowerCAmelCase         =							expected_configs[0]
	assert expected_config in infos
	__lowerCAmelCase         =							infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()  ) == expected_splits_in_first_config






@pytest.mark.parametrize(
    "path, expected_config, expected_splits"			,							[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     int			,							UpperCamelCase:     Optional[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert expected_config in infos
	__lowerCAmelCase         =							infos[expected_config]
	assert info.config_name == expected_config
	assert list(info.splits.keys()  ) == expected_splits







@pytest.mark.parametrize(
    "path, config_name, expected_exception"			,							[
        ("paws", None, ValueError),
    ]			,							)
def 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     List[str]			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	with pytest.raises(UpperCamelCase  ):
		get_dataset_split_names(UpperCamelCase			,							config_name=UpperCamelCase  )






