import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def 							lowerCAmelCase(     __lowerCamelCase				,    __lowerCamelCase				,    __lowerCamelCase				,    __lowerCamelCase				,    __lowerCamelCase = None				,    __lowerCamelCase = None				,    __lowerCamelCase = None				,    ):
					if config_name_or_path is None:
										__a		 =       'facebook/rag-token-base' if model_type == 'rag_token' else 'facebook/rag-sequence-base'

					if generator_tokenizer_name_or_path is None:
										__a		 =       generator_name_or_path

					if question_encoder_tokenizer_name_or_path is None:
										__a		 =       question_encoder_name_or_path

					__a		 =       RagTokenForGeneration if model_type == 'rag_token' else RagSequenceForGeneration

					# Save model.
					__a		 =       RagConfig.from_pretrained(__lowerCamelCase						)
					__a		 =       AutoConfig.from_pretrained(__lowerCamelCase						)
					__a		 =       AutoConfig.from_pretrained(__lowerCamelCase						)

					__a		 =       gen_config
					__a		 =       question_encoder_config

					__a		 =       model_class.from_pretrained_question_encoder_generator(
					    __lowerCamelCase				,    __lowerCamelCase				,    config=__lowerCamelCase						)
					rag_model.save_pretrained(__lowerCamelCase						)

					# Sanity check.
					model_class.from_pretrained(__lowerCamelCase						)

					# Save tokenizers.
					__a		 =       AutoTokenizer.from_pretrained(__lowerCamelCase						)
					gen_tokenizer.save_pretrained(dest_dir / 'generator_tokenizer/'						)
					__a		 =       AutoTokenizer.from_pretrained(__lowerCamelCase						)
					question_encoder_tokenizer.save_pretrained(dest_dir / 'question_encoder_tokenizer/'						)


if __name__ == "__main__":
	lowerCamelCase_    :		List[Any]							=	argparse.ArgumentParser()
	parser.add_argument(
	    """--model_type""",
	    choices=["""rag_sequence""", """rag_token"""],
	    required=True,
	    type=str,
	    help="""RAG model type: rag_sequence, rag_token""",
	)
	parser.add_argument("""--dest""", type=str, required=True, help="""Path to the output checkpoint directory.""")
	parser.add_argument("""--generator_name_or_path""", type=str, required=True, help="""Generator model identifier""")
	parser.add_argument(
	    """--question_encoder_name_or_path""", type=str, required=True, help="""Question encoder model identifier"""
	)

	parser.add_argument(
	    """--generator_tokenizer_name_or_path""",
	    type=str,
	    help="""Generator tokenizer identifier, if not specified, resolves to ``generator_name_or_path``""",
	)
	parser.add_argument(
	    """--question_encoder_tokenizer_name_or_path""",
	    type=str,
	    help="""Question encoder tokenizer identifier, if not specified, resolves to ``question_encoder_name_or_path``""",
	)
	parser.add_argument(
	    """--config_name_or_path""",
	    type=str,
	    help=(
	        """Identifier of the model config to use, if not provided, resolves to a base config for a given"""
	        """ ``model_type``"""
	    ),
	)

	lowerCamelCase_    :		Optional[Any]							=	parser.parse_args()

	lowerCamelCase_    :		List[Any]							=	Path(args.dest)
	dest_dir.mkdir(exist_ok=True)

	consolidate(
	    args.model_type,
	    args.generator_name_or_path,
	    args.question_encoder_name_or_path,
	    dest_dir,
	    args.config_name_or_path,
	    args.generator_tokenizer_name_or_path,
	    args.question_encoder_tokenizer_name_or_path,
	)





from collections import defaultdict
def 							lowerCAmelCase(     __lowerCamelCase				,    __lowerCamelCase						):
					__a		 =       first_str.lower().strip()
					__a		 =       second_str.lower().strip()

					# Remove whitespace
					__a		 =       first_str.replace(' '				,    ''						)
					__a		 =       second_str.replace(' '				,    ''						)

					# Strings of different lengths are not anagrams
					if len(__lowerCamelCase						) != len(__lowerCamelCase						):
										return False

					# Default values for count should be 0
					__a		 =       defaultdict(__lowerCamelCase						)

					# For each character in input strings,
					# increment count in the corresponding
					for i in range(len(__lowerCamelCase						)						):
										count[first_str[i]] += 1
										count[second_str[i]] -= 1

					return all(_count == 0 for _count in count.values()						)


if __name__ == "__main__":
	from doctest import testmod

	testmod()
	lowerCamelCase_    :		List[str]							=	input("""Enter the first string """).strip()
	lowerCamelCase_    :		Optional[Any]							=	input("""Enter the second string """).strip()

	lowerCamelCase_    :		str							=	check_anagrams(input_a, input_b)
	print(F'''{input_a} and {input_b} are {'' if status else 'not '}anagrams.''')




