import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE      ,   unittest.TestCase				):
							_UpperCAmelCase						    =     LEDTokenizer
							_UpperCAmelCase						    =     LEDTokenizerFast
							_UpperCAmelCase						    =     True







							def 				snake_case  (				self     :    Any		):
										super().setUp()
										lowerCamelCase						:Optional[int]						  =     [
										    '''l''',
										    '''o''',
										    '''w''',
										    '''e''',
										    '''r''',
										    '''s''',
										    '''t''',
										    '''i''',
										    '''d''',
										    '''n''',
										    '''\u0120''',
										    '''\u0120l''',
										    '''\u0120n''',
										    '''\u0120lo''',
										    '''\u0120low''',
										    '''er''',
										    '''\u0120lowest''',
										    '''\u0120newer''',
										    '''\u0120wider''',
										    '''<unk>''',
										]
										lowerCamelCase						:Any						  =     dict(zip(__snake_case	,					range(len(__snake_case		)		)		)		)
										lowerCamelCase						:List[str]						  =     ['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
										lowerCamelCase						:int						  =     {'''unk_token''': '''<unk>'''}

										lowerCamelCase						:Optional[int]						  =     os.path.join(self.tmpdirname	,					VOCAB_FILES_NAMES['''vocab_file''']		)
										lowerCamelCase						:Any						  =     os.path.join(self.tmpdirname	,					VOCAB_FILES_NAMES['''merges_file''']		)
										with open(self.vocab_file	,					'''w'''	,					encoding='''utf-8'''		) as fp:
													fp.write(json.dumps(__snake_case		) + '''\n'''		)
										with open(self.merges_file	,					'''w'''	,					encoding='''utf-8'''		) as fp:
													fp.write('''\n'''.join(__snake_case		)		)







							def 				snake_case  (				self     :    int	,					**__snake_case     :    int		):
										kwargs.update(self.special_tokens_map		)
										return self.tokenizer_class.from_pretrained(self.tmpdirname	,					**__snake_case		)







							def 				snake_case  (				self     :    Dict	,					**__snake_case     :    Any		):
										kwargs.update(self.special_tokens_map		)
										return self.rust_tokenizer_class.from_pretrained(self.tmpdirname	,					**__snake_case		)







							def 				snake_case  (				self     :    Optional[Any]	,					__snake_case     :    Union[str, Any]		):
										return "lower newer", "lower newer"







							@cached_property
							def 				snake_case  (				self     :    Any		):
										return LEDTokenizer.from_pretrained('''allenai/led-base-16384'''		)







							@cached_property
							def 				snake_case  (				self     :    int		):
										return LEDTokenizerFast.from_pretrained('''allenai/led-base-16384'''		)







							@require_torch
							def 				snake_case  (				self     :    str		):
										lowerCamelCase						:Any						  =     ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
										lowerCamelCase						:List[Any]						  =     [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
													lowerCamelCase						:Optional[Any]						  =     tokenizer(__snake_case	,					max_length=len(__snake_case		)	,					padding=__snake_case	,					return_tensors='''pt'''		)
													self.assertIsInstance(__snake_case	,					__snake_case		)

													self.assertEqual((2, 9)	,					batch.input_ids.shape		)
													self.assertEqual((2, 9)	,					batch.attention_mask.shape		)
													lowerCamelCase						:List[Any]						  =     batch.input_ids.tolist()[0]
													self.assertListEqual(__snake_case	,					__snake_case		)







							@require_torch
							def 				snake_case  (				self     :    Tuple		):
										lowerCamelCase						:Dict						  =     ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
													lowerCamelCase						:Union[str, Any]						  =     tokenizer(__snake_case	,					padding=__snake_case	,					return_tensors='''pt'''		)
													self.assertIn('''input_ids'''	,					__snake_case		)
													self.assertIn('''attention_mask'''	,					__snake_case		)
													self.assertNotIn('''labels'''	,					__snake_case		)
													self.assertNotIn('''decoder_attention_mask'''	,					__snake_case		)







							@require_torch
							def 				snake_case  (				self     :    Union[str, Any]		):
										lowerCamelCase						:Union[str, Any]						  =     [
										    '''Summary of the text.''',
										    '''Another summary.''',
										]
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
													lowerCamelCase						:List[Any]						  =     tokenizer(text_target=__snake_case	,					max_length=32	,					padding='''max_length'''	,					return_tensors='''pt'''		)
													self.assertEqual(32	,					targets['''input_ids'''].shape[1]		)







							@require_torch
							def 				snake_case  (				self     :    List[Any]		):
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
													lowerCamelCase						:Optional[Any]						  =     tokenizer(
													    ['''I am a small frog''' * 1024, '''I am a small frog''']	,					padding=__snake_case	,					truncation=__snake_case	,					return_tensors='''pt'''		)
													self.assertIsInstance(__snake_case	,					__snake_case		)
													self.assertEqual(batch.input_ids.shape	,					(2, 5122)		)







							@require_torch
							def 				snake_case  (				self     :    Optional[int]		):
										lowerCamelCase						:Union[str, Any]						  =     ['''A long paragraph for summarization.''']
										lowerCamelCase						:Any						  =     [
										    '''Summary of the text.''',
										]
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
													lowerCamelCase						:Union[str, Any]						  =     tokenizer(__snake_case	,					return_tensors='''pt'''		)
													lowerCamelCase						:Any						  =     tokenizer(text_target=__snake_case	,					return_tensors='''pt'''		)
													lowerCamelCase						:Optional[int]						  =     inputs['''input_ids''']
													lowerCamelCase						:Any						  =     targets['''input_ids''']
													self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()		)
													self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()		)
													self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()		)
													self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()		)







							@require_torch
							def 				snake_case  (				self     :    Dict		):
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
													lowerCamelCase						:Optional[int]						  =     ['''Summary of the text.''', '''Another summary.''']
													lowerCamelCase						:List[Any]						  =     [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

													lowerCamelCase						:Optional[int]						  =     tokenizer(__snake_case	,					padding=__snake_case		)
													lowerCamelCase						:Union[str, Any]						  =     [[0] * len(__snake_case		) for x in encoded_output['''input_ids''']]
													lowerCamelCase						:str						  =     tokenizer.pad(__snake_case		)
													self.assertSequenceEqual(outputs['''global_attention_mask''']	,					__snake_case		)







							def 				snake_case  (				self     :    Tuple		):
										pass







							def 				snake_case  (				self     :    Optional[int]		):
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"		):
																lowerCamelCase						:Optional[Any]						  =     self.rust_tokenizer_class.from_pretrained(__snake_case	,					**__snake_case		)
																lowerCamelCase						:Tuple						  =     self.tokenizer_class.from_pretrained(__snake_case	,					**__snake_case		)
																lowerCamelCase						:int						  =     '''A, <mask> AllenNLP sentence.'''
																lowerCamelCase						:str						  =     tokenizer_r.encode_plus(__snake_case	,					add_special_tokens=__snake_case	,					return_token_type_ids=__snake_case		)
																lowerCamelCase						:str						  =     tokenizer_p.encode_plus(__snake_case	,					add_special_tokens=__snake_case	,					return_token_type_ids=__snake_case		)
																self.assertEqual(sum(tokens_r['''token_type_ids''']		)	,					sum(tokens_p['''token_type_ids''']		)		)
																self.assertEqual(
																    sum(tokens_r['''attention_mask''']		) / len(tokens_r['''attention_mask''']		)	,					sum(tokens_p['''attention_mask''']		) / len(tokens_p['''attention_mask''']		)	,					)

																lowerCamelCase						:Optional[int]						  =     tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']		)
																lowerCamelCase						:Tuple						  =     tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']		)
																self.assertSequenceEqual(tokens_p['''input_ids''']	,					[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]		)
																self.assertSequenceEqual(tokens_r['''input_ids''']	,					[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]		)

																self.assertSequenceEqual(
																    __snake_case	,					['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']		)
																self.assertSequenceEqual(
																    __snake_case	,					['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']		)




import os
from typing import Optional

import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     ''
							_UpperCAmelCase						    =     (
							    None  # protocol passed in prefix to the url. ex: "gzip", for gzip://file.txt::http://foo.bar/file.txt.gz
							)
							_UpperCAmelCase						    =     None  # compression type in fsspec. ex: "gzip"
							_UpperCAmelCase						    =     None  # extension of the filename to strip. ex: "".gz" to get file.txt from file.txt.gz







							def __init__(				self     :    str	,					__snake_case     :    str = ""	,					__snake_case     :    Optional[str] = None	,					__snake_case     :    Optional[dict] = None	,					**__snake_case     :    Dict		):
										super().__init__(self	,					**__snake_case		)
										# always open as "rb" since fsspec can then use the TextIOWrapper to make it work for "r" mode
										lowerCamelCase						:Optional[Any]						  =     fsspec.open(
										    __snake_case	,					mode='''rb'''	,					protocol=__snake_case	,					compression=self.compression	,					client_kwargs={
										        '''requote_redirect_url''': False,  # see https://github.com/huggingface/datasets/pull/5459
										        '''trust_env''': True,  # Enable reading proxy env variables.
										        **(target_options or {}).pop('''client_kwargs'''	,					{}		),  # To avoid issues if it was already passed.
										    }	,					**(target_options or {})	,					)
										lowerCamelCase						:List[str]						  =     os.path.basename(self.file.path.split('''::'''		)[0]		)
										lowerCamelCase						:Dict						  =     (
										    self.compressed_name[: self.compressed_name.rindex('''.'''		)]
										    if '''.''' in self.compressed_name
										    else self.compressed_name
										)
										lowerCamelCase						:List[str]						  =     None







							@classmethod
							def 				snake_case  (				cls     :    Any	,					__snake_case     :    Any		):
										# compressed file paths are always relative to the archive root
										return super()._strip_protocol(__snake_case		).lstrip('''/'''		)







							def 				snake_case  (				self     :    Any		):
										if self.dir_cache is None:
													lowerCamelCase						:Optional[Any]						  =     {**self.file.fs.info(self.file.path		), '''name''': self.uncompressed_name}
													lowerCamelCase						:Optional[Any]						  =     {f['''name''']: f}







							def 				snake_case  (				self     :    Union[str, Any]	,					__snake_case     :    str		):
										return self.file.open().read()







							def 				snake_case  (				self     :    Optional[int]	,					__snake_case     :    str	,					__snake_case     :    str = "rb"	,					__snake_case     :    int=None	,					__snake_case     :    Optional[int]=True	,					__snake_case     :    str=None	,					**__snake_case     :    str	,					):
										lowerCamelCase						:List[str]						  =     self._strip_protocol(__snake_case		)
										if mode != "rb":
													raise ValueError(F"Tried to read with mode {mode} on file {self.file.path} opened with mode 'rb'"		)
										return self.file.open()


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'bz2'
							_UpperCAmelCase						    =     'bz2'
							_UpperCAmelCase						    =     '.bz2'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'gzip'
							_UpperCAmelCase						    =     'gzip'
							_UpperCAmelCase						    =     '.gz'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'lz4'
							_UpperCAmelCase						    =     'lz4'
							_UpperCAmelCase						    =     '.lz4'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'xz'
							_UpperCAmelCase						    =     'xz'
							_UpperCAmelCase						    =     '.xz'


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'zstd'
							_UpperCAmelCase						    =     'zstd'
							_UpperCAmelCase						    =     '.zst'







							def __init__(				self     :    str	,					__snake_case     :    str	,					__snake_case     :    str = "rb"	,					__snake_case     :    Optional[str] = None	,					__snake_case     :    Optional[dict] = None	,					__snake_case     :    int = DEFAULT_BLOCK_SIZE	,					**__snake_case     :    int	,					):
										super().__init__(
										    fo=__snake_case	,					mode=__snake_case	,					target_protocol=__snake_case	,					target_options=__snake_case	,					block_size=__snake_case	,					**__snake_case	,					)
										# We need to wrap the zstd decompressor to avoid this error in fsspec==2021.7.0 and zstandard==0.15.2:
										#
										# File "/Users/user/.virtualenvs/hf-datasets/lib/python3.7/site-packages/fsspec/core.py", line 145, in open
										#     out.close = close
										# AttributeError: 'zstd.ZstdDecompressionReader' object attribute 'close' is read-only
										#
										# see https://github.com/intake/filesystem_spec/issues/725
										lowerCamelCase						:Tuple						  =     self.file.__enter__
										class   _lowerCAmelCase		:







																	def __init__(				self     :    Dict	,					__snake_case     :    Tuple		):
																				lowerCamelCase						:Optional[int]						  =     file_







																	def __enter__(				self     :    Optional[int]		):
																				self._file.__enter__()
																				return self







																	def __exit__(				self     :    str	,					*__snake_case     :    Optional[Any]	,					**__snake_case     :    List[Any]		):
																				self._file.__exit__(*__snake_case	,					**__snake_case		)







																	def __iter__(				self     :    Optional[Any]		):
																				return iter(self._file		)







																	def 				snake_case  (				self     :    List[Any]		):
																				return next(self._file		)







																	def __getattr__(				self     :    Any	,					__snake_case     :    str		):
																				return getattr(self._file	,					__snake_case		)

										def fixed_enter(*__snake_case     :    Optional[int]	,					**__snake_case     :    str		):
													return WrappedFile(_enter(*__snake_case	,					**__snake_case		)		)

										lowerCamelCase						:Dict						  =     fixed_enter



