





import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration

def     snake_case							(UpperCamelCase			:     Union[str, Any]			,    UpperCamelCase			:     Optional[Any]			,    UpperCamelCase			:     Union[str, Any]			,    UpperCamelCase			:     Any			,    UpperCamelCase			:     Any = None			,    UpperCamelCase			:     Dict = None			,    UpperCamelCase			:     int = None			,    ):




	'''simple docstring'''







	if config_name_or_path is None:
		lowerCamelCase__										=			"""facebook/rag-token-base""" if model_type == """rag_token""" else """facebook/rag-sequence-base"""

	if generator_tokenizer_name_or_path is None:
		lowerCamelCase__										=			generator_name_or_path

	if question_encoder_tokenizer_name_or_path is None:
		lowerCamelCase__										=			question_encoder_name_or_path

	lowerCamelCase__										=			RagTokenForGeneration if model_type == """rag_token""" else RagSequenceForGeneration

	# Save model.
	lowerCamelCase__										=			RagConfig.from_pretrained(UpperCamelCase							)
	lowerCamelCase__										=			AutoConfig.from_pretrained(UpperCamelCase							)
	lowerCamelCase__										=			AutoConfig.from_pretrained(UpperCamelCase							)

	lowerCamelCase__										=			gen_config
	lowerCamelCase__										=			question_encoder_config

	lowerCamelCase__										=			model_class.from_pretrained_question_encoder_generator(
	    UpperCamelCase			,    UpperCamelCase			,    config=UpperCamelCase							)
	rag_model.save_pretrained(UpperCamelCase							)

	# Sanity check.
	model_class.from_pretrained(UpperCamelCase							)

	# Save tokenizers.
	lowerCamelCase__										=			AutoTokenizer.from_pretrained(UpperCamelCase							)
	gen_tokenizer.save_pretrained(dest_dir / """generator_tokenizer/"""							)
	lowerCamelCase__										=			AutoTokenizer.from_pretrained(UpperCamelCase							)
	question_encoder_tokenizer.save_pretrained(dest_dir / """question_encoder_tokenizer/"""							)


if __name__ == "__main__":
					a__    :		Tuple      						=     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``"""
					    ),
					)

					a__    :		List[str]      						=     parser.parse_args()

					a__    :		Optional[int]      						=     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,
					)






'''simple docstring'''


def 						lowerCamelCase__   (				a							):
						__snake_case						 =   int(a							)
						if n_element < 1:
												__snake_case						 =   ValueError('a should be a positive number'							)
												raise my_error

						__snake_case						 =   [1]
						__snake_case ,       __snake_case ,       __snake_case						 =   (0, 0, 0)
						__snake_case						 =   1
						while index < n_element:
												while hamming_list[i] * 2 <= hamming_list[-1]:
																		i += 1
												while hamming_list[j] * 3 <= hamming_list[-1]:
																		j += 1
												while hamming_list[k] * 5 <= hamming_list[-1]:
																		k += 1
												hamming_list.append(
												    min(hamming_list[i] * 2    ,	hamming_list[j] * 3    ,	hamming_list[k] * 5							)							)
												index += 1
						return hamming_list


if __name__ == "__main__":
	_lowercase  =			input("""Enter the last number (nth term) of the Hamming Number Series: """)
	print("""Formula of Hamming Number Series => 2^i * 3^j * 5^k""")
	_lowercase  =			hamming(int(n))
	print("""-----------------------------------------------------""")
	print(f'''The list with nth numbers is: {hamming_numbers}''')
	print("""-----------------------------------------------------""")

