





"""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     __A      (			a_   ,       a_   ,       a_   ,       a_   ,       a_=True   ,       a_="pt")		->		Any:
				__a :						int			       =  {'''add_prefix_space''': True} if isinstance(a_   ,       a_) and not line.startswith(''' ''') else {}
				__a :						str			       =  padding_side
				return tokenizer(
				    [line]   ,       max_length=a_   ,       padding='''max_length''' if pad_to_max_length else None   ,       truncation=a_   ,       return_tensors=a_   ,       add_special_tokens=a_   ,       **a_   ,       )

def     __A      (			a_   ,       a_   ,       a_=None   ,       )		->		Tuple:
				__a :						Tuple			       =  input_ids.ne(a_).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 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




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







					def __len__(						self     ):
									return len(self.src_lens     )







					def __getitem__(						self	,			_UpperCAmelCase     ):
									__a :						Optional[int]			       =  index + 1  # linecache starts at 1
									__a :						Optional[int]			       =  self.prefix + linecache.getline(str(self.src_file     )	,			_UpperCAmelCase     ).rstrip('''\n'''     )
									__a :						str			       =  linecache.getline(str(self.tgt_file     )	,			_UpperCAmelCase     ).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	,			_UpperCAmelCase     ):
													source_line += self.tokenizer.eos_token
													tgt_line += self.tokenizer.eos_token

									# Pad source and target to the right
									__a :						List[Any]			       =  (
									    self.tokenizer.question_encoder if isinstance(self.tokenizer	,			_UpperCAmelCase     ) else self.tokenizer
									)
									__a :						List[str]			       =  self.tokenizer.generator if isinstance(self.tokenizer	,			_UpperCAmelCase     ) else self.tokenizer

									__a :						Tuple			       =  encode_line(_UpperCAmelCase	,			_UpperCAmelCase	,			self.max_source_length	,			'''right'''     )
									__a :						int			       =  encode_line(_UpperCAmelCase	,			_UpperCAmelCase	,			self.max_target_length	,			'''right'''     )

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







					@staticmethod
					def  _lowerCamelCase		(						_UpperCAmelCase     ):
									return [len(_UpperCAmelCase     ) for x in Path(_UpperCAmelCase     ).open().readlines()]







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase     ):
									__a :						List[str]			       =  torch.stack([x['''input_ids'''] for x in batch]     )
									__a :						Any			       =  torch.stack([x['''attention_mask'''] for x in batch]     )
									__a :						Optional[int]			       =  torch.stack([x['''decoder_input_ids'''] for x in batch]     )
									__a :						List[Any]			       =  (
									    self.tokenizer.generator.pad_token_id
									    if isinstance(self.tokenizer	,			_UpperCAmelCase     )
									    else self.tokenizer.pad_token_id
									)
									__a :						str			       =  (
									    self.tokenizer.question_encoder.pad_token_id
									    if isinstance(self.tokenizer	,			_UpperCAmelCase     )
									    else self.tokenizer.pad_token_id
									)
									__a :						Dict			       =  trim_batch(_UpperCAmelCase	,			_UpperCAmelCase     )
									__a :						Dict			       =  trim_batch(_UpperCAmelCase	,			_UpperCAmelCase	,			attention_mask=_UpperCAmelCase     )
									__a :						Optional[Any]			       =  {
									    '''input_ids''': source_ids,
									    '''attention_mask''': source_mask,
									    '''decoder_input_ids''': y,
									}
									return batch






A 			=  getLogger(__name__)

def     __A      (			a_)		->		Tuple:
				return list(itertools.chain.from_iterable(a_))

def     __A      (			a_)		->		None:
				__a :						Any			       =  get_git_info()
				save_json(a_   ,       os.path.join(a_   ,       '''git_log.json'''))

def     __A      (			a_   ,       a_   ,       a_=4   ,       **a_)		->		Union[str, Any]:
				with open(a_   ,       '''w''') as f:
								json.dump(a_   ,       a_   ,       indent=a_   ,       **a_)

def     __A      (			a_)		->		str:
				with open(a_) as f:
								return json.load(a_)

def     __A      (			)		->		Optional[Any]:
				__a :						Dict			       =  git.Repo(search_parent_directories=a_)
				__a :						Optional[Any]			       =  {
				    '''repo_id''': str(a_),
				    '''repo_sha''': str(repo.head.object.hexsha),
				    '''repo_branch''': str(repo.active_branch),
				    '''hostname''': str(socket.gethostname()),
				}
				return repo_infos

def     __A      (			a_   ,       a_)		->		List:
				return list(map(a_   ,       a_))

def     __A      (			a_   ,       a_)		->		Any:
				with open(a_   ,       '''wb''') as f:
								return pickle.dump(a_   ,       a_)

def     __A      (			a_)		->		int:

				def remove_articles(a_):
								return re.sub(R'''\b(a|an|the)\b'''   ,       ''' '''   ,       a_)

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

				def remove_punc(a_):
								__a :						Dict			       =  set(string.punctuation)
								return "".join(ch for ch in text if ch not in exclude)

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

				return white_space_fix(remove_articles(remove_punc(lower(a_))))

def     __A      (			a_   ,       a_)		->		Any:
				__a :						Any			       =  normalize_answer(a_).split()
				__a :						str			       =  normalize_answer(a_).split()
				__a :						Optional[Any]			       =  Counter(a_) & Counter(a_)
				__a :						int			       =  sum(common.values())
				if num_same == 0:
								return 0
				__a :						str			       =  1.0 * num_same / len(a_)
				__a :						Any			       =  1.0 * num_same / len(a_)
				__a :						List[str]			       =  (2 * precision * recall) / (precision + recall)
				return fa

def     __A      (			a_   ,       a_)		->		Tuple:
				return normalize_answer(a_) == normalize_answer(a_)

def     __A      (			a_   ,       a_)		->		Dict:
				assert len(a_) == len(a_)
				__a :						Dict			       =  0
				for hypo, pred in zip(a_   ,       a_):
								em += exact_match_score(a_   ,       a_)
				if len(a_) > 0:
								em /= len(a_)
				return {"em": em}

def     __A      (			a_)		->		Dict:
				return model_prefix.startswith('''rag''')






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






"""simple docstring"""






# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
A 			=  abspath(join(dirname(dirname(dirname(__file__))), '''src'''))
sys.path.insert(1, git_repo_path)


# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='''ignore''', category=FutureWarning)

def     __A      (			a_						:Tuple)		->		Dict:
				from transformers.testing_utils import pytest_addoption_shared

				pytest_addoption_shared(a_)






def     __A      (			a_						:Any)		->		int:
				from transformers.testing_utils import pytest_terminal_summary_main

				__a :						str			       =  terminalreporter.config.getoption('''--make-reports''')
				if make_reports:
								pytest_terminal_summary_main(a_   ,       id=a_)