





"""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      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE=True							,     SCREAMING_SNAKE_CASE="pt"     ):
						UpperCamelCase				:		Any				   =			{"""add_prefix_space""": True} if isinstance(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ) and not line.startswith(""" """     ) else {}
						UpperCamelCase				:		Dict				   =			padding_side
						return tokenizer(
						    [line]							,     max_length=SCREAMING_SNAKE_CASE							,     padding="""max_length""" if pad_to_max_length else None							,     truncation=SCREAMING_SNAKE_CASE							,     return_tensors=SCREAMING_SNAKE_CASE							,     add_special_tokens=SCREAMING_SNAKE_CASE							,     **SCREAMING_SNAKE_CASE							,     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE=None							,     ):
						UpperCamelCase				:		Any				   =			input_ids.ne(SCREAMING_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 							lowercase__			(   __SCREAMING_SNAKE_CASE	):

			"""simple docstring"""







			def __init__(      self						,   _A						,   _A						,   _A						,   _A						,   _A="train"						,   _A=None						,   _A=None						,   _A=None						,   _A=""						,   ):






									'''simple docstring'''







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







			def __len__(      self    ):






									'''simple docstring'''







									return len(self.src_lens    )







			def __getitem__(      self						,   _A    ):






									'''simple docstring'''







									UpperCamelCase				:		Any				   =			index + 1  # linecache starts at 1
									UpperCamelCase				:		List[Any]				   =			self.prefix + linecache.getline(str(self.src_file    )						,   _A    ).rstrip("""\n"""    )
									UpperCamelCase				:		List[str]				   =			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
									UpperCamelCase				:		List[str]				   =			(
									    self.tokenizer.question_encoder if isinstance(self.tokenizer						,   _A    ) else self.tokenizer
									)
									UpperCamelCase				:		Tuple				   =			self.tokenizer.generator if isinstance(self.tokenizer						,   _A    ) else self.tokenizer

									UpperCamelCase				:		str				   =			encode_line(_A						,   _A						,   self.max_source_length						,   """right"""    )
									UpperCamelCase				:		List[Any]				   =			encode_line(_A						,   _A						,   self.max_target_length						,   """right"""    )

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







			@staticmethod
			def   _a      (      _A    ):






									'''simple docstring'''







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







			def   _a      (      self						,   _A    ):






									'''simple docstring'''







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


__magic_name__       :					Tuple						=			getLogger(__name__)

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						return list(itertools.chain.from_iterable(SCREAMING_SNAKE_CASE     )     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		List[Any]				   =			get_git_info()
						save_json(SCREAMING_SNAKE_CASE							,     os.path.join(SCREAMING_SNAKE_CASE							,     """git_log.json"""     )     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE=4							,     **SCREAMING_SNAKE_CASE     ):
						with open(SCREAMING_SNAKE_CASE							,     """w"""     ) as f:
												json.dump(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     indent=SCREAMING_SNAKE_CASE							,     **SCREAMING_SNAKE_CASE     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						with open(SCREAMING_SNAKE_CASE     ) as f:
												return json.load(SCREAMING_SNAKE_CASE     )

def      UpperCamelCase							():
						UpperCamelCase				:		Optional[int]				   =			git.Repo(search_parent_directories=SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		List[Any]				   =			{
						    """repo_id""": str(SCREAMING_SNAKE_CASE     ),
						    """repo_sha""": str(repo.head.object.hexsha     ),
						    """repo_branch""": str(repo.active_branch     ),
						    """hostname""": str(socket.gethostname()     ),
						}
						return repo_infos

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						return list(map(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						with open(SCREAMING_SNAKE_CASE							,     """wb"""     ) as f:
												return pickle.dump(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):

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

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

						def remove_punc(SCREAMING_SNAKE_CASE     ):
												UpperCamelCase				:		Union[str, Any]				   =			set(string.punctuation     )
												return "".join(ch for ch in text if ch not in exclude     )

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

						return white_space_fix(remove_articles(remove_punc(lower(SCREAMING_SNAKE_CASE     )     )     )     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		str				   =			normalize_answer(SCREAMING_SNAKE_CASE     ).split()
						UpperCamelCase				:		Optional[int]				   =			normalize_answer(SCREAMING_SNAKE_CASE     ).split()
						UpperCamelCase				:		int				   =			Counter(SCREAMING_SNAKE_CASE     ) & Counter(SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		str				   =			sum(common.values()     )
						if num_same == 0:
												return 0
						UpperCamelCase				:		Tuple				   =			1.0 * num_same / len(SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		Any				   =			1.0 * num_same / len(SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		Optional[int]				   =			(2 * precision * recall) / (precision + recall)
						return fa

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						return normalize_answer(SCREAMING_SNAKE_CASE     ) == normalize_answer(SCREAMING_SNAKE_CASE     )

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						assert len(SCREAMING_SNAKE_CASE     ) == len(SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		Tuple				   =			0
						for hypo, pred in zip(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
												em += exact_match_score(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						if len(SCREAMING_SNAKE_CASE     ) > 0:
												em /= len(SCREAMING_SNAKE_CASE     )
						return {"em": em}

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						return model_prefix.startswith("""rag"""     )

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










"""simple docstring"""


def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		int				   =			0

						# if input_string is "aba" than new_input_string become "a|b|a"
						UpperCamelCase				:		str				   =			""""""
						UpperCamelCase				:		Dict				   =			""""""

						# append each character + "|" in new_string for range(0, length-1)
						for i in input_string[: len(SCREAMING_SNAKE_CASE     ) - 1]:
												new_input_string += i + "|"
						# append last character
						new_input_string += input_string[-1]

						# we will store the starting and ending of previous furthest ending palindromic
						# substring
						UpperCamelCase   ,						UpperCamelCase				:		int				   =			0, 0

						# length[i] shows the length of palindromic substring with center i
						UpperCamelCase				:		List[Any]				   =			[1 for i in range(len(SCREAMING_SNAKE_CASE     )     )]

						# for each character in new_string find corresponding palindromic string
						UpperCamelCase				:		Optional[Any]				   =			0
						for j in range(len(SCREAMING_SNAKE_CASE     )     ):
												UpperCamelCase				:		Union[str, Any]				   =			1 if j > r else min(length[l + r - j] // 2							,     r - j + 1     )
												while (
												    j - k >= 0
												    and j + k < len(SCREAMING_SNAKE_CASE     )
												    and new_input_string[k + j] == new_input_string[j - k]
												):
																		k += 1

												UpperCamelCase				:		int				   =			2 * k - 1

												# does this string is ending after the previously explored end (that is r) ?
												# if yes the update the new r to the last index of this
												if j + k - 1 > r:
																		UpperCamelCase				:		int				   =			j - k + 1  # noqa: E741
																		UpperCamelCase				:		List[Any]				   =			j + k - 1

												# update max_length and start position
												if max_length < length[j]:
																		UpperCamelCase				:		List[str]				   =			length[j]
																		UpperCamelCase				:		List[str]				   =			j

    # create that string
						UpperCamelCase				:		Optional[Any]				   =			new_input_string[start - max_length // 2 : start + max_length // 2 + 1]
						for i in s:
												if i != "|":
																		output_string += i

						return output_string


if __name__ == "__main__":
		import doctest

		doctest.testmod()



