






"""simple docstring"""



import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer



def 						lowercase    (				__snake_case				: int		,					__snake_case				: Dict		,					__snake_case				: List[str]		,					__snake_case				: Optional[int]		,					__snake_case				: str=True		,					__snake_case				: int="pt"	):
		lowercase_ : int							       =   {'''add_prefix_space''': True} if isinstance(__snake_case		,					__snake_case	) and not line.startswith(''' '''	) else {}
		lowercase_ : str							       =   padding_side
		return tokenizer(
		    [line]		,					max_length=__snake_case		,					padding='''max_length''' if pad_to_max_length else None		,					truncation=__snake_case		,					return_tensors=__snake_case		,					add_special_tokens=__snake_case		,					**__snake_case		,					)



def 						lowercase    (				__snake_case				: Dict		,					__snake_case				: Dict		,					__snake_case				: int=None		,					):
		lowercase_ : Optional[Any]							       =   input_ids.ne(__snake_case	).any(dim=0	)
		if attention_mask is None:
				return input_ids[:, keep_column_mask]
		else:
				return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])





class 					_UpperCAmelCase       ( _A							):




					def __init__(				self     :						Any    ,						A     :						str    ,						A     :						Optional[Any]    ,						A     :						int    ,						A     :						Optional[Any]    ,						A     :						Optional[int]="train"    ,						A     :						Dict=None    ,						A     :						int=None    ,						A     :						Union[str, Any]=None    ,						A     :						List[str]=""    ,						)  ->  List[str]:
							super().__init__()
							lowercase_ : Any							       =   Path(A   ).joinpath(type_path + '''.source'''   )
							lowercase_ : int							       =   Path(A   ).joinpath(type_path + '''.target'''   )
							lowercase_ : Optional[Any]							       =   self.get_char_lens(self.src_file   )
							lowercase_ : str							       =   max_source_length
							lowercase_ : Any							       =   max_target_length
							assert min(self.src_lens   ) > 0, F'''found empty line in {self.src_file}'''
							lowercase_ : Union[str, Any]							       =   tokenizer
							lowercase_ : Optional[int]							       =   prefix
							if n_obs is not None:
									lowercase_ : Union[str, Any]							       =   self.src_lens[:n_obs]
							lowercase_ : str							       =   src_lang
							lowercase_ : Any							       =   tgt_lang




					def __len__(				self     :						List[Any]   )  ->  str:
							return len(self.src_lens   )




					def __getitem__(				self     :						Any    ,						A     :						List[str]   )  ->  Dict[str, torch.Tensor]:
							lowercase_ : List[str]							       =   index + 1  # linecache starts at 1
							lowercase_ : int							       =   self.prefix + linecache.getline(str(self.src_file   )    ,						A   ).rstrip('''\n'''   )
							lowercase_ : int							       =   linecache.getline(str(self.tgt_file   )    ,						A   ).rstrip('''\n'''   )
							assert source_line, F'''empty source line for index {index}'''
							assert tgt_line, F'''empty tgt line for index {index}'''

							# Need to add eos token manually for T5
							if isinstance(self.tokenizer    ,						A   ):
									source_line += self.tokenizer.eos_token
									tgt_line += self.tokenizer.eos_token

							# Pad source and target to the right
							lowercase_ : Tuple							       =   (
							    self.tokenizer.question_encoder if isinstance(self.tokenizer    ,						A   ) else self.tokenizer
							)
							lowercase_ : Any							       =   self.tokenizer.generator if isinstance(self.tokenizer    ,						A   ) else self.tokenizer

							lowercase_ : str							       =   encode_line(A    ,						A    ,						self.max_source_length    ,						'''right'''   )
							lowercase_ : Optional[Any]							       =   encode_line(A    ,						A    ,						self.max_target_length    ,						'''right'''   )

							lowercase_ : Any							       =   source_inputs['''input_ids'''].squeeze()
							lowercase_ : List[Any]							       =   target_inputs['''input_ids'''].squeeze()
							lowercase_ : List[str]							       =   source_inputs['''attention_mask'''].squeeze()
							return {
							    "input_ids": source_ids,
							    "attention_mask": src_mask,
							    "decoder_input_ids": target_ids,
							}




					@staticmethod
					def   A  (				A     :						Tuple   )  ->  List[str]:
							return [len(A   ) for x in Path(A   ).open().readlines()]






					def   A  (				self     :						Dict    ,						A     :						Union[str, Any]   )  ->  Dict[str, torch.Tensor]:
							lowercase_ : List[Any]							       =   torch.stack([x['''input_ids'''] for x in batch]   )
							lowercase_ : str							       =   torch.stack([x['''attention_mask'''] for x in batch]   )
							lowercase_ : int							       =   torch.stack([x['''decoder_input_ids'''] for x in batch]   )
							lowercase_ : str							       =   (
							    self.tokenizer.generator.pad_token_id
							    if isinstance(self.tokenizer    ,						A   )
							    else self.tokenizer.pad_token_id
							)
							lowercase_ : Optional[Any]							       =   (
							    self.tokenizer.question_encoder.pad_token_id
							    if isinstance(self.tokenizer    ,						A   )
							    else self.tokenizer.pad_token_id
							)
							lowercase_ : int							       =   trim_batch(A    ,						A   )
							lowercase_       ,					lowercase_ : List[Any]							       =   trim_batch(A    ,						A    ,						attention_mask=A   )
							lowercase_ : List[str]							       =   {
							    '''input_ids''': source_ids,
							    '''attention_mask''': source_mask,
							    '''decoder_input_ids''': y,
							}
							return batch
__A		:       Tuple  				=		getLogger(__name__)



def 						lowercase    (				__snake_case				: List[List]	):
		return list(itertools.chain.from_iterable(__snake_case	)	)



def 						lowercase    (				__snake_case				: str	):
		lowercase_ : str							       =   get_git_info()
		save_json(__snake_case		,					os.path.join(__snake_case		,					'''git_log.json'''	)	)



def 						lowercase    (				__snake_case				: int		,					__snake_case				: List[Any]		,					__snake_case				: Any=4		,					**__snake_case				: Dict	):
		with open(__snake_case		,					'''w'''	) as f:
				json.dump(__snake_case		,					__snake_case		,					indent=__snake_case		,					**__snake_case	)



def 						lowercase    (				__snake_case				: Tuple	):
		with open(__snake_case	) as f:
				return json.load(__snake_case	)



def 						lowercase    (				):
		lowercase_ : Union[str, Any]							       =   git.Repo(search_parent_directories=__snake_case	)
		lowercase_ : Optional[Any]							       =   {
		    '''repo_id''': str(__snake_case	),
		    '''repo_sha''': str(repo.head.object.hexsha	),
		    '''repo_branch''': str(repo.active_branch	),
		    '''hostname''': str(socket.gethostname()	),
		}
		return repo_infos



def 						lowercase    (				__snake_case				: Callable		,					__snake_case				: Iterable	):
		return list(map(__snake_case		,					__snake_case	)	)



def 						lowercase    (				__snake_case				: Any		,					__snake_case				: List[str]	):
		with open(__snake_case		,					'''wb'''	) as f:
				return pickle.dump(__snake_case		,					__snake_case	)



def 						lowercase    (				__snake_case				: Any	):

		def remove_articles(__snake_case				: List[Any]	):
				return re.sub(r'''\b(a|an|the)\b'''		,					''' '''		,					__snake_case	)

		def white_space_fix(__snake_case				: List[str]	):
				return " ".join(text.split()	)

		def remove_punc(__snake_case				: Optional[int]	):
				lowercase_ : str							       =   set(string.punctuation	)
				return "".join(ch for ch in text if ch not in exclude	)

		def lower(__snake_case				: Tuple	):
				return text.lower()

		return white_space_fix(remove_articles(remove_punc(lower(__snake_case	)	)	)	)



def 						lowercase    (				__snake_case				: List[Any]		,					__snake_case				: Dict	):
		lowercase_ : Optional[Any]							       =   normalize_answer(__snake_case	).split()
		lowercase_ : List[Any]							       =   normalize_answer(__snake_case	).split()
		lowercase_ : str							       =   Counter(__snake_case	) & Counter(__snake_case	)
		lowercase_ : Union[str, Any]							       =   sum(common.values()	)
		if num_same == 0:
				return 0
		lowercase_ : Dict							       =   1.0 * num_same / len(__snake_case	)
		lowercase_ : str							       =   1.0 * num_same / len(__snake_case	)
		lowercase_ : Union[str, Any]							       =   (2 * precision * recall) / (precision + recall)
		return fa



def 						lowercase    (				__snake_case				: Optional[Any]		,					__snake_case				: Any	):
		return normalize_answer(__snake_case	) == normalize_answer(__snake_case	)



def 						lowercase    (				__snake_case				: List[str]		,					__snake_case				: List[str]	):
		assert len(__snake_case	) == len(__snake_case	)
		lowercase_ : Union[str, Any]							       =   0
		for hypo, pred in zip(__snake_case		,					__snake_case	):
				em += exact_match_score(__snake_case		,					__snake_case	)
		if len(__snake_case	) > 0:
				em /= len(__snake_case	)
		return {"em": em}



def 						lowercase    (				__snake_case				: List[str]	):
		return model_prefix.startswith('''rag'''	)






def 						lowercase    (				__snake_case				: Optional[int]		,					__snake_case				: str		,					__snake_case				: Union[str, Any]	):
		lowercase_ : Union[str, Any]							       =   {p: p for p in extra_params}
		# T5 models don't have `dropout` param, they have `dropout_rate` instead
		lowercase_ : List[str]							       =   '''dropout_rate'''
		for p in extra_params:
				if getattr(__snake_case		,					__snake_case		,					__snake_case	):
						if not hasattr(__snake_case		,					__snake_case	) and not hasattr(__snake_case		,					equivalent_param[p]	):
								logger.info('''config doesn\'t have a `{}` attribute'''.format(__snake_case	)	)
								delattr(__snake_case		,					__snake_case	)
								continue
						lowercase_ : Tuple							       =   p if hasattr(__snake_case		,					__snake_case	) else equivalent_param[p]
						setattr(__snake_case		,					__snake_case		,					getattr(__snake_case		,					__snake_case	)	)
						delattr(__snake_case		,					__snake_case	)
		return hparams, config











"""simple docstring"""



def 						lowercase    (				__snake_case				: Optional[int]	):
		lowercase_ : int							       =   0
		lowercase_ : Optional[Any]							       =   len(__snake_case	)

		for i in range(n - 1	):
				for j in range(i + 1		,					__snake_case	):
						if arr[i] > arr[j]:
								num_inversions += 1

		return num_inversions



def 						lowercase    (				__snake_case				: str	):
		if len(__snake_case	) <= 1:
				return arr, 0
		lowercase_ : Optional[Any]							       =   len(__snake_case	) // 2
		lowercase_ : List[Any]							       =   arr[0:mid]
		lowercase_ : Union[str, Any]							       =   arr[mid:]

		lowercase_       ,					lowercase_ : Tuple							       =   count_inversions_recursive(__snake_case	)
		lowercase_       ,					lowercase_ : List[Any]							       =   count_inversions_recursive(__snake_case	)
		lowercase_       ,					lowercase_ : List[Any]							       =   _count_cross_inversions(__snake_case		,					__snake_case	)

		lowercase_ : List[Any]							       =   inversion_p + inversions_q + cross_inversions
		return c, num_inversions



def 						lowercase    (				__snake_case				: str		,					__snake_case				: Optional[int]	):
		lowercase_ : Optional[Any]							       =   []
		lowercase_ : Any							       =   0
		while i < len(__snake_case	) and j < len(__snake_case	):
				if p[i] > q[j]:
						# if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
						# These are all inversions. The claim emerges from the
						# property that P is sorted.
						num_inversion += len(__snake_case	) - i
						r.append(q[j]	)
						j += 1
				else:
						r.append(p[i]	)
						i += 1

		if i < len(__snake_case	):
				r.extend(p[i:]	)
		else:
				r.extend(q[j:]	)

		return r, num_inversion



def 						lowercase    (				):
		lowercase_ : Union[str, Any]							       =   [1_0, 2, 1, 5, 5, 2, 1_1]

		# this arr has 8 inversions:
		# (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

		lowercase_ : int							       =   count_inversions_bf(__snake_case	)
		lowercase_       ,					lowercase_ : Dict							       =   count_inversions_recursive(__snake_case	)

		assert num_inversions_bf == num_inversions_recursive == 8

		print('''number of inversions = '''		,					__snake_case	)

		# testing an array with zero inversion (a sorted arr_1)

		arr_a.sort()
		lowercase_ : Dict							       =   count_inversions_bf(__snake_case	)
		lowercase_       ,					lowercase_ : Dict							       =   count_inversions_recursive(__snake_case	)

		assert num_inversions_bf == num_inversions_recursive == 0
		print('''number of inversions = '''		,					__snake_case	)

		# an empty list should also have zero inversions
		lowercase_ : List[Any]							       =   []
		lowercase_ : Any							       =   count_inversions_bf(__snake_case	)
		lowercase_       ,					lowercase_ : List[str]							       =   count_inversions_recursive(__snake_case	)

		assert num_inversions_bf == num_inversions_recursive == 0
		print('''number of inversions = '''		,					__snake_case	)


if __name__ == "__main__":
						main()



