





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  __magic_name__  (				lowercase				,       lowercase				,       lowercase				,       lowercase				,       lowercase=True				,       lowercase="pt"				)				-> Optional[int]:

							"""simple docstring"""



							lowercase_	:   Tuple  				=     {"""add_prefix_space""": True} if isinstance(lowercase				,       lowercase				) and not line.startswith(""" """				) else {}
							lowercase_	:   Union[str, Any]  				=     padding_side
							return tokenizer(
							    [line]				,       max_length=lowercase				,       padding="""max_length""" if pad_to_max_length else None				,       truncation=lowercase				,       return_tensors=lowercase				,       add_special_tokens=lowercase				,       **lowercase				,       )





def  __magic_name__  (				lowercase				,       lowercase				,       lowercase=None				,       )				-> str:

							"""simple docstring"""



							lowercase_	:   Dict  				=     input_ids.ne(lowercase				).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__					(     lowerCamelCase__				):






		'''simple docstring'''






		def __init__(							self,   snake_case__,   snake_case__,   snake_case__,   snake_case__,   snake_case__="train",   snake_case__=None,   snake_case__=None,   snake_case__=None,   snake_case__="",   )       -> Dict:






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






		def __len__(							self  )       -> List[Any]:






									"""simple docstring"""
									return len(self.src_lens  )






		def __getitem__(							self,   snake_case__  )       -> Dict[str, torch.Tensor]:






									"""simple docstring"""
									lowercase_	:   Tuple  				=     index + 1  # linecache starts at 1
									lowercase_	:   Optional[Any]  				=     self.prefix + linecache.getline(str(self.src_file  ),   snake_case__  ).rstrip("""\n"""  )
									lowercase_	:   int  				=     linecache.getline(str(self.tgt_file  ),   snake_case__  ).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,   snake_case__  ):
																source_line += self.tokenizer.eos_token
																tgt_line += self.tokenizer.eos_token

									# Pad source and target to the right
									lowercase_	:   Optional[int]  				=     (
									    self.tokenizer.question_encoder if isinstance(self.tokenizer,   snake_case__  ) else self.tokenizer
									)
									lowercase_	:   str  				=     self.tokenizer.generator if isinstance(self.tokenizer,   snake_case__  ) else self.tokenizer

									lowercase_	:   Optional[int]  				=     encode_line(snake_case__,   snake_case__,   self.max_source_length,   """right"""  )
									lowercase_	:   Optional[Any]  				=     encode_line(snake_case__,   snake_case__,   self.max_target_length,   """right"""  )

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






		@staticmethod
		def 						snake_case__				(							snake_case__  )       -> int:






									"""simple docstring"""
									return [len(snake_case__  ) for x in Path(snake_case__  ).open().readlines()]






		def 						snake_case__				(							self,   snake_case__  )       -> Dict[str, torch.Tensor]:






									"""simple docstring"""
									lowercase_	:   Optional[int]  				=     torch.stack([x["""input_ids"""] for x in batch]  )
									lowercase_	:   Union[str, Any]  				=     torch.stack([x["""attention_mask"""] for x in batch]  )
									lowercase_	:   List[str]  				=     torch.stack([x["""decoder_input_ids"""] for x in batch]  )
									lowercase_	:   Any  				=     (
									    self.tokenizer.generator.pad_token_id
									    if isinstance(self.tokenizer,   snake_case__  )
									    else self.tokenizer.pad_token_id
									)
									lowercase_	:   Any  				=     (
									    self.tokenizer.question_encoder.pad_token_id
									    if isinstance(self.tokenizer,   snake_case__  )
									    else self.tokenizer.pad_token_id
									)
									lowercase_	:   Tuple  				=     trim_batch(snake_case__,   snake_case__  )
									lowercase_				,		lowercase_	:   List[str]  				=     trim_batch(snake_case__,   snake_case__,   attention_mask=snake_case__  )
									lowercase_	:   Optional[Any]  				=     {
									    """input_ids""": source_ids,
									    """attention_mask""": source_mask,
									    """decoder_input_ids""": y,
									}
									return batch




UpperCAmelCase_							=				getLogger(__name__)





def  __magic_name__  (				lowercase				)				-> List[str]:

							"""simple docstring"""



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





def  __magic_name__  (				lowercase				)				-> None:

							"""simple docstring"""



							lowercase_	:   Optional[Any]  				=     get_git_info()
							save_json(lowercase				,       os.path.join(lowercase				,       """git_log.json"""				)				)





def  __magic_name__  (				lowercase				,       lowercase				,       lowercase=4				,       **lowercase				)				-> str:

							"""simple docstring"""



							with open(lowercase				,       """w"""				) as f:
														json.dump(lowercase				,       lowercase				,       indent=lowercase				,       **lowercase				)





def  __magic_name__  (				lowercase				)				-> List[str]:

							"""simple docstring"""



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





def  __magic_name__  (				)				-> Union[str, Any]:

							"""simple docstring"""



							lowercase_	:   str  				=     git.Repo(search_parent_directories=lowercase				)
							lowercase_	:   Any  				=     {
							    """repo_id""": str(lowercase				),
							    """repo_sha""": str(repo.head.object.hexsha				),
							    """repo_branch""": str(repo.active_branch				),
							    """hostname""": str(socket.gethostname()				),
							}
							return repo_infos





def  __magic_name__  (				lowercase				,       lowercase				)				-> List:

							"""simple docstring"""



							return list(map(lowercase				,       lowercase				)				)





def  __magic_name__  (				lowercase				,       lowercase				)				-> Any:

							"""simple docstring"""



							with open(lowercase				,       """wb"""				) as f:
														return pickle.dump(lowercase				,       lowercase				)





def  __magic_name__  (				lowercase				)				-> int:

							"""simple docstring"""



							def remove_articles(lowercase				):
														return re.sub(r"""\b(a|an|the)\b"""				,       """ """				,       lowercase				)

							def white_space_fix(lowercase				):
														return " ".join(text.split()				)

							def remove_punc(lowercase				):
														lowercase_	:   int  				=     set(string.punctuation				)
														return "".join(ch for ch in text if ch not in exclude				)

							def lower(lowercase				):
														return text.lower()

							return white_space_fix(remove_articles(remove_punc(lower(lowercase				)				)				)				)





def  __magic_name__  (				lowercase				,       lowercase				)				-> List[Any]:

							"""simple docstring"""



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





def  __magic_name__  (				lowercase				,       lowercase				)				-> Dict:

							"""simple docstring"""



							return normalize_answer(lowercase				) == normalize_answer(lowercase				)





def  __magic_name__  (				lowercase				,       lowercase				)				-> Dict:

							"""simple docstring"""



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





def  __magic_name__  (				lowercase				)				-> str:

							"""simple docstring"""



							return model_prefix.startswith("""rag"""				)





def  __magic_name__  (				lowercase				,       lowercase				,       lowercase				)				-> Optional[int]:

							"""simple docstring"""



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






import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline





@pytest.mark.integration
def  __magic_name__  (				)				-> Union[str, Any]:

							"""simple docstring"""



							with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT				):
														with pytest.raises(lowercase				):
																					requests.request("""GET"""				,       """https://huggingface.co"""				)
														with pytest.raises(requests.exceptions.ConnectTimeout				):
																					requests.request("""GET"""				,       """https://huggingface.co"""				,       timeout=1.0				)





@pytest.mark.integration
def  __magic_name__  (				)				-> Union[str, Any]:

							"""simple docstring"""



							with offline(OfflineSimulationMode.CONNECTION_FAILS				):
														with pytest.raises(requests.exceptions.ConnectionError				):
																					requests.request("""GET"""				,       """https://huggingface.co"""				)





def  __magic_name__  (				)				-> Dict:

							"""simple docstring"""



							with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1				):
														with pytest.raises(lowercase				):
																					http_head("""https://huggingface.co"""				)