




'''simple docstring'''


import argparse
from pathlib import Path

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

						if generator_tokenizer_name_or_path is None:
												__snake_case						 =   generator_name_or_path

						if question_encoder_tokenizer_name_or_path is None:
												__snake_case						 =   question_encoder_name_or_path

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

						# Save model.
						__snake_case						 =   RagConfig.from_pretrained(a							)
						__snake_case						 =   AutoConfig.from_pretrained(a							)
						__snake_case						 =   AutoConfig.from_pretrained(a							)

						__snake_case						 =   gen_config
						__snake_case						 =   question_encoder_config

						__snake_case						 =   model_class.from_pretrained_question_encoder_generator(
						    a    ,	a    ,	config=a							)
						rag_model.save_pretrained(a							)

						# Sanity check.
						model_class.from_pretrained(a							)

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


if __name__ == "__main__":
	_lowercase  =			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``"""
	    ),
	)

	_lowercase  =			parser.parse_args()

	_lowercase  =			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						 =   [0] * len(a							)
						__snake_case						 =   []
						__snake_case						 =   []
						__snake_case						 =   0

						for values in graph.values():
												for i in values:
																		indegree[i] += 1

						for i in range(len(a							)							):
												if indegree[i] == 0:
																		queue.append(a							)

						while queue:
												__snake_case						 =   queue.pop(0							)
												cnt += 1
												topo.append(a							)
												for x in graph[vertex]:
																		indegree[x] -= 1
																		if indegree[x] == 0:
																								queue.append(a							)

						if cnt != len(a							):
												print('Cycle exists'							)
						else:
												print(a							)


# Adjacency List of Graph
_lowercase  =			{0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}






topological_sort(graph)

