



import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


__snake_case    :		int  =get_logger(__name__)



class 	lowerCamelCase__      :




		'''simple docstring'''



		snake_case_     ="""dummy_data"""
		snake_case_     ="""datasets"""
		snake_case_     =False



		def __init__(self		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase = None		,__lowerCamelCase = False		,__lowerCamelCase = True		,__lowerCamelCase = None		,)					->      List[Any]:

						"""simple docstring"""






						lowerCAmelCase__					:    str												=					0
						lowerCAmelCase__					:    Union[str, Any]												=					dataset_name
						lowerCAmelCase__					:    List[Any]												=					cache_dir
						lowerCAmelCase__					:    str												=					use_local_dummy_data
						lowerCAmelCase__					:    List[Any]												=					config
						# download_callbacks take a single url as input
						lowerCAmelCase__					:    List[Callable]												=					download_callbacks or []
						# if False, it doesn't load existing files and it returns the paths of the dummy files relative
						# to the dummy_data zip file root
						lowerCAmelCase__					:    List[Any]												=					load_existing_dummy_data

						# TODO(PVP, QL) might need to make this more general
						lowerCAmelCase__					:    Optional[Any]												=					str(__lowerCamelCase			)
						# to be downloaded
						lowerCAmelCase__					:    Optional[int]												=					None
						lowerCAmelCase__					:    Any												=					None



		@property
		def 		lowerCAmelCase__				(self			)					->      Optional[int]:

						"""simple docstring"""






						if self._dummy_file is None:
										lowerCAmelCase__					:    List[str]												=					self.download_dummy_data()
						return self._dummy_file



		@property
		def 		lowerCAmelCase__				(self			)					->      Optional[int]:

						"""simple docstring"""






						if self.config is not None:
										# structure is dummy / config_name / version_name
										return os.path.join('''dummy'''		,self.config.name		,self.version_name			)
						# structure is dummy / version_name
						return os.path.join('''dummy'''		,self.version_name			)



		@property
		def 		lowerCAmelCase__				(self			)					->      List[str]:

						"""simple docstring"""






						return os.path.join(self.dummy_data_folder		,'''dummy_data.zip'''			)



		def 		lowerCAmelCase__				(self			)					->      Dict:

						"""simple docstring"""






						lowerCAmelCase__					:    Optional[Any]												=					(
						    self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
						)

						lowerCAmelCase__					:    int												=					cached_path(
						    __lowerCamelCase		,cache_dir=self.cache_dir		,extract_compressed_file=__lowerCamelCase		,force_extract=__lowerCamelCase			)

						return os.path.join(__lowerCamelCase		,self.dummy_file_name			)



		@property
		def 		lowerCAmelCase__				(self			)					->      Union[str, Any]:

						"""simple docstring"""






						return os.path.join(self.datasets_scripts_dir		,self.dataset_name		,self.dummy_zip_file			)



		@property
		def 		lowerCAmelCase__				(self			)					->      int:

						"""simple docstring"""






						if self._bucket_url is None:
										lowerCAmelCase__					:    Tuple												=					hf_github_url(self.dataset_name		,self.dummy_zip_file.replace(os.sep		,'''/'''			)			)
						return self._bucket_url



		@property
		def 		lowerCAmelCase__				(self			)					->      Any:

						"""simple docstring"""






						if os.path.isdir(self.dummy_file			):
										return self.dummy_file
						# else cut off path to file -> example `xsum`.
						return "/".join(self.dummy_file.replace(os.sep		,'''/'''			).split('''/'''			)[:-1]			)



		def 		lowerCAmelCase__				(self		,__lowerCamelCase		,*__lowerCamelCase			)					->      Any:

						"""simple docstring"""






						if self.load_existing_dummy_data:
										# dummy data is downloaded and tested
										lowerCAmelCase__					:    int												=					self.dummy_file
						else:
										# dummy data cannot be downloaded and only the path to dummy file is returned
										lowerCAmelCase__					:    List[str]												=					self.dummy_file_name

						# special case when data_url is a dict
						if isinstance(__lowerCamelCase		,__lowerCamelCase			):
										return self.create_dummy_data_dict(__lowerCamelCase		,__lowerCamelCase			)
						elif isinstance(__lowerCamelCase		,(list, tuple)			):
										return self.create_dummy_data_list(__lowerCamelCase		,__lowerCamelCase			)
						else:
										return self.create_dummy_data_single(__lowerCamelCase		,__lowerCamelCase			)



		def 		lowerCAmelCase__				(self		,__lowerCamelCase		,*__lowerCamelCase			)					->      Optional[int]:

						"""simple docstring"""






						return self.download_and_extract(__lowerCamelCase			)



		def 		lowerCAmelCase__				(self		,__lowerCamelCase		,__lowerCamelCase			)					->      Dict:

						"""simple docstring"""






						return self.download_and_extract(__lowerCamelCase			)



		def 		lowerCAmelCase__				(self		,__lowerCamelCase		,*__lowerCamelCase		,**__lowerCamelCase			)					->      Dict:

						"""simple docstring"""






						return path



		def 		lowerCAmelCase__				(self			)					->      int:

						"""simple docstring"""






						return {}



		def 		lowerCAmelCase__				(self		,__lowerCamelCase		,__lowerCamelCase			)					->      Tuple:

						"""simple docstring"""






						lowerCAmelCase__					:    List[str]												=					{}
						for key, single_urls in data_url.items():
										for download_callback in self.download_callbacks:
														if isinstance(__lowerCamelCase		,__lowerCamelCase			):
																		for single_url in single_urls:
																						download_callback(__lowerCamelCase			)
														else:
																		lowerCAmelCase__					:    Dict												=					single_urls
																		download_callback(__lowerCamelCase			)
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
										if isinstance(__lowerCamelCase		,__lowerCamelCase			):
														lowerCAmelCase__					:    Optional[Any]												=					[os.path.join(__lowerCamelCase		,urllib.parse.quote_plus(Path(__lowerCamelCase			).name			)			) for x in single_urls]
										else:
														lowerCAmelCase__					:    Tuple												=					single_urls
														lowerCAmelCase__					:    Dict												=					os.path.join(__lowerCamelCase		,urllib.parse.quote_plus(Path(__lowerCamelCase			).name			)			)
										lowerCAmelCase__					:    List[Any]												=					value

						# make sure that values are unique
						if all(isinstance(__lowerCamelCase		,__lowerCamelCase			) for i in dummy_data_dict.values()			) and len(set(dummy_data_dict.values()			)			) < len(
						    dummy_data_dict.values()			):
										# append key to value to make its name unique
										lowerCAmelCase__					:    Dict												=					{key: value + key for key, value in dummy_data_dict.items()}

						return dummy_data_dict



		def 		lowerCAmelCase__				(self		,__lowerCamelCase		,__lowerCamelCase			)					->      Tuple:

						"""simple docstring"""






						lowerCAmelCase__					:    int												=					[]
						# trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
						lowerCAmelCase__					:    str												=					all(bool(re.findall('''[0-9]{3,}-of-[0-9]{3,}'''		,__lowerCamelCase			)			) for url in data_url			)
						lowerCAmelCase__					:    str												=					all(
						    url.startswith('''https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed'''			) for url in data_url			)
						if data_url and (is_tf_records or is_pubmed_records):
										lowerCAmelCase__					:    Optional[Any]												=					[data_url[0]] * len(__lowerCamelCase			)
						for single_url in data_url:
										for download_callback in self.download_callbacks:
														download_callback(__lowerCamelCase			)
										# we force the name of each key to be the last file / folder name of the url path
										# if the url has arguments, we need to encode them with urllib.parse.quote_plus
										lowerCAmelCase__					:    Dict												=					os.path.join(__lowerCamelCase		,urllib.parse.quote_plus(single_url.split('''/'''			)[-1]			)			)
										dummy_data_list.append(__lowerCamelCase			)
						return dummy_data_list



		def 		lowerCAmelCase__				(self		,__lowerCamelCase		,__lowerCamelCase			)					->      Optional[Any]:

						"""simple docstring"""






						for download_callback in self.download_callbacks:
										download_callback(__lowerCamelCase			)
						# we force the name of each key to be the last file / folder name of the url path
						# if the url has arguments, we need to encode them with urllib.parse.quote_plus
						lowerCAmelCase__					:    Dict												=					os.path.join(__lowerCamelCase		,urllib.parse.quote_plus(data_url.split('''/'''			)[-1]			)			)
						if os.path.exists(__lowerCamelCase			) or not self.load_existing_dummy_data:
										return value
						else:
										# Backward compatibility, maybe deprecate at one point.
										# For many datasets with single url calls to dl_manager.download_and_extract,
										# the dummy_data.zip file is actually the zipped downloaded file
										# while now we expected the dummy_data.zip file to be a directory containing
										# the downloaded file.
										return path_to_dummy_data



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

						"""simple docstring"""






						pass



		def 		lowerCAmelCase__				(self			)					->      int:

						"""simple docstring"""






						pass



		def 		lowerCAmelCase__				(self		,__lowerCamelCase			)					->      List[str]:

						"""simple docstring"""






						def _iter_archive_members(__lowerCamelCase			):
										# this preserves the order of the members inside the ZIP archive
										lowerCAmelCase__					:    List[Any]												=					Path(self.dummy_file			).parent
										lowerCAmelCase__					:    Tuple												=					path.relative_to(__lowerCamelCase			)
										with ZipFile(self.local_path_to_dummy_data			) as zip_file:
														lowerCAmelCase__					:    Union[str, Any]												=					zip_file.namelist()
										for member in members:
														if member.startswith(relative_path.as_posix()			):
																		yield dummy_parent_path.joinpath(__lowerCamelCase			)

						lowerCAmelCase__					:    Any												=					Path(__lowerCamelCase			)
						lowerCAmelCase__					:    Optional[int]												=					_iter_archive_members(__lowerCamelCase			) if self.use_local_dummy_data else path.rglob('''*'''			)
						for file_path in file_paths:
										if file_path.is_file() and not file_path.name.startswith(('''.''', '''__''')			):
														yield file_path.relative_to(__lowerCamelCase			).as_posix(), file_path.open('''rb'''			)



		def 		lowerCAmelCase__				(self		,__lowerCamelCase			)					->      List[Any]:

						"""simple docstring"""






						if not isinstance(__lowerCamelCase		,__lowerCamelCase			):
										lowerCAmelCase__					:    List[Any]												=					[paths]
						for path in paths:
										if os.path.isfile(__lowerCamelCase			):
														if os.path.basename(__lowerCamelCase			).startswith(('''.''', '''__''')			):
																		return
														yield path
										else:
														for dirpath, dirnames, filenames in os.walk(__lowerCamelCase			):
																		if os.path.basename(__lowerCamelCase			).startswith(('''.''', '''__''')			):
																						continue
																		dirnames.sort()
																		for filename in sorted(__lowerCamelCase			):
																						if filename.startswith(('''.''', '''__''')			):
																										continue
																						yield os.path.join(__lowerCamelCase		,__lowerCamelCase			)






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      lowerCAmelCase__		(   lowerCamelCase_		:		int	,lowerCamelCase_		:		Optional[Any]	,lowerCamelCase_		:		Optional[int]	,lowerCamelCase_		:		Optional[int]	,lowerCamelCase_		:		Any=True	,lowerCamelCase_		:		Tuple="pt"):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		Optional[int]	,lowerCamelCase_		:		Dict	,lowerCamelCase_		:		Any=None	,):





				'''simple docstring'''

				lowerCAmelCase__					:    List[Any]												=					input_ids.ne(lowerCamelCase_).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 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		def __init__(self		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase="train"		,__lowerCamelCase=None		,__lowerCamelCase=None		,__lowerCamelCase=None		,__lowerCamelCase=""		,)					->      List[str]:

						"""simple docstring"""






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



		def __len__(self			)					->      str:

						"""simple docstring"""






						return len(self.src_lens			)



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

						"""simple docstring"""






						lowerCAmelCase__					:    List[Any]												=					index + 1  # linecache starts at 1
						lowerCAmelCase__					:    Any												=					self.prefix + linecache.getline(str(self.src_file			)		,__lowerCamelCase			).rstrip('''\n'''			)
						lowerCAmelCase__					:    Any												=					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
						lowerCAmelCase__					:    List[str]												=					(
						    self.tokenizer.question_encoder if isinstance(self.tokenizer		,__lowerCamelCase			) else self.tokenizer
						)
						lowerCAmelCase__					:    Dict												=					self.tokenizer.generator if isinstance(self.tokenizer		,__lowerCamelCase			) else self.tokenizer

						lowerCAmelCase__					:    Union[str, Any]												=					encode_line(__lowerCamelCase		,__lowerCamelCase		,self.max_source_length		,'''right'''			)
						lowerCAmelCase__					:    Any												=					encode_line(__lowerCamelCase		,__lowerCamelCase		,self.max_target_length		,'''right'''			)

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



		@staticmethod
		def 		lowerCAmelCase__				(__lowerCamelCase			)					->      List[str]:

						"""simple docstring"""






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



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

						"""simple docstring"""






						lowerCAmelCase__					:    Union[str, Any]												=					torch.stack([x['''input_ids'''] for x in batch]			)
						lowerCAmelCase__					:    Union[str, Any]												=					torch.stack([x['''attention_mask'''] for x in batch]			)
						lowerCAmelCase__					:    List[Any]												=					torch.stack([x['''decoder_input_ids'''] for x in batch]			)
						lowerCAmelCase__					:    Any												=					(
						    self.tokenizer.generator.pad_token_id
						    if isinstance(self.tokenizer		,__lowerCamelCase			)
						    else self.tokenizer.pad_token_id
						)
						lowerCAmelCase__					:    Tuple												=					(
						    self.tokenizer.question_encoder.pad_token_id
						    if isinstance(self.tokenizer		,__lowerCamelCase			)
						    else self.tokenizer.pad_token_id
						)
						lowerCAmelCase__					:    Dict												=					trim_batch(__lowerCamelCase		,__lowerCamelCase			)
						lowerCAmelCase__						,		lowerCAmelCase__					:    Union[str, Any]												=					trim_batch(__lowerCamelCase		,__lowerCamelCase		,attention_mask=__lowerCamelCase			)
						lowerCAmelCase__					:    Union[str, Any]												=					{
						    '''input_ids''': source_ids,
						    '''attention_mask''': source_mask,
						    '''decoder_input_ids''': y,
						}
						return batch


__snake_case    :		Any  =getLogger(__name__)






def      lowerCAmelCase__		(   lowerCamelCase_		:		List[List]):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		str):





				'''simple docstring'''

				lowerCAmelCase__					:    int												=					get_git_info()
				save_json(lowerCamelCase_	,os.path.join(lowerCamelCase_	,'''git_log.json'''))






def      lowerCAmelCase__		(   lowerCamelCase_		:		Tuple	,lowerCamelCase_		:		Union[str, Any]	,lowerCamelCase_		:		Tuple=4	,**lowerCamelCase_		:		List[str]):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		Tuple):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   ):





				'''simple docstring'''

				lowerCAmelCase__					:    str												=					git.Repo(search_parent_directories=lowerCamelCase_)
				lowerCAmelCase__					:    List[Any]												=					{
				    '''repo_id''': str(lowerCamelCase_),
				    '''repo_sha''': str(repo.head.object.hexsha),
				    '''repo_branch''': str(repo.active_branch),
				    '''hostname''': str(socket.gethostname()),
				}
				return repo_infos






def      lowerCAmelCase__		(   lowerCamelCase_		:		Callable	,lowerCamelCase_		:		Iterable):





				'''simple docstring'''

				return list(map(lowerCamelCase_	,lowerCamelCase_))






def      lowerCAmelCase__		(   lowerCamelCase_		:		Any	,lowerCamelCase_		:		Optional[Any]):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		int):





				'''simple docstring'''

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

				def white_space_fix(lowerCamelCase_		:		Optional[int]):
								return " ".join(text.split())

				def remove_punc(lowerCamelCase_		:		List[str]):
								lowerCAmelCase__					:    List[Any]												=					set(string.punctuation)
								return "".join(ch for ch in text if ch not in exclude)

				def lower(lowerCamelCase_		:		Optional[int]):
								return text.lower()

				return white_space_fix(remove_articles(remove_punc(lower(lowerCamelCase_))))






def      lowerCAmelCase__		(   lowerCamelCase_		:		List[Any]	,lowerCamelCase_		:		Optional[int]):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		Union[str, Any]	,lowerCamelCase_		:		Any):





				'''simple docstring'''

				return normalize_answer(lowerCamelCase_) == normalize_answer(lowerCamelCase_)






def      lowerCAmelCase__		(   lowerCamelCase_		:		List[str]	,lowerCamelCase_		:		List[str]):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		int):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		List[str]	,lowerCamelCase_		:		Dict	,lowerCamelCase_		:		str):





				'''simple docstring'''

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

