




import os
import sys
import unittest


lowerCAmelCase__	   = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import get_test_info  # noqa: E402
from get_test_info import (  # noqa: E402
    get_model_to_test_mapping,
    get_model_to_tester_mapping,
    get_test_to_tester_mapping,
)


lowerCAmelCase__	   = os.path.join("""tests""", """models""", """bert""", """test_modeling_bert.py""")
lowerCAmelCase__	   = os.path.join("""tests""", """models""", """blip""", """test_modeling_blip.py""")

class 					a__						(					unittest.TestCase			):
			"""simple docstring"""







			def      UpperCamelCase		(    self       )  ->						int:
							'''simple docstring'''






							A__        =			get_test_to_tester_mapping(lowercase       )
							A__        =			get_test_to_tester_mapping(lowercase       )

							A__        =			{"""BertModelTest""": """BertModelTester"""}

							A__        =			{
							    """BlipModelTest""": """BlipModelTester""",
							    """BlipTextImageModelTest""": """BlipTextImageModelsModelTester""",
							    """BlipTextModelTest""": """BlipTextModelTester""",
							    """BlipTextRetrievalModelTest""": """BlipTextRetrievalModelTester""",
							    """BlipVQAModelTest""": """BlipVQAModelTester""",
							    """BlipVisionModelTest""": """BlipVisionModelTester""",
							}

							self.assertEqual(get_test_info.to_json(lowercase       )      ,      lowercase       )
							self.assertEqual(get_test_info.to_json(lowercase       )      ,      lowercase       )


			def      UpperCamelCase		(    self       )  ->						Any:
							'''simple docstring'''






							A__        =			get_model_to_test_mapping(lowercase       )
							A__        =			get_model_to_test_mapping(lowercase       )

							A__        =			{
							    """BertForMaskedLM""": ["""BertModelTest"""],
							    """BertForMultipleChoice""": ["""BertModelTest"""],
							    """BertForNextSentencePrediction""": ["""BertModelTest"""],
							    """BertForPreTraining""": ["""BertModelTest"""],
							    """BertForQuestionAnswering""": ["""BertModelTest"""],
							    """BertForSequenceClassification""": ["""BertModelTest"""],
							    """BertForTokenClassification""": ["""BertModelTest"""],
							    """BertLMHeadModel""": ["""BertModelTest"""],
							    """BertModel""": ["""BertModelTest"""],
							}

							A__        =			{
							    """BlipForConditionalGeneration""": ["""BlipTextImageModelTest"""],
							    """BlipForImageTextRetrieval""": ["""BlipTextRetrievalModelTest"""],
							    """BlipForQuestionAnswering""": ["""BlipVQAModelTest"""],
							    """BlipModel""": ["""BlipModelTest"""],
							    """BlipTextModel""": ["""BlipTextModelTest"""],
							    """BlipVisionModel""": ["""BlipVisionModelTest"""],
							}

							self.assertEqual(get_test_info.to_json(lowercase       )      ,      lowercase       )
							self.assertEqual(get_test_info.to_json(lowercase       )      ,      lowercase       )


			def      UpperCamelCase		(    self       )  ->						Dict:
							'''simple docstring'''






							A__        =			get_model_to_tester_mapping(lowercase       )
							A__        =			get_model_to_tester_mapping(lowercase       )

							A__        =			{
							    """BertForMaskedLM""": ["""BertModelTester"""],
							    """BertForMultipleChoice""": ["""BertModelTester"""],
							    """BertForNextSentencePrediction""": ["""BertModelTester"""],
							    """BertForPreTraining""": ["""BertModelTester"""],
							    """BertForQuestionAnswering""": ["""BertModelTester"""],
							    """BertForSequenceClassification""": ["""BertModelTester"""],
							    """BertForTokenClassification""": ["""BertModelTester"""],
							    """BertLMHeadModel""": ["""BertModelTester"""],
							    """BertModel""": ["""BertModelTester"""],
							}

							A__        =			{
							    """BlipForConditionalGeneration""": ["""BlipTextImageModelsModelTester"""],
							    """BlipForImageTextRetrieval""": ["""BlipTextRetrievalModelTester"""],
							    """BlipForQuestionAnswering""": ["""BlipVQAModelTester"""],
							    """BlipModel""": ["""BlipModelTester"""],
							    """BlipTextModel""": ["""BlipTextModelTester"""],
							    """BlipVisionModel""": ["""BlipVisionModelTester"""],
							}

							self.assertEqual(get_test_info.to_json(lowercase       )      ,      lowercase       )
							self.assertEqual(get_test_info.to_json(lowercase       )      ,      lowercase       )




from dataclasses import dataclass, field
from typing import Optional

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

@dataclass
class 					a__						:
			"""simple docstring"""







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



def 					lowerCAmelCase__							(	)			->      List[Any]:




				'''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()

