






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


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







def 						_UpperCamelCase (     UpperCamelCase_							:       str		)	-> CheckpointState:

						"""simple docstring"""



						print(F"Reading saved model from {model_file}"		)
						lowerCAmelCase__         =    torch.load(UpperCamelCase_     ,							map_location=lambda UpperCamelCase_     ,							UpperCamelCase_		: default_restore_location(UpperCamelCase_     ,							'cpu'		)		)
						return CheckpointState(**UpperCamelCase_		)


class      __SCREAMING_SNAKE_CASE       :






						def __init__(						self  ,    _UpperCamelCase ):






												"""simple docstring"""
												lowerCAmelCase__         =    src_file






						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												raise NotImplementedError







						@staticmethod
						def    UpperCamelCase__   (						_UpperCamelCase  ,    *_UpperCamelCase  ,    **_UpperCamelCase ):






												"""simple docstring"""
												if comp_type.startswith('c' ):
																		return DPRContextEncoderState(*_UpperCamelCase  ,    **_UpperCamelCase )
												if comp_type.startswith('q' ):
																		return DPRQuestionEncoderState(*_UpperCamelCase  ,    **_UpperCamelCase )
												if comp_type.startswith('r' ):
																		return DPRReaderState(*_UpperCamelCase  ,    **_UpperCamelCase )
												else:
																		raise ValueError('Component type must be either \'ctx_encoder\', \'question_encoder\' or \'reader\'.' )




class      __SCREAMING_SNAKE_CASE       ( __lowercase):






						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    DPRContextEncoder(DPRConfig(**BertConfig.get_config_dict('bert-base-uncased' )[0] ) )
												print(F"Loading DPR biencoder from {self.src_file}" )
												lowerCAmelCase__         =    load_states_from_checkpoint(self.src_file )
												lowerCAmelCase__    ,							lowerCAmelCase__         =    model.ctx_encoder, 'ctx_model.'
												# Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
												lowerCAmelCase__         =    {'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(_UpperCamelCase ):
																								lowerCAmelCase__         =    key[len(_UpperCamelCase ) :]
																								if not key.startswith('encode_proj.' ):
																														lowerCAmelCase__         =    'bert_model.' + key
																								lowerCAmelCase__         =    value
												encoder.load_state_dict(_UpperCamelCase )
												return model




class      __SCREAMING_SNAKE_CASE       ( __lowercase):






						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    DPRQuestionEncoder(DPRConfig(**BertConfig.get_config_dict('bert-base-uncased' )[0] ) )
												print(F"Loading DPR biencoder from {self.src_file}" )
												lowerCAmelCase__         =    load_states_from_checkpoint(self.src_file )
												lowerCAmelCase__    ,							lowerCAmelCase__         =    model.question_encoder, 'question_model.'
												# Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
												lowerCAmelCase__         =    {'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(_UpperCamelCase ):
																								lowerCAmelCase__         =    key[len(_UpperCamelCase ) :]
																								if not key.startswith('encode_proj.' ):
																														lowerCAmelCase__         =    'bert_model.' + key
																								lowerCAmelCase__         =    value
												encoder.load_state_dict(_UpperCamelCase )
												return model




class      __SCREAMING_SNAKE_CASE       ( __lowercase):






						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    DPRReader(DPRConfig(**BertConfig.get_config_dict('bert-base-uncased' )[0] ) )
												print(F"Loading DPR reader from {self.src_file}" )
												lowerCAmelCase__         =    load_states_from_checkpoint(self.src_file )
												# Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
												lowerCAmelCase__         =    {
												    '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' ):
																								lowerCAmelCase__         =    'encoder.bert_model.' + key[len('encoder.' ) :]
																		lowerCAmelCase__         =    value
												model.span_predictor.load_state_dict(_UpperCamelCase )
												return model







def 						_UpperCamelCase (     UpperCamelCase_							:       str     ,							UpperCamelCase_							:       Path     ,							UpperCamelCase_							:       Path		)	-> Optional[Any]:

						"""simple docstring"""



						lowerCAmelCase__         =    Path(UpperCamelCase_		)
						dest_dir.mkdir(exist_ok=UpperCamelCase_		)

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


if __name__ == "__main__":
					__snake_case     :     Union[str, 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.""")
					__snake_case     :     int       =  parser.parse_args()

					__snake_case     :     Any       =  Path(args.src)
					__snake_case     :     Optional[int]       =  f'converted-{src_file.name}' if args.dest is None else args.dest
					__snake_case     :     str       =  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)













from __future__ import annotations

from collections.abc import Iterable, Iterator
from typing import Any, Generic, TypeVar

__snake_case     :     str       =  TypeVar("""T""", bound=bool)


class      __SCREAMING_SNAKE_CASE       ( Generic[T]):






						def __init__(						self  ,    _UpperCamelCase ):






												"""simple docstring"""
												lowerCAmelCase__         =    value
												lowerCAmelCase__         =    None
												lowerCAmelCase__         =    None






						@property
						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												return self._value







						@staticmethod
						def    UpperCamelCase__   (						_UpperCamelCase  ,    _UpperCamelCase ):






												"""simple docstring"""
												if not roota:
																		return roota

												if not roota:
																		return roota

												if roota.value > roota.value:
																		lowerCAmelCase__    ,							lowerCAmelCase__         =    roota, roota

												lowerCAmelCase__         =    roota
												lowerCAmelCase__         =    roota.right
												lowerCAmelCase__         =    roota.left
												lowerCAmelCase__         =    SkewNode.merge(_UpperCamelCase  ,    _UpperCamelCase )

												return result




class      __SCREAMING_SNAKE_CASE       ( Generic[T]):






						def __init__(						self  ,    _UpperCamelCase = () ):






												"""simple docstring"""
												lowerCAmelCase__         =    None
												if data:
																		for item in data:
																								self.insert(_UpperCamelCase )






						def __bool__(						self ):






												"""simple docstring"""
												return self._root is not None






						def __iter__(						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    []
												while self:
																		result.append(self.pop() )

												# Pushing items back to the heap not to clear it.
												for item in result:
																		self.insert(_UpperCamelCase )

												return iter(_UpperCamelCase )






						def    UpperCamelCase__   (						self  ,    _UpperCamelCase ):






												"""simple docstring"""
												lowerCAmelCase__         =    SkewNode.merge(self._root  ,    SkewNode(_UpperCamelCase ) )






						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    self.top()
												lowerCAmelCase__         =    (
												    SkewNode.merge(self._root.left  ,    self._root.right ) if self._root else None
												)

												return result






						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												if not self._root:
																		raise IndexError('Can\'t get top element for the empty heap.' )
												return self._root.value







						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    None


if __name__ == "__main__":
					import doctest

					doctest.testmod()





