


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   (      __magic_name__	:				Tuple       ,       __magic_name__	:				Optional[int]       ,       __magic_name__	:				Any       ,       __magic_name__	:				List[str]       ,       __magic_name__	:				List[Any]=True       ,       __magic_name__	:				Tuple="pt"	)  ->    Dict:
		"""simple docstring"""




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






def 					UpperCamelCase   (      __magic_name__	:				int       ,       __magic_name__	:				int       ,       __magic_name__	:				Any=None       ,       )  ->    Union[str, Any]:
		"""simple docstring"""




		lowercase__	     =						input_ids.ne(__magic_name__	).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 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					def __init__(self       :		Any ,   _UpperCAmelCase       :		Any ,   _UpperCAmelCase       :		int ,   _UpperCAmelCase       :		List[str] ,   _UpperCAmelCase       :		int ,   _UpperCAmelCase       :		Optional[Any]="train" ,   _UpperCAmelCase       :		Tuple=None ,   _UpperCAmelCase       :		Optional[Any]=None ,   _UpperCAmelCase       :		Optional[int]=None ,   _UpperCAmelCase       :		Any="" ,   )		->  Any:




							"""simple docstring"""


							super().__init__()
							lowercase__	     =						Path(_UpperCAmelCase						).joinpath(type_path + """.source"""						)
							lowercase__	     =						Path(_UpperCAmelCase						).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       :		Optional[int]						)		->  List[Any]:




							"""simple docstring"""


							return len(self.src_lens						)

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




							"""simple docstring"""


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

							lowercase__	     =						encode_line(_UpperCAmelCase ,   _UpperCAmelCase ,   self.max_source_length ,   """right"""						)
							lowercase__	     =						encode_line(_UpperCAmelCase ,   _UpperCAmelCase ,   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     lowerCamelCase__	(_UpperCAmelCase       :		Any						)		->  Optional[Any]:




							"""simple docstring"""


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


					def     lowerCamelCase__	(self       :		Any ,   _UpperCAmelCase       :		Union[str, Any]						)		->  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 ,   _UpperCAmelCase						)
							    else self.tokenizer.pad_token_id
							)
							lowercase__	     =						(
							    self.tokenizer.question_encoder.pad_token_id
							    if isinstance(self.tokenizer ,   _UpperCAmelCase						)
							    else self.tokenizer.pad_token_id
							)
							lowercase__	     =						trim_batch(_UpperCAmelCase ,   _UpperCAmelCase						)
							lowercase__     ,      lowercase__	     =						trim_batch(_UpperCAmelCase ,   _UpperCAmelCase ,   attention_mask=_UpperCAmelCase						)
							lowercase__	     =						{
							    """input_ids""": source_ids,
							    """attention_mask""": source_mask,
							    """decoder_input_ids""": y,
							}
							return batch






A			:						Dict        =  getLogger(__name__)






def 					UpperCamelCase   (      __magic_name__	:				List[List]	)  ->    Dict:
		"""simple docstring"""




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






def 					UpperCamelCase   (      __magic_name__	:				str	)  ->    None:
		"""simple docstring"""




		lowercase__	     =						get_git_info()
		save_json(__magic_name__       ,       os.path.join(__magic_name__       ,       """git_log.json"""	)	)






def 					UpperCamelCase   (      __magic_name__	:				Optional[Any]       ,       __magic_name__	:				Tuple       ,       __magic_name__	:				Dict=4       ,       **__magic_name__	:				List[str]	)  ->    Optional[Any]:
		"""simple docstring"""




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






def 					UpperCamelCase   (      __magic_name__	:				int	)  ->    Optional[int]:
		"""simple docstring"""




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






def 					UpperCamelCase   (      )  ->    Optional[Any]:
		"""simple docstring"""




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






def 					UpperCamelCase   (      __magic_name__	:				Callable       ,       __magic_name__	:				Iterable	)  ->    List:
		"""simple docstring"""




		return list(map(__magic_name__       ,       __magic_name__	)	)






def 					UpperCamelCase   (      __magic_name__	:				int       ,       __magic_name__	:				str	)  ->    Optional[int]:
		"""simple docstring"""




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






def 					UpperCamelCase   (      __magic_name__	:				str	)  ->    Dict:
		"""simple docstring"""




		def remove_articles(__magic_name__	:				Optional[int]	):
				return re.sub(R"""\b(a|an|the)\b"""       ,       """ """       ,       __magic_name__	)

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

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

		def lower(__magic_name__	:				Tuple	):
				return text.lower()

		return white_space_fix(remove_articles(remove_punc(lower(__magic_name__	)	)	)	)






def 					UpperCamelCase   (      __magic_name__	:				int       ,       __magic_name__	:				List[Any]	)  ->    str:
		"""simple docstring"""




		lowercase__	     =						normalize_answer(__magic_name__	).split()
		lowercase__	     =						normalize_answer(__magic_name__	).split()
		lowercase__	     =						Counter(__magic_name__	) & Counter(__magic_name__	)
		lowercase__	     =						sum(common.values()	)
		if num_same == 0:
				return 0
		lowercase__	     =						1.0 * num_same / len(__magic_name__	)
		lowercase__	     =						1.0 * num_same / len(__magic_name__	)
		lowercase__	     =						(2 * precision * recall) / (precision + recall)
		return fa






def 					UpperCamelCase   (      __magic_name__	:				int       ,       __magic_name__	:				str	)  ->    List[Any]:
		"""simple docstring"""




		return normalize_answer(__magic_name__	) == normalize_answer(__magic_name__	)






def 					UpperCamelCase   (      __magic_name__	:				List[str]       ,       __magic_name__	:				List[str]	)  ->    Dict:
		"""simple docstring"""




		assert len(__magic_name__	) == len(__magic_name__	)
		lowercase__	     =						0
		for hypo, pred in zip(__magic_name__       ,       __magic_name__	):
				em += exact_match_score(__magic_name__       ,       __magic_name__	)
		if len(__magic_name__	) > 0:
				em /= len(__magic_name__	)
		return {"em": em}






def 					UpperCamelCase   (      __magic_name__	:				List[str]	)  ->    str:
		"""simple docstring"""




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







def 					UpperCamelCase   (      __magic_name__	:				Union[str, Any]       ,       __magic_name__	:				int       ,       __magic_name__	:				int	)  ->    int:
		"""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(__magic_name__       ,       __magic_name__       ,       __magic_name__	):
						if not hasattr(__magic_name__       ,       __magic_name__	) and not hasattr(__magic_name__       ,       equivalent_param[p]	):
								logger.info("""config doesn't have a `{}` attribute""".format(__magic_name__	)	)
								delattr(__magic_name__       ,       __magic_name__	)
								continue
						lowercase__	     =						p if hasattr(__magic_name__       ,       __magic_name__	) else equivalent_param[p]
						setattr(__magic_name__       ,       __magic_name__       ,       getattr(__magic_name__       ,       __magic_name__	)	)
						delattr(__magic_name__       ,       __magic_name__	)
		return hparams, config





import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A			:						Optional[Any]        =  get_tests_dir('fixtures/test_sentencepiece_no_bos.model')



@require_sentencepiece
@require_tokenizers
class 				A       (			UpperCAmelCase__					,    unittest.TestCase				):
					'''simple docstring'''






					A__     =					PegasusTokenizer
					A__     =					PegasusTokenizerFast
					A__     =					True
					A__     =					True

					def     lowerCamelCase__	(self       :		List[Any]						)		->  Tuple:




							"""simple docstring"""


							super().setUp()

							# We have a SentencePiece fixture for testing
							lowercase__	     =						PegasusTokenizer(_UpperCAmelCase						)
							tokenizer.save_pretrained(self.tmpdirname						)

					@cached_property
					def     lowerCamelCase__	(self       :		Tuple						)		->  Any:




							"""simple docstring"""


							return PegasusTokenizer.from_pretrained("""google/pegasus-large"""						)

					def     lowerCamelCase__	(self       :		Tuple ,   **_UpperCAmelCase       :		int						)		->  PegasusTokenizer:




							"""simple docstring"""


							return PegasusTokenizer.from_pretrained(self.tmpdirname ,   **_UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Optional[int] ,   _UpperCAmelCase       :		Any						)		->  List[str]:




							"""simple docstring"""


							return ("This is a test", "This is a test")

					def     lowerCamelCase__	(self       :		Dict						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						"""</s>"""
							lowercase__	     =						1

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(_UpperCAmelCase						) ,   _UpperCAmelCase						)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(_UpperCAmelCase						) ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Optional[int]						)		->  str:




							"""simple docstring"""


							lowercase__	     =						list(self.get_tokenizer().get_vocab().keys()						)

							self.assertEqual(vocab_keys[0] ,   """<pad>"""						)
							self.assertEqual(vocab_keys[1] ,   """</s>"""						)
							self.assertEqual(vocab_keys[-1] ,   """v"""						)
							self.assertEqual(len(_UpperCAmelCase						) ,   1103						)

					def     lowerCamelCase__	(self       :		str						)		->  Dict:




							"""simple docstring"""


							self.assertEqual(self.get_tokenizer().vocab_size ,   1103						)

					def     lowerCamelCase__	(self       :		Any						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						self.rust_tokenizer_class.from_pretrained(self.tmpdirname						)
							lowercase__	     =						self.tokenizer_class.from_pretrained(self.tmpdirname						)
							lowercase__	     =						(
							    """Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"""
							    """ </s> <pad> <pad> <pad>"""
							)
							lowercase__	     =						rust_tokenizer([raw_input_str] ,   return_tensors=_UpperCAmelCase ,   add_special_tokens=_UpperCAmelCase						).input_ids[0]
							lowercase__	     =						py_tokenizer([raw_input_str] ,   return_tensors=_UpperCAmelCase ,   add_special_tokens=_UpperCAmelCase						).input_ids[0]
							self.assertListEqual(_UpperCAmelCase ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		int						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						self._large_tokenizer
							# <mask_1> masks whole sentence while <mask_2> masks single word
							lowercase__	     =						"""<mask_1> To ensure a <mask_2> flow of bank resolutions."""
							lowercase__	     =						[2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
							lowercase__	     =						tokenizer([raw_input_str] ,   return_tensors=_UpperCAmelCase						).input_ids[0]
							self.assertListEqual(_UpperCAmelCase ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Optional[Any]						)		->  int:




							"""simple docstring"""


							lowercase__	     =						self._large_tokenizer
							# The tracebacks for the following asserts are **better** without messages or self.assertEqual
							assert tokenizer.vocab_size == 9_6103
							assert tokenizer.pad_token_id == 0
							assert tokenizer.eos_token_id == 1
							assert tokenizer.offset == 103
							assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
							assert tokenizer.unk_token == "<unk>"
							assert tokenizer.model_max_length == 1024
							lowercase__	     =						"""To ensure a smooth flow of bank resolutions."""
							lowercase__	     =						[413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
							lowercase__	     =						tokenizer([raw_input_str] ,   return_tensors=_UpperCAmelCase						).input_ids[0]
							self.assertListEqual(_UpperCAmelCase ,   _UpperCAmelCase						)
							assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]						) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]

					@require_torch
					def     lowerCamelCase__	(self       :		Union[str, Any]						)		->  Union[str, Any]:




							"""simple docstring"""


							lowercase__	     =						["""This is going to be way too long.""" * 150, """short example"""]
							lowercase__	     =						["""not super long but more than 5 tokens""", """tiny"""]
							lowercase__	     =						self._large_tokenizer(_UpperCAmelCase ,   padding=_UpperCAmelCase ,   truncation=_UpperCAmelCase ,   return_tensors="""pt"""						)
							lowercase__	     =						self._large_tokenizer(
							    text_target=_UpperCAmelCase ,   max_length=5 ,   padding=_UpperCAmelCase ,   truncation=_UpperCAmelCase ,   return_tensors="""pt"""						)

							assert batch.input_ids.shape == (2, 1024)
							assert batch.attention_mask.shape == (2, 1024)
							assert targets["input_ids"].shape == (2, 5)
							assert len(_UpperCAmelCase						) == 2  # input_ids, attention_mask.


					@slow
					def     lowerCamelCase__	(self       :		List[Any]						)		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						{"""input_ids""": [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=_UpperCAmelCase ,   model_name="""google/bigbird-pegasus-large-arxiv""" ,   revision="""ba85d0851d708441f91440d509690f1ab6353415""" ,   )






@require_sentencepiece
@require_tokenizers
class 				A       (			UpperCAmelCase__					,    unittest.TestCase				):
					'''simple docstring'''






					A__     =					PegasusTokenizer
					A__     =					PegasusTokenizerFast
					A__     =					True
					A__     =					True

					def     lowerCamelCase__	(self       :		Any						)		->  int:




							"""simple docstring"""


							super().setUp()

							# We have a SentencePiece fixture for testing
							lowercase__	     =						PegasusTokenizer(_UpperCAmelCase ,   offset=0 ,   mask_token_sent=_UpperCAmelCase ,   mask_token="""[MASK]"""						)
							tokenizer.save_pretrained(self.tmpdirname						)

					@cached_property
					def     lowerCamelCase__	(self       :		Any						)		->  str:




							"""simple docstring"""


							return PegasusTokenizer.from_pretrained("""google/bigbird-pegasus-large-arxiv"""						)

					def     lowerCamelCase__	(self       :		str ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  PegasusTokenizer:




							"""simple docstring"""


							return PegasusTokenizer.from_pretrained(self.tmpdirname ,   **_UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Tuple ,   _UpperCAmelCase       :		Any						)		->  Union[str, Any]:




							"""simple docstring"""


							return ("This is a test", "This is a test")

					def     lowerCamelCase__	(self       :		Any						)		->  int:




							"""simple docstring"""


							lowercase__	     =						self.rust_tokenizer_class.from_pretrained(self.tmpdirname						)
							lowercase__	     =						self.tokenizer_class.from_pretrained(self.tmpdirname						)
							lowercase__	     =						(
							    """Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"""
							    """ <pad> <pad> <pad>"""
							)
							lowercase__	     =						rust_tokenizer([raw_input_str] ,   return_tensors=_UpperCAmelCase ,   add_special_tokens=_UpperCAmelCase						).input_ids[0]
							lowercase__	     =						py_tokenizer([raw_input_str] ,   return_tensors=_UpperCAmelCase ,   add_special_tokens=_UpperCAmelCase						).input_ids[0]
							self.assertListEqual(_UpperCAmelCase ,   _UpperCAmelCase						)

					@require_torch
					def     lowerCamelCase__	(self       :		List[str]						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						["""This is going to be way too long.""" * 1000, """short example"""]
							lowercase__	     =						["""not super long but more than 5 tokens""", """tiny"""]
							lowercase__	     =						self._large_tokenizer(_UpperCAmelCase ,   padding=_UpperCAmelCase ,   truncation=_UpperCAmelCase ,   return_tensors="""pt"""						)
							lowercase__	     =						self._large_tokenizer(
							    text_target=_UpperCAmelCase ,   max_length=5 ,   padding=_UpperCAmelCase ,   truncation=_UpperCAmelCase ,   return_tensors="""pt"""						)

							assert batch.input_ids.shape == (2, 4096)
							assert batch.attention_mask.shape == (2, 4096)
							assert targets["input_ids"].shape == (2, 5)
							assert len(_UpperCAmelCase						) == 2  # input_ids, attention_mask.


					def     lowerCamelCase__	(self       :		Optional[int]						)		->  Any:




							"""simple docstring"""


							lowercase__	     =						(
							    """This is an example string that is used to test the original TF implementation against the HF"""
							    """ implementation"""
							)

							lowercase__	     =						self._large_tokenizer(_UpperCAmelCase						).input_ids

							self.assertListEqual(
							    _UpperCAmelCase ,   [182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1] ,   )

