




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 		_A(       UpperCamelCase__							:			Union[str, Any]				,       UpperCamelCase__							:			int				,       UpperCamelCase__							:			Tuple				,       UpperCamelCase__							:			Optional[int]				,       UpperCamelCase__							:			Any=True				,       UpperCamelCase__							:			Dict="pt"				)    -> Optional[int]:
							'''simple docstring'''


							__lowercase      =    {'''add_prefix_space''': True} if isinstance(UpperCamelCase__				,       UpperCamelCase__				) and not line.startswith(''' '''				) else {}
							__lowercase      =    padding_side
							return tokenizer(
							    [line]				,       max_length=UpperCamelCase__				,       padding='''max_length''' if pad_to_max_length else None				,       truncation=UpperCamelCase__				,       return_tensors=UpperCamelCase__				,       add_special_tokens=UpperCamelCase__				,       **UpperCamelCase__				,       )







def 		_A(       UpperCamelCase__							:			Union[str, Any]				,       UpperCamelCase__							:			Union[str, Any]				,       UpperCamelCase__							:			List[str]=None				,       )    -> Optional[Any]:
							'''simple docstring'''


							__lowercase      =    input_ids.ne(UpperCamelCase__				).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 a (     __SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						def __init__( self :     Union[str, Any]				,							lowerCamelCase__ :     Tuple				,							lowerCamelCase__ :     Tuple				,							lowerCamelCase__ :     Tuple				,							lowerCamelCase__ :     int				,							lowerCamelCase__ :     Dict="train"				,							lowerCamelCase__ :     Optional[int]=None				,							lowerCamelCase__ :     Dict=None				,							lowerCamelCase__ :     Any=None				,							lowerCamelCase__ :     List[Any]=""				,							)    ->						Union[str, Any]:
													"""simple docstring"""


													super().__init__()
													__lowercase      =    Path(lowerCamelCase__				).joinpath(type_path + '''.source'''				)
													__lowercase      =    Path(lowerCamelCase__				).joinpath(type_path + '''.target'''				)
													__lowercase      =    self.get_char_lens(self.src_file				)
													__lowercase      =    max_source_length
													__lowercase      =    max_target_length
													assert min(self.src_lens				) > 0, f'found empty line in {self.src_file}'
													__lowercase      =    tokenizer
													__lowercase      =    prefix
													if n_obs is not None:
																				__lowercase      =    self.src_lens[:n_obs]
													__lowercase      =    src_lang
													__lowercase      =    tgt_lang






						def __len__( self :     List[str]				)    ->						Tuple:
													"""simple docstring"""


													return len(self.src_lens				)






						def __getitem__( self :     List[str]				,							lowerCamelCase__ :     Tuple				)    ->						Dict[str, torch.Tensor]:
													"""simple docstring"""


													__lowercase      =    index + 1  # linecache starts at 1
													__lowercase      =    self.prefix + linecache.getline(str(self.src_file				)				,							lowerCamelCase__				).rstrip('''\n'''				)
													__lowercase      =    linecache.getline(str(self.tgt_file				)				,							lowerCamelCase__				).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				,							lowerCamelCase__				):
																				source_line += self.tokenizer.eos_token
																				tgt_line += self.tokenizer.eos_token

													# Pad source and target to the right
													__lowercase      =    (
													    self.tokenizer.question_encoder if isinstance(self.tokenizer				,							lowerCamelCase__				) else self.tokenizer
													)
													__lowercase      =    self.tokenizer.generator if isinstance(self.tokenizer				,							lowerCamelCase__				) else self.tokenizer

													__lowercase      =    encode_line(lowerCamelCase__				,							lowerCamelCase__				,							self.max_source_length				,							'''right'''				)
													__lowercase      =    encode_line(lowerCamelCase__				,							lowerCamelCase__				,							self.max_target_length				,							'''right'''				)

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






						@staticmethod
						def     UpperCAmelCase_      ( lowerCamelCase__ :     Any				)    ->						Dict:
													"""simple docstring"""


													return [len(lowerCamelCase__				) for x in Path(lowerCamelCase__				).open().readlines()]






						def     UpperCAmelCase_      ( self :     str				,							lowerCamelCase__ :     int				)    ->						Dict[str, torch.Tensor]:
													"""simple docstring"""


													__lowercase      =    torch.stack([x['''input_ids'''] for x in batch]				)
													__lowercase      =    torch.stack([x['''attention_mask'''] for x in batch]				)
													__lowercase      =    torch.stack([x['''decoder_input_ids'''] for x in batch]				)
													__lowercase      =    (
													    self.tokenizer.generator.pad_token_id
													    if isinstance(self.tokenizer				,							lowerCamelCase__				)
													    else self.tokenizer.pad_token_id
													)
													__lowercase      =    (
													    self.tokenizer.question_encoder.pad_token_id
													    if isinstance(self.tokenizer				,							lowerCamelCase__				)
													    else self.tokenizer.pad_token_id
													)
													__lowercase      =    trim_batch(lowerCamelCase__				,							lowerCamelCase__				)
													__lowercase     ,     __lowercase      =    trim_batch(lowerCamelCase__				,							lowerCamelCase__				,							attention_mask=lowerCamelCase__				)
													__lowercase      =    {
													    '''input_ids''': source_ids,
													    '''attention_mask''': source_mask,
													    '''decoder_input_ids''': y,
													}
													return batch





UpperCAmelCase__				     = getLogger(__name__)







def 		_A(       UpperCamelCase__							:			List[List]				)    -> Union[str, Any]:
							'''simple docstring'''


							return list(itertools.chain.from_iterable(UpperCamelCase__				)				)







def 		_A(       UpperCamelCase__							:			str				)    -> None:
							'''simple docstring'''


							__lowercase      =    get_git_info()
							save_json(UpperCamelCase__				,       os.path.join(UpperCamelCase__				,       '''git_log.json'''				)				)







def 		_A(       UpperCamelCase__							:			Optional[int]				,       UpperCamelCase__							:			Optional[int]				,       UpperCamelCase__							:			Optional[int]=4				,       **UpperCamelCase__							:			List[str]				)    -> Tuple:
							'''simple docstring'''


							with open(UpperCamelCase__				,       '''w'''				) as f:
														json.dump(UpperCamelCase__				,       UpperCamelCase__				,       indent=UpperCamelCase__				,       **UpperCamelCase__				)







def 		_A(       UpperCamelCase__							:			List[str]				)    -> List[str]:
							'''simple docstring'''


							with open(UpperCamelCase__				) as f:
														return json.load(UpperCamelCase__				)







def 		_A(       )    -> Optional[Any]:
							'''simple docstring'''


							__lowercase      =    git.Repo(search_parent_directories=UpperCamelCase__				)
							__lowercase      =    {
							    '''repo_id''': str(UpperCamelCase__				),
							    '''repo_sha''': str(repo.head.object.hexsha				),
							    '''repo_branch''': str(repo.active_branch				),
							    '''hostname''': str(socket.gethostname()				),
							}
							return repo_infos







def 		_A(       UpperCamelCase__							:			Callable				,       UpperCamelCase__							:			Iterable				)    -> List:
							'''simple docstring'''


							return list(map(UpperCamelCase__				,       UpperCamelCase__				)				)







def 		_A(       UpperCamelCase__							:			Any				,       UpperCamelCase__							:			Optional[Any]				)    -> Any:
							'''simple docstring'''


							with open(UpperCamelCase__				,       '''wb'''				) as f:
														return pickle.dump(UpperCamelCase__				,       UpperCamelCase__				)







def 		_A(       UpperCamelCase__							:			Dict				)    -> Optional[int]:
							'''simple docstring'''


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

							def white_space_fix(UpperCamelCase__							:			Dict				):
														return " ".join(text.split()				)

							def remove_punc(UpperCamelCase__							:			Any				):
														__lowercase      =    set(string.punctuation				)
														return "".join(ch for ch in text if ch not in exclude				)

							def lower(UpperCamelCase__							:			str				):
														return text.lower()

							return white_space_fix(remove_articles(remove_punc(lower(UpperCamelCase__				)				)				)				)







def 		_A(       UpperCamelCase__							:			Dict				,       UpperCamelCase__							:			Tuple				)    -> int:
							'''simple docstring'''


							__lowercase      =    normalize_answer(UpperCamelCase__				).split()
							__lowercase      =    normalize_answer(UpperCamelCase__				).split()
							__lowercase      =    Counter(UpperCamelCase__				) & Counter(UpperCamelCase__				)
							__lowercase      =    sum(common.values()				)
							if num_same == 0:
														return 0
							__lowercase      =    1.0 * num_same / len(UpperCamelCase__				)
							__lowercase      =    1.0 * num_same / len(UpperCamelCase__				)
							__lowercase      =    (2 * precision * recall) / (precision + recall)
							return fa







def 		_A(       UpperCamelCase__							:			List[str]				,       UpperCamelCase__							:			Tuple				)    -> Optional[Any]:
							'''simple docstring'''


							return normalize_answer(UpperCamelCase__				) == normalize_answer(UpperCamelCase__				)







def 		_A(       UpperCamelCase__							:			List[str]				,       UpperCamelCase__							:			List[str]				)    -> Dict:
							'''simple docstring'''


							assert len(UpperCamelCase__				) == len(UpperCamelCase__				)
							__lowercase      =    0
							for hypo, pred in zip(UpperCamelCase__				,       UpperCamelCase__				):
														em += exact_match_score(UpperCamelCase__				,       UpperCamelCase__				)
							if len(UpperCamelCase__				) > 0:
														em /= len(UpperCamelCase__				)
							return {"em": em}







def 		_A(       UpperCamelCase__							:			Any				)    -> int:
							'''simple docstring'''


							return model_prefix.startswith('''rag'''				)







def 		_A(       UpperCamelCase__							:			Any				,       UpperCamelCase__							:			Any				,       UpperCamelCase__							:			Optional[int]				)    -> Optional[Any]:
							'''simple docstring'''


							__lowercase      =    {p: p for p in extra_params}
							# T5 models don't have `dropout` param, they have `dropout_rate` instead
							__lowercase      =    '''dropout_rate'''
							for p in extra_params:
														if getattr(UpperCamelCase__				,       UpperCamelCase__				,       UpperCamelCase__				):
																					if not hasattr(UpperCamelCase__				,       UpperCamelCase__				) and not hasattr(UpperCamelCase__				,       equivalent_param[p]				):
																												logger.info('''config doesn\'t have a `{}` attribute'''.format(UpperCamelCase__				)				)
																												delattr(UpperCamelCase__				,       UpperCamelCase__				)
																												continue
																					__lowercase      =    p if hasattr(UpperCamelCase__				,       UpperCamelCase__				) else equivalent_param[p]
																					setattr(UpperCamelCase__				,       UpperCamelCase__				,       getattr(UpperCamelCase__				,       UpperCamelCase__				)				)
																					delattr(UpperCamelCase__				,       UpperCamelCase__				)
							return hparams, config












import itertools
import string
from collections.abc import Generator, Iterable







def 		_A(       UpperCamelCase__							:			Iterable[str]				,       UpperCamelCase__							:			int				)    -> Generator[tuple[str, ...], None, None]:
							'''simple docstring'''


							__lowercase      =    iter(UpperCamelCase__				)
							while True:
														__lowercase      =    tuple(itertools.islice(UpperCamelCase__				,       UpperCamelCase__				)				)
														if not chunk:
																					return
														yield chunk







def 		_A(       UpperCamelCase__							:			str				)    -> str:
							'''simple docstring'''


							__lowercase      =    ''''''.join([c.upper() for c in dirty if c in string.ascii_letters]				)
							__lowercase      =    ''''''

							if len(UpperCamelCase__				) < 2:
														return dirty

							for i in range(len(UpperCamelCase__				) - 1				):
														clean += dirty[i]

														if dirty[i] == dirty[i + 1]:
																					clean += "X"

							clean += dirty[-1]

							if len(UpperCamelCase__				) & 1:
														clean += "X"

							return clean







def 		_A(       UpperCamelCase__							:			str				)    -> list[str]:
							'''simple docstring'''


							__lowercase      =    '''ABCDEFGHIKLMNOPQRSTUVWXYZ'''
							# we're using a list instead of a '2d' array because it makes the math
							# for setting up the table and doing the actual encoding/decoding simpler
							__lowercase      =    []

							# copy key chars into the table if they are in `alphabet` ignoring duplicates
							for char in key.upper():
														if char not in table and char in alphabet:
																					table.append(UpperCamelCase__				)

    # fill the rest of the table in with the remaining alphabet chars
							for char in alphabet:
														if char not in table:
																					table.append(UpperCamelCase__				)

							return table







def 		_A(       UpperCamelCase__							:			str				,       UpperCamelCase__							:			str				)    -> str:
							'''simple docstring'''


							__lowercase      =    generate_table(UpperCamelCase__				)
							__lowercase      =    prepare_input(UpperCamelCase__				)
							__lowercase      =    ''''''

							# https://en.wikipedia.org/wiki/Playfair_cipher#Description
							for chara, chara in chunker(UpperCamelCase__				,       2				):
														__lowercase     ,     __lowercase      =    divmod(table.index(UpperCamelCase__				)				,       5				)
														__lowercase     ,     __lowercase      =    divmod(table.index(UpperCamelCase__				)				,       5				)

														if rowa == rowa:
																					ciphertext += table[rowa * 5 + (cola + 1) % 5]
																					ciphertext += table[rowa * 5 + (cola + 1) % 5]
														elif cola == cola:
																					ciphertext += table[((rowa + 1) % 5) * 5 + cola]
																					ciphertext += table[((rowa + 1) % 5) * 5 + cola]
														else:  # rectangle
																					ciphertext += table[rowa * 5 + cola]
																					ciphertext += table[rowa * 5 + cola]

							return ciphertext







def 		_A(       UpperCamelCase__							:			str				,       UpperCamelCase__							:			str				)    -> str:
							'''simple docstring'''


							__lowercase      =    generate_table(UpperCamelCase__				)
							__lowercase      =    ''''''

							# https://en.wikipedia.org/wiki/Playfair_cipher#Description
							for chara, chara in chunker(UpperCamelCase__				,       2				):
														__lowercase     ,     __lowercase      =    divmod(table.index(UpperCamelCase__				)				,       5				)
														__lowercase     ,     __lowercase      =    divmod(table.index(UpperCamelCase__				)				,       5				)

														if rowa == rowa:
																					plaintext += table[rowa * 5 + (cola - 1) % 5]
																					plaintext += table[rowa * 5 + (cola - 1) % 5]
														elif cola == cola:
																					plaintext += table[((rowa - 1) % 5) * 5 + cola]
																					plaintext += table[((rowa - 1) % 5) * 5 + cola]
														else:  # rectangle
																					plaintext += table[rowa * 5 + cola]
																					plaintext += table[rowa * 5 + cola]

							return plaintext






