


'''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 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase=True       ,			_UpperCamelCase="pt"  ):


			'''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 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase=None       ,			):


			'''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 	lowerCamelCase_       (				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_="" ,       )   ->			Optional[Any]:







								'''simple docstring'''

								super().__init__()
								__lowercase 					=   Path(snake_case_						).joinpath(type_path + '''.source'''						)
								__lowercase 					=   Path(snake_case_						).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						)   ->			str:







								'''simple docstring'''

								return len(self.src_lens						)






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







								'''simple docstring'''

								__lowercase 					=   index + 1  # linecache starts at 1
								__lowercase 					=   self.prefix + linecache.getline(str(self.src_file						) ,       snake_case_						).rstrip('''\n'''						)
								__lowercase 					=   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 					=   (
								    self.tokenizer.question_encoder if isinstance(self.tokenizer ,       snake_case_						) else self.tokenizer
								)
								__lowercase 					=   self.tokenizer.generator if isinstance(self.tokenizer ,       snake_case_						) else self.tokenizer

								__lowercase 					=   encode_line(snake_case_ ,       snake_case_ ,       self.max_source_length ,       '''right'''						)
								__lowercase 					=   encode_line(snake_case_ ,       snake_case_ ,       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 A      (				snake_case_						)   ->			Union[str, Any]:







								'''simple docstring'''

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






					def A      (				self ,       snake_case_						)   ->			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 ,       snake_case_						)
								    else self.tokenizer.pad_token_id
								)
								__lowercase 					=   (
								    self.tokenizer.question_encoder.pad_token_id
								    if isinstance(self.tokenizer ,       snake_case_						)
								    else self.tokenizer.pad_token_id
								)
								__lowercase 					=   trim_batch(snake_case_ ,       snake_case_						)
								__lowercase					, __lowercase 					=   trim_batch(snake_case_ ,       snake_case_ ,       attention_mask=snake_case_						)
								__lowercase 					=   {
								    '''input_ids''': source_ids,
								    '''attention_mask''': source_mask,
								    '''decoder_input_ids''': y,
								}
								return batch




a : Optional[Any]		=				getLogger(__name__)


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







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


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







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


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase=4       ,			**_UpperCamelCase  ):


			'''simple docstring'''







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


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







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


def 		lowercase_  (     ):


			'''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 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''simple docstring'''







			return list(map(_UpperCamelCase       ,			_UpperCamelCase  )  )


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''simple docstring'''







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


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







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

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

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

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

			return white_space_fix(remove_articles(remove_punc(lower(_UpperCamelCase  )  )  )  )


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''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 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''simple docstring'''







			return normalize_answer(_UpperCamelCase  ) == normalize_answer(_UpperCamelCase  )


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''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 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







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





def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase  ):


			'''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






from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

a : Optional[int]		=				typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
a : Union[str, Any]		=				typing.Union[np.floataa, int, float]  # noqa: UP007


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''simple docstring'''







			return np.sqrt(np.sum((np.asarray(_UpperCamelCase  ) - np.asarray(_UpperCamelCase  )) ** 2  )  )


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''simple docstring'''







			return sum((va - va) ** 2 for va, va in zip(_UpperCamelCase       ,			_UpperCamelCase  )  ) ** (1 / 2)


if __name__ == "__main__":


	def 		lowercase_  (     ):


				'''simple docstring'''







				from timeit import timeit

				print('''Without Numpy'''  )
				print(
				    timeit(
				        '''euclidean_distance_no_np([1, 2, 3], [4, 5, 6])'''       ,			number=1_00_00       ,			globals=globals()       ,			)  )
				print('''With Numpy'''  )
				print(
				    timeit(
				        '''euclidean_distance([1, 2, 3], [4, 5, 6])'''       ,			number=1_00_00       ,			globals=globals()       ,			)  )





	benchmark()


