
from dataclasses import dataclass, field
from typing import Optional

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





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






def      lowerCamelCase__       (       ):




			"""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=__lowerCAmelCase					,							decoder_config=__lowerCAmelCase					,							)

			# 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()





def      lowerCamelCase__       (       __lowerCAmelCase						:						list[list[int]]					,							__lowerCAmelCase						:						int					,							__lowerCAmelCase						:						int					,							__lowerCAmelCase						:						set       ):




			"""simple docstring"""


			lowerCAmelCase_			,						lowerCAmelCase_      			=			len(__lowerCAmelCase       ), len(grid[0]       )
			if (
			    min(__lowerCAmelCase					,							__lowerCAmelCase       ) < 0
			    or row == row_length
			    or col == col_length
			    or (row, col) in visit
			    or grid[row][col] == 1
			):
						return 0
			if row == row_length - 1 and col == col_length - 1:
						return 1

			visit.add((row, col)       )

			lowerCAmelCase_      			=			0
			count += depth_first_search(__lowerCAmelCase					,							row + 1					,							__lowerCAmelCase					,							__lowerCAmelCase       )
			count += depth_first_search(__lowerCAmelCase					,							row - 1					,							__lowerCAmelCase					,							__lowerCAmelCase       )
			count += depth_first_search(__lowerCAmelCase					,							__lowerCAmelCase					,							col + 1					,							__lowerCAmelCase       )
			count += depth_first_search(__lowerCAmelCase					,							__lowerCAmelCase					,							col - 1					,							__lowerCAmelCase       )

			visit.remove((row, col)       )
			return count


if __name__ == "__main__":
			import doctest

			doctest.testmod()



