
"""simple docstring"""




import logging
import os
import threading
import time


try:
						import warnings
except ImportError:
						A_							:			Optional[int]											= None

try:
						import msvcrt
except ImportError:
						A_							:			Any											= None

try:
						import fcntl
except ImportError:
						A_							:			List[Any]											= None


# Backward compatibility
# ------------------------------------------------
try:
						TimeoutError
except NameError:
						A_							:			Optional[Any]											= OSError


# Data
# ------------------------------------------------
A_							:			Union[str, Any]											= [
    "Timeout",
    "BaseFileLock",
    "WindowsFileLock",
    "UnixFileLock",
    "SoftFileLock",
    "FileLock",
]

A_							:			Union[str, Any]											= "3.0.12"


A_							:			str											= None

def 	A       (     ):




			'''simple docstring'''


			global _logger
			SCREAMING_SNAKE_CASE__								=      _logger or logging.getLogger(__name__    )
			return _logger





class    lowerCamelCase						(_UpperCAmelCase			):

			def __init__(					self				:						int    ,				__UpperCAmelCase				:						List[Any]       )   ->    Tuple:
						SCREAMING_SNAKE_CASE__								=      lock_file
						return None





			def __str__(					self				:						List[str]       )   ->    Any:
						SCREAMING_SNAKE_CASE__								=      F"""The file lock '{self.lock_file}' could not be acquired."""
						return temp





class    lowerCamelCase						:

			def __init__(					self				:						str    ,				__UpperCAmelCase				:						Union[str, Any]       )   ->    List[Any]:
						SCREAMING_SNAKE_CASE__								=      lock
						return None

			def __enter__(					self				:						Tuple       )   ->    Union[str, Any]:
						return self.lock





			def __exit__(					self				:						Optional[Any]    ,				__UpperCAmelCase				:						Tuple    ,				__UpperCAmelCase				:						List[str]    ,				__UpperCAmelCase				:						Optional[Any]       )   ->    Any:
						self.lock.release()
						return None





class    lowerCamelCase						:

			def __init__(					self				:						Any    ,				__UpperCAmelCase				:						Optional[Any]    ,				__UpperCAmelCase				:						Tuple=-1    ,				__UpperCAmelCase				:						str=None       )   ->    Dict:
						SCREAMING_SNAKE_CASE__								=      max_filename_length if max_filename_length is not None else 2_5_5
						# Hash the filename if it's too long
						SCREAMING_SNAKE_CASE__								=      self.hash_filename_if_too_long(lowerCamelCase_    ,				lowerCamelCase_       )
						# The path to the lock file.
						SCREAMING_SNAKE_CASE__								=      lock_file

						# The file descriptor for the *_lock_file* as it is returned by the
						# os.open() function.
						# This file lock is only NOT None, if the object currently holds the
						# lock.
						SCREAMING_SNAKE_CASE__								=      None

						# The default timeout value.
						SCREAMING_SNAKE_CASE__								=      timeout

						# We use this lock primarily for the lock counter.
						SCREAMING_SNAKE_CASE__								=      threading.Lock()

						# The lock counter is used for implementing the nested locking
						# mechanism. Whenever the lock is acquired, the counter is increased and
						# the lock is only released, when this value is 0 again.
						SCREAMING_SNAKE_CASE__								=      0
						return None

			@property
			def 					SCREAMING_SNAKE_CASE				(					self				:						str       )   ->    Any:
						return self._lock_file

			@property
			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[Any]       )   ->    Tuple:
						return self._timeout

			@timeout.setter
			def 					SCREAMING_SNAKE_CASE				(					self				:						Tuple    ,				__UpperCAmelCase				:						List[str]       )   ->    Union[str, Any]:
						SCREAMING_SNAKE_CASE__								=      float(lowerCamelCase_       )
						return None

			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[int]       )   ->    Tuple:
						raise NotImplementedError()

			def 					SCREAMING_SNAKE_CASE				(					self				:						List[str]       )   ->    str:
						raise NotImplementedError()

			@property
			def 					SCREAMING_SNAKE_CASE				(					self				:						Dict       )   ->    Any:
						return self._lock_file_fd is not None

			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[Any]    ,				__UpperCAmelCase				:						Any=None    ,				__UpperCAmelCase				:						Optional[int]=0.05       )   ->    Union[str, Any]:




						if timeout is None:
									SCREAMING_SNAKE_CASE__								=      self.timeout

						# Increment the number right at the beginning.
						# We can still undo it, if something fails.
						with self._thread_lock:
									self._lock_counter += 1

						SCREAMING_SNAKE_CASE__								=      id(self       )
						SCREAMING_SNAKE_CASE__								=      self._lock_file
						SCREAMING_SNAKE_CASE__								=      time.time()
						try:
									while True:
												with self._thread_lock:
															if not self.is_locked:
																		logger().debug(F"""Attempting to acquire lock {lock_id} on {lock_filename}"""       )
																		self._acquire()

												if self.is_locked:
															logger().debug(F"""Lock {lock_id} acquired on {lock_filename}"""       )
															break
												elif timeout >= 0 and time.time() - start_time > timeout:
															logger().debug(F"""Timeout on acquiring lock {lock_id} on {lock_filename}"""       )
															raise Timeout(self._lock_file       )
												else:
															logger().debug(
															    F"""Lock {lock_id} not acquired on {lock_filename}, waiting {poll_intervall} seconds ..."""       )
															time.sleep(lowerCamelCase_       )
						except:  # noqa
									# Something did go wrong, so decrement the counter.
									with self._thread_lock:
												SCREAMING_SNAKE_CASE__								=      max(0    ,				self._lock_counter - 1       )

									raise
						return _Acquire_ReturnProxy(lock=self       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						int    ,				__UpperCAmelCase				:						Dict=False       )   ->    Tuple:




						with self._thread_lock:
									if self.is_locked:
												self._lock_counter -= 1

												if self._lock_counter == 0 or force:
															SCREAMING_SNAKE_CASE__								=      id(self       )
															SCREAMING_SNAKE_CASE__								=      self._lock_file

															logger().debug(F"""Attempting to release lock {lock_id} on {lock_filename}"""       )
															self._release()
															SCREAMING_SNAKE_CASE__								=      0
															logger().debug(F"""Lock {lock_id} released on {lock_filename}"""       )

						return None

			def __enter__(					self				:						Any       )   ->    Optional[int]:
						self.acquire()
						return self

			def __exit__(					self				:						Tuple    ,				__UpperCAmelCase				:						Optional[int]    ,				__UpperCAmelCase				:						List[str]    ,				__UpperCAmelCase				:						Union[str, Any]       )   ->    List[str]:
						self.release()
						return None

			def __del__(					self				:						List[Any]       )   ->    int:
						self.release(force=lowerCamelCase_       )
						return None





			def 					SCREAMING_SNAKE_CASE				(					self				:						List[Any]    ,				__UpperCAmelCase				:						str    ,				__UpperCAmelCase				:						int       )   ->    str:
						SCREAMING_SNAKE_CASE__								=      os.path.basename(lowerCamelCase_       )
						if len(lowerCamelCase_       ) > max_length and max_length > 0:
									SCREAMING_SNAKE_CASE__								=      os.path.dirname(lowerCamelCase_       )
									SCREAMING_SNAKE_CASE__								=      str(hash(lowerCamelCase_       )       )
									SCREAMING_SNAKE_CASE__								=      filename[: max_length - len(lowerCamelCase_       ) - 8] + '''...''' + hashed_filename + '''.lock'''
									return os.path.join(lowerCamelCase_    ,				lowerCamelCase_       )
						else:
									return path





class    lowerCamelCase						(_UpperCAmelCase			):

			def __init__(					self				:						int    ,				__UpperCAmelCase				:						List[Any]    ,				__UpperCAmelCase				:						Optional[int]=-1    ,				__UpperCAmelCase				:						List[Any]=None       )   ->    Union[str, Any]:
						from .file_utils import relative_to_absolute_path

						super().__init__(lowerCamelCase_    ,				timeout=lowerCamelCase_    ,				max_filename_length=lowerCamelCase_       )
						SCREAMING_SNAKE_CASE__								=      '''\\\\?\\''' + relative_to_absolute_path(self.lock_file       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						Any       )   ->    Union[str, Any]:
						SCREAMING_SNAKE_CASE__								=      os.O_RDWR | os.O_CREAT | os.O_TRUNC

						try:
									SCREAMING_SNAKE_CASE__								=      os.open(self._lock_file    ,				lowerCamelCase_       )
						except OSError:
									pass
						else:
									try:
												msvcrt.locking(lowerCamelCase_    ,				msvcrt.LK_NBLCK    ,				1       )
									except OSError:
												os.close(lowerCamelCase_       )
									else:
												SCREAMING_SNAKE_CASE__								=      fd
						return None





			def 					SCREAMING_SNAKE_CASE				(					self				:						List[Any]       )   ->    int:
						SCREAMING_SNAKE_CASE__								=      self._lock_file_fd
						SCREAMING_SNAKE_CASE__								=      None
						msvcrt.locking(lowerCamelCase_    ,				msvcrt.LK_UNLCK    ,				1       )
						os.close(lowerCamelCase_       )

						try:
									os.remove(self._lock_file       )
						# Probably another instance of the application
						# that acquired the file lock.
						except OSError:
									pass
						return None





class    lowerCamelCase						(_UpperCAmelCase			):

			def __init__(					self				:						List[str]    ,				__UpperCAmelCase				:						List[str]    ,				__UpperCAmelCase				:						Optional[Any]=-1    ,				__UpperCAmelCase				:						Any=None       )   ->    int:
						SCREAMING_SNAKE_CASE__								=      os.statvfs(os.path.dirname(lowerCamelCase_       )       ).f_namemax
						super().__init__(lowerCamelCase_    ,				timeout=lowerCamelCase_    ,				max_filename_length=lowerCamelCase_       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						Union[str, Any]       )   ->    Any:
						SCREAMING_SNAKE_CASE__								=      os.O_RDWR | os.O_CREAT | os.O_TRUNC
						SCREAMING_SNAKE_CASE__								=      os.open(self._lock_file    ,				lowerCamelCase_       )

						try:
									fcntl.flock(lowerCamelCase_    ,				fcntl.LOCK_EX | fcntl.LOCK_NB       )
						except OSError:
									os.close(lowerCamelCase_       )
						else:
									SCREAMING_SNAKE_CASE__								=      fd
						return None





			def 					SCREAMING_SNAKE_CASE				(					self				:						List[str]       )   ->    Dict:
						SCREAMING_SNAKE_CASE__								=      self._lock_file_fd
						SCREAMING_SNAKE_CASE__								=      None
						fcntl.flock(lowerCamelCase_    ,				fcntl.LOCK_UN       )
						os.close(lowerCamelCase_       )
						return None





class    lowerCamelCase						(_UpperCAmelCase			):

			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[int]       )   ->    int:
						SCREAMING_SNAKE_CASE__								=      os.O_WRONLY | os.O_CREAT | os.O_EXCL | os.O_TRUNC
						try:
									SCREAMING_SNAKE_CASE__								=      os.open(self._lock_file    ,				lowerCamelCase_       )
						except OSError:
									pass
						else:
									SCREAMING_SNAKE_CASE__								=      fd
						return None





			def 					SCREAMING_SNAKE_CASE				(					self				:						List[str]       )   ->    List[Any]:
						os.close(self._lock_file_fd       )
						SCREAMING_SNAKE_CASE__								=      None

						try:
									os.remove(self._lock_file       )
						# The file is already deleted and that's what we want.
						except OSError:
									pass
						return None
A_							:			Union[str, Any]											= None

if msvcrt:
						A_							:			Union[str, Any]											= WindowsFileLock
elif fcntl:
						A_							:			Dict											= UnixFileLock
else:
						A_							:			List[str]											= SoftFileLock

						if warnings is not None:
												warnings.warn("only soft file lock is available")





"""simple docstring"""




import argparse
import logging
from collections import namedtuple

import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer  # The authors' implementation

from transformers import BertTokenizer


logging.basicConfig(level=logging.INFO)
A_							:			Tuple											= logging.getLogger(__name__)


A_							:			Tuple											= "Hello world! cécé herlolip"


A_							:			Dict											= namedtuple(
    "BertAbsConfig",
    [
        "temp_dir",
        "large",
        "use_bert_emb",
        "finetune_bert",
        "encoder",
        "share_emb",
        "max_pos",
        "enc_layers",
        "enc_hidden_size",
        "enc_heads",
        "enc_ff_size",
        "enc_dropout",
        "dec_layers",
        "dec_hidden_size",
        "dec_heads",
        "dec_ff_size",
        "dec_dropout",
    ],
)

def 	A       (     snake_case__		,				snake_case__    ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__								=      BertAbsConfig(
			    temp_dir="""."""		,				finetune_bert=snake_case__		,				large=snake_case__		,				share_emb=snake_case__		,				use_bert_emb=snake_case__		,				encoder="""bert"""		,				max_pos=5_12		,				enc_layers=6		,				enc_hidden_size=5_12		,				enc_heads=8		,				enc_ff_size=5_12		,				enc_dropout=0.2		,				dec_layers=6		,				dec_hidden_size=7_68		,				dec_heads=8		,				dec_ff_size=20_48		,				dec_dropout=0.2		,				)
			SCREAMING_SNAKE_CASE__								=      torch.load(snake_case__		,				lambda snake_case__		,				snake_case__    : storage    )
			SCREAMING_SNAKE_CASE__								=      AbsSummarizer(snake_case__		,				torch.device("""cpu"""    )		,				snake_case__    )
			original.eval()

			SCREAMING_SNAKE_CASE__								=      BertAbsSummarizer(snake_case__		,				torch.device("""cpu"""    )    )
			new_model.eval()

			# -------------------
			# Convert the weights
			# -------------------

			logging.info("""convert the model"""    )
			new_model.bert.load_state_dict(original.bert.state_dict()    )
			new_model.decoder.load_state_dict(original.decoder.state_dict()    )
			new_model.generator.load_state_dict(original.generator.state_dict()    )

			# ----------------------------------
			# Make sure the outpus are identical
			# ----------------------------------

			logging.info("""Make sure that the models' outputs are identical"""    )
			SCREAMING_SNAKE_CASE__								=      BertTokenizer.from_pretrained("""bert-base-uncased"""    )

			# prepare the model inputs
			SCREAMING_SNAKE_CASE__								=      tokenizer.encode("""This is sample éàalj'-."""    )
			encoder_input_ids.extend([tokenizer.pad_token_id] * (5_12 - len(snake_case__    ))    )
			SCREAMING_SNAKE_CASE__								=      torch.tensor(snake_case__    ).unsqueeze(0    )
			SCREAMING_SNAKE_CASE__								=      tokenizer.encode("""This is sample 3 éàalj'-."""    )
			decoder_input_ids.extend([tokenizer.pad_token_id] * (5_12 - len(snake_case__    ))    )
			SCREAMING_SNAKE_CASE__								=      torch.tensor(snake_case__    ).unsqueeze(0    )

			# failsafe to make sure the weights reset does not affect the
			# loaded weights.
			assert torch.max(torch.abs(original.generator[0].weight - new_model.generator[0].weight    )    ) == 0

			# forward pass
			SCREAMING_SNAKE_CASE__								=      encoder_input_ids
			SCREAMING_SNAKE_CASE__								=      decoder_input_ids
			SCREAMING_SNAKE_CASE__								=      SCREAMING_SNAKE_CASE__								=      None
			SCREAMING_SNAKE_CASE__								=      None
			SCREAMING_SNAKE_CASE__								=      SCREAMING_SNAKE_CASE__								=      None
			SCREAMING_SNAKE_CASE__								=      SCREAMING_SNAKE_CASE__								=      None
			SCREAMING_SNAKE_CASE__								=      None

			# The original model does not apply the geneator layer immediatly but rather in
			# the beam search (where it combines softmax + linear layer). Since we already
			# apply the softmax in our generation process we only apply the linear layer here.
			# We make sure that the outputs of the full stack are identical
			SCREAMING_SNAKE_CASE__								=      original(snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__    )[0]
			SCREAMING_SNAKE_CASE__								=      original.generator(snake_case__    )

			SCREAMING_SNAKE_CASE__								=      new_model(
			    snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__    )[0]
			SCREAMING_SNAKE_CASE__								=      new_model.generator(snake_case__    )

			SCREAMING_SNAKE_CASE__								=      torch.max(torch.abs(output_converted_model - output_original_model    )    ).item()
			print("""Maximum absolute difference beween weights: {:.2f}""".format(snake_case__    )    )
			SCREAMING_SNAKE_CASE__								=      torch.max(torch.abs(output_converted_generator - output_original_generator    )    ).item()
			print("""Maximum absolute difference beween weights: {:.2f}""".format(snake_case__    )    )

			SCREAMING_SNAKE_CASE__								=      torch.allclose(snake_case__		,				snake_case__		,				atol=1e-3    )
			if are_identical:
						logging.info("""all weights are equal up to 1e-3"""    )
			else:
						raise ValueError("""the weights are different. The new model is likely different from the original one."""    )

			# The model has been saved with torch.save(model) and this is bound to the exact
			# directory structure. We save the state_dict instead.
			logging.info("""saving the model's state dictionary"""    )
			torch.save(
			    new_model.state_dict()		,				"""./bertabs-finetuned-cnndm-extractive-abstractive-summarization/pytorch_model.bin"""    )


if __name__ == "__main__":
						A_							:			Dict											= argparse.ArgumentParser()
						parser.add_argument(
						    "--bertabs_checkpoint_path",
						    default=None,
						    type=str,
						    required=True,
						    help="Path the official PyTorch dump.",
						)
						parser.add_argument(
						    "--pytorch_dump_folder_path",
						    default=None,
						    type=str,
						    required=True,
						    help="Path to the output PyTorch model.",
						)
						A_							:			Tuple											= parser.parse_args()

						convert_bertabs_checkpoints(
						    args.bertabs_checkpoint_path,
						    args.pytorch_dump_folder_path,
						)


