import argparse
from pathlib import Path

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





def 		__lowerCamelCase							(UpperCAmelCase__       :							str ,	UpperCAmelCase__       :							str ,	UpperCAmelCase__       :							str ,	UpperCAmelCase__       :							Path ,	UpperCAmelCase__       :							str = None ,	UpperCAmelCase__       :							str = None ,	UpperCAmelCase__       :							str = None ,	) ->    List[Any]:
					if config_name_or_path is None:
										SCREAMING_SNAKE_CASE           =    "facebook/rag-token-base" if model_type == "rag_token" else "facebook/rag-sequence-base"

					if generator_tokenizer_name_or_path is None:
										SCREAMING_SNAKE_CASE           =    generator_name_or_path

					if question_encoder_tokenizer_name_or_path is None:
										SCREAMING_SNAKE_CASE           =    question_encoder_name_or_path

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

					# Save model.
					SCREAMING_SNAKE_CASE           =    RagConfig.from_pretrained(_UpperCamelCase					)
					SCREAMING_SNAKE_CASE           =    AutoConfig.from_pretrained(_UpperCamelCase					)
					SCREAMING_SNAKE_CASE           =    AutoConfig.from_pretrained(_UpperCamelCase					)

					SCREAMING_SNAKE_CASE           =    gen_config
					SCREAMING_SNAKE_CASE           =    question_encoder_config

					SCREAMING_SNAKE_CASE           =    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.
					SCREAMING_SNAKE_CASE           =    AutoTokenizer.from_pretrained(_UpperCamelCase					)
					gen_tokenizer.save_pretrained(dest_dir / "generator_tokenizer/"					)
					SCREAMING_SNAKE_CASE           =    AutoTokenizer.from_pretrained(_UpperCamelCase					)
					question_encoder_tokenizer.save_pretrained(dest_dir / "question_encoder_tokenizer/"					)


if __name__ == "__main__":
							_lowerCamelCase   :				str     			=						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[int]     			=						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,
							)





# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

_lowerCamelCase   :				Union[str, Any]     			=						TypeVar('''T''')


class   lowercase      (       Generic[T]       ):




							def __init__(  self				:   int		,							_UpperCamelCase				:   bool = True )   ->			None:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =    {}  # dictionary of lists
												SCREAMING_SNAKE_CASE           =    directed




							def 		__snake_case(  self				:   int		,							_UpperCamelCase				:   T		,							_UpperCamelCase				:   T )   ->			GraphAdjacencyList[T]:



												'''simple docstring'''

												if not self.directed:  # For undirected graphs
																	# if both source vertex and destination vertex are both present in the
																	# adjacency list, add destination vertex to source vertex list of adjacent
																	# vertices and add source vertex to destination vertex list of adjacent
																	# vertices.
																	if source_vertex in self.adj_list and destination_vertex in self.adj_list:
																						self.adj_list[source_vertex].append(_UpperCamelCase )
																						self.adj_list[destination_vertex].append(_UpperCamelCase )
																	# if only source vertex is present in adjacency list, add destination vertex
																	# to source vertex list of adjacent vertices, then create a new vertex with
																	# destination vertex as key and assign a list containing the source vertex
																	# as it's first adjacent vertex.
																	elif source_vertex in self.adj_list:
																						self.adj_list[source_vertex].append(_UpperCamelCase )
																						SCREAMING_SNAKE_CASE           =    [source_vertex]
																	# if only destination vertex is present in adjacency list, add source vertex
																	# to destination vertex list of adjacent vertices, then create a new vertex
																	# with source vertex as key and assign a list containing the source vertex
																	# as it's first adjacent vertex.
																	elif destination_vertex in self.adj_list:
																						self.adj_list[destination_vertex].append(_UpperCamelCase )
																						SCREAMING_SNAKE_CASE           =    [destination_vertex]
																	# if both source vertex and destination vertex are not present in adjacency
																	# list, create a new vertex with source vertex as key and assign a list
																	# containing the destination vertex as it's first adjacent vertex also
																	# create a new vertex with destination vertex as key and assign a list
																	# containing the source vertex as it's first adjacent vertex.
																	else:
																						SCREAMING_SNAKE_CASE           =    [destination_vertex]
																						SCREAMING_SNAKE_CASE           =    [source_vertex]
												else:  # For directed graphs
																	# if both source vertex and destination vertex are present in adjacency
																	# list, add destination vertex to source vertex list of adjacent vertices.
																	if source_vertex in self.adj_list and destination_vertex in self.adj_list:
																						self.adj_list[source_vertex].append(_UpperCamelCase )
																	# if only source vertex is present in adjacency list, add destination
																	# vertex to source vertex list of adjacent vertices and create a new vertex
																	# with destination vertex as key, which has no adjacent vertex
																	elif source_vertex in self.adj_list:
																						self.adj_list[source_vertex].append(_UpperCamelCase )
																						SCREAMING_SNAKE_CASE           =    []
																	# if only destination vertex is present in adjacency list, create a new
																	# vertex with source vertex as key and assign a list containing destination
																	# vertex as first adjacent vertex
																	elif destination_vertex in self.adj_list:
																						SCREAMING_SNAKE_CASE           =    [destination_vertex]
																	# if both source vertex and destination vertex are not present in adjacency
																	# list, create a new vertex with source vertex as key and a list containing
																	# destination vertex as it's first adjacent vertex. Then create a new vertex
																	# with destination vertex as key, which has no adjacent vertex
																	else:
																						SCREAMING_SNAKE_CASE           =    [destination_vertex]
																						SCREAMING_SNAKE_CASE           =    []

												return self





							def __repr__(  self				:   Union[str, Any] )   ->			str:



												'''simple docstring'''

												return pformat(self.adj_list )




