
import argparse
import collections
from pathlib import Path

import torch
from torch.serialization import default_restore_location

from transformers import BertConfig, DPRConfig, DPRContextEncoder, DPRQuestionEncoder, DPRReader


lowercase__						:Optional[Any]					    =       collections.namedtuple(
    "CheckpointState", ["model_dict", "optimizer_dict", "scheduler_dict", "offset", "epoch", "encoder_params"]
)



def 			UpperCamelCase       (				lowerCAmelCase__						):
					'''simple docstring'''
					print(f'Reading saved model from {model_file}'						)
					lowercase		      =		torch.load(lowerCAmelCase__					,     map_location=lambda lowerCAmelCase__					,     lowerCAmelCase__						: default_restore_location(lowerCAmelCase__					,     '''cpu'''						)						)
					return CheckpointState(**lowerCAmelCase__						)







class 							lowercase						:




							def __init__(							self  ,A__):
												lowercase		      =		src_file




							def 					A__ (							self):
												raise NotImplementedError





							@staticmethod
							def 					A__ (							A__  ,*A__  ,**A__):
												if comp_type.startswith('''c'''):
																	return DPRContextEncoderState(*A__  ,**A__)
												if comp_type.startswith('''q'''):
																	return DPRQuestionEncoderState(*A__  ,**A__)
												if comp_type.startswith('''r'''):
																	return DPRReaderState(*A__  ,**A__)
												else:
																	raise ValueError('''Component type must be either \'ctx_encoder\', \'question_encoder\' or \'reader\'.''')







class 							lowercase						(   SCREAMING_SNAKE_CASE__						):




							def 					A__ (							self):
												lowercase		      =		DPRContextEncoder(DPRConfig(**BertConfig.get_config_dict('''bert-base-uncased''')[0]))
												print(f'Loading DPR biencoder from {self.src_file}')
												lowercase		      =		load_states_from_checkpoint(self.src_file)
												lowercase      ,		lowercase		      =		model.ctx_encoder, '''ctx_model.'''
												# Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
												lowercase		      =		{'''bert_model.embeddings.position_ids''': model.ctx_encoder.bert_model.embeddings.position_ids}
												for key, value in saved_state.model_dict.items():
																	if key.startswith(A__):
																						lowercase		      =		key[len(A__) :]
																						if not key.startswith('''encode_proj.'''):
																											lowercase		      =		'''bert_model.''' + key
																						lowercase		      =		value
												encoder.load_state_dict(A__)
												return model







class 							lowercase						(   SCREAMING_SNAKE_CASE__						):




							def 					A__ (							self):
												lowercase		      =		DPRQuestionEncoder(DPRConfig(**BertConfig.get_config_dict('''bert-base-uncased''')[0]))
												print(f'Loading DPR biencoder from {self.src_file}')
												lowercase		      =		load_states_from_checkpoint(self.src_file)
												lowercase      ,		lowercase		      =		model.question_encoder, '''question_model.'''
												# Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
												lowercase		      =		{'''bert_model.embeddings.position_ids''': model.question_encoder.bert_model.embeddings.position_ids}
												for key, value in saved_state.model_dict.items():
																	if key.startswith(A__):
																						lowercase		      =		key[len(A__) :]
																						if not key.startswith('''encode_proj.'''):
																											lowercase		      =		'''bert_model.''' + key
																						lowercase		      =		value
												encoder.load_state_dict(A__)
												return model







class 							lowercase						(   SCREAMING_SNAKE_CASE__						):




							def 					A__ (							self):
												lowercase		      =		DPRReader(DPRConfig(**BertConfig.get_config_dict('''bert-base-uncased''')[0]))
												print(f'Loading DPR reader from {self.src_file}')
												lowercase		      =		load_states_from_checkpoint(self.src_file)
												# Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
												lowercase		      =		{
												    '''encoder.bert_model.embeddings.position_ids''': model.span_predictor.encoder.bert_model.embeddings.position_ids
												}
												for key, value in saved_state.model_dict.items():
																	if key.startswith('''encoder.''') and not key.startswith('''encoder.encode_proj'''):
																						lowercase		      =		'''encoder.bert_model.''' + key[len('''encoder.''') :]
																	lowercase		      =		value
												model.span_predictor.load_state_dict(A__)
												return model



def 			UpperCamelCase       (				lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__						):
					'''simple docstring'''
					lowercase		      =		Path(lowerCAmelCase__						)
					dest_dir.mkdir(exist_ok=lowerCAmelCase__						)

					lowercase		      =		DPRState.from_type(lowerCAmelCase__					,     src_file=lowerCAmelCase__						)
					lowercase		      =		dpr_state.load_dpr_model()
					model.save_pretrained(lowerCAmelCase__						)
					model.from_pretrained(lowerCAmelCase__						)  # sanity check


if __name__ == "__main__":
							lowercase__						:List[Any]					    =       argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    "--type", type=str, help="Type of the component to convert: 'ctx_encoder', 'question_encoder' or 'reader'."
							)
							parser.add_argument(
							    "--src",
							    type=str,
							    help=(
							        "Path to the dpr checkpoint file. They can be downloaded from the official DPR repo"
							        " https://github.com/facebookresearch/DPR. Note that in the official repo, both encoders are stored in the"
							        " 'retriever' checkpoints."
							    ),
							)
							parser.add_argument("--dest", type=str, default=None, help="Path to the output PyTorch model directory.")
							lowercase__						:Union[str, Any]					    =       parser.parse_args()

							lowercase__						:Optional[Any]					    =       Path(args.src)
							lowercase__						:Optional[Any]					    =       F'converted-{src_file.name}' if args.dest is None else args.dest
							lowercase__						:Dict					    =       Path(dest_dir)
							assert src_file.exists()
							assert (
							    args.type is not None
							), "Please specify the component type of the DPR model to convert: 'ctx_encoder', 'question_encoder' or 'reader'."
							convert(args.type, src_file, dest_dir)






def 			UpperCamelCase       (				lowerCAmelCase__ = 30						):
					'''simple docstring'''
					lowercase		      =		exponent + 2
					lowercase		      =		(1 + 5**0.5) / 2
					lowercase		      =		(phi**fibonacci_index - (phi - 1) ** fibonacci_index) / 5**0.5

					return int(lowerCAmelCase__						)


if __name__ == "__main__":
							print(F'{solution() = }')




