






import copy
import re

class 						A__							:
						UpperCAmelCase             =						"hp"
						UpperCAmelCase             =						{}
						UpperCAmelCase             =						None




						@classmethod
						def 							__UpperCamelCase				(       cls					:      Optional[int]				,    _a					:      Optional[int]				,    _a					:      List[str]  )							->     List[str]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =prefix
										_SCREAMING_SNAKE_CASE			  =defaults
										cls.build_naming_info()




						@staticmethod
						def 							__UpperCamelCase				(       _a					:      Optional[Any]				,    _a					:      List[str]  )							->     Optional[int]:


										"""simple docstring"""





										if len(_a  ) == 0:
														return ""
										_SCREAMING_SNAKE_CASE			  =None
										if any(char.isdigit() for char in word  ):
														raise Exception(f"Parameters should not contain numbers: '{word}' contains a number"  )
										if word in info["short_word"]:
														return info["short_word"][word]
										for prefix_len in range(1				,    len(_a  ) + 1  ):
														_SCREAMING_SNAKE_CASE			  =word[:prefix_len]
														if prefix in info["reverse_short_word"]:
																		continue
														else:
																		_SCREAMING_SNAKE_CASE			  =prefix
																		break

										if short_word is None:
														# Paranoid fallback
														def int_to_alphabetic(_a					:      Optional[Any]  ):
																		_SCREAMING_SNAKE_CASE			  =''''''
																		while integer != 0:
																						_SCREAMING_SNAKE_CASE			  =chr(ord('''A'''  ) + integer % 10  ) + s
																						integer //= 10
																		return s

														_SCREAMING_SNAKE_CASE			  =0
														while True:
																		_SCREAMING_SNAKE_CASE			  =word + '''#''' + int_to_alphabetic(_a  )
																		if sword in info["reverse_short_word"]:
																						continue
																		else:
																						_SCREAMING_SNAKE_CASE			  =sword
																						break

										_SCREAMING_SNAKE_CASE			  =short_word
										_SCREAMING_SNAKE_CASE			  =word
										return short_word




						@staticmethod
						def 							__UpperCamelCase				(       _a					:      Optional[Any]				,    _a					:      Union[str, Any]  )							->     List[Any]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =param_name.split('''_'''  )

										_SCREAMING_SNAKE_CASE			  =[TrialShortNamer.shortname_for_word(_a				,    _a  ) for word in words]

										# We try to create a separatorless short name, but if there is a collision we have to fallback
										# to a separated short name
										_SCREAMING_SNAKE_CASE			  =['''''', '''_''']

										for separator in separators:
														_SCREAMING_SNAKE_CASE			  =separator.join(_a  )
														if shortname not in info["reverse_short_param"]:
																		_SCREAMING_SNAKE_CASE			  =shortname
																		_SCREAMING_SNAKE_CASE			  =param_name
																		return shortname

										return param_name




						@staticmethod
						def 							__UpperCamelCase				(       _a					:      Optional[Any]				,    _a					:      Optional[int]  )							->     int:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =TrialShortNamer.shortname_for_key(_a				,    _a  )
										_SCREAMING_SNAKE_CASE			  =short_name
										_SCREAMING_SNAKE_CASE			  =param_name




						@classmethod
						def 							__UpperCamelCase				(       cls					:      Dict  )							->     Union[str, Any]:


										"""simple docstring"""





										if cls.NAMING_INFO is not None:
														return

										_SCREAMING_SNAKE_CASE			  ={
										    '''short_word''': {},
										    '''reverse_short_word''': {},
										    '''short_param''': {},
										    '''reverse_short_param''': {},
										}

										_SCREAMING_SNAKE_CASE			  =list(cls.DEFAULTS.keys()  )

										for k in field_keys:
														cls.add_new_param_name(_a				,    _a  )

										_SCREAMING_SNAKE_CASE			  =info




						@classmethod
						def 							__UpperCamelCase				(       cls					:      Dict				,    _a					:      Optional[int]  )							->     str:


										"""simple docstring"""





										cls.build_naming_info()
										assert cls.PREFIX is not None
										_SCREAMING_SNAKE_CASE			  =[copy.copy(cls.PREFIX  )]

										for k, v in params.items():
														if k not in cls.DEFAULTS:
																		raise Exception(f"You should provide a default value for the param name {k} with value {v}"  )
														if v == cls.DEFAULTS[k]:
																		# The default value is not added to the name
																		continue

														_SCREAMING_SNAKE_CASE			  =cls.NAMING_INFO['''short_param'''][k]

														if isinstance(_a				,    _a  ):
																		_SCREAMING_SNAKE_CASE			  =1 if v else 0

														_SCREAMING_SNAKE_CASE			  ='''''' if isinstance(_a				,    (int, float)  ) else '''-'''
														_SCREAMING_SNAKE_CASE			  =f"{key}{sep}{v}"
														name.append(_a  )

										return "_".join(_a  )




						@classmethod
						def 							__UpperCamelCase				(       cls					:      Optional[Any]				,    _a					:      Dict  )							->     Union[str, Any]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =repr[len(cls.PREFIX  ) + 1 :]
										if repr == "":
														_SCREAMING_SNAKE_CASE			  =[]
										else:
														_SCREAMING_SNAKE_CASE			  =repr.split('''_'''  )

										_SCREAMING_SNAKE_CASE			  ={}

										for value in values:
														if "-" in value:
																		_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE			  =value.split('''-'''  )
														else:
																		_SCREAMING_SNAKE_CASE			  =re.sub('''[0-9.]'''				,    ''''''				,    _a  )
																		_SCREAMING_SNAKE_CASE			  =float(re.sub('''[^0-9.]'''				,    ''''''				,    _a  )  )

														_SCREAMING_SNAKE_CASE			  =cls.NAMING_INFO['''reverse_short_param'''][p_k]

														_SCREAMING_SNAKE_CASE			  =p_v

										for k in cls.DEFAULTS:
														if k not in parameters:
																		_SCREAMING_SNAKE_CASE			  =cls.DEFAULTS[k]

										return parameters



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 						A__							(		UpperCamelCase__   ,     unittest.TestCase  ):
						UpperCAmelCase             =						LEDTokenizer
						UpperCAmelCase             =						LEDTokenizerFast
						UpperCAmelCase             =						True




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


										"""simple docstring"""





										super().setUp()
										_SCREAMING_SNAKE_CASE			  =[
										    '''l''',
										    '''o''',
										    '''w''',
										    '''e''',
										    '''r''',
										    '''s''',
										    '''t''',
										    '''i''',
										    '''d''',
										    '''n''',
										    '''\u0120''',
										    '''\u0120l''',
										    '''\u0120n''',
										    '''\u0120lo''',
										    '''\u0120low''',
										    '''er''',
										    '''\u0120lowest''',
										    '''\u0120newer''',
										    '''\u0120wider''',
										    '''<unk>''',
										]
										_SCREAMING_SNAKE_CASE			  =dict(zip(_a				,    range(len(_a  )  )  )  )
										_SCREAMING_SNAKE_CASE			  =['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
										_SCREAMING_SNAKE_CASE			  ={'''unk_token''': '''<unk>'''}

										_SCREAMING_SNAKE_CASE			  =os.path.join(self.tmpdirname				,    VOCAB_FILES_NAMES['''vocab_file''']  )
										_SCREAMING_SNAKE_CASE			  =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(_a  ) + '''\n'''  )
										with open(self.merges_file				,    '''w'''				,    encoding='''utf-8'''  ) as fp:
														fp.write('''\n'''.join(_a  )  )




						def 							__UpperCamelCase				(       self					:      str				,    **_a					:      int  )							->     Optional[Any]:


										"""simple docstring"""





										kwargs.update(self.special_tokens_map  )
										return self.tokenizer_class.from_pretrained(self.tmpdirname				,    **_a  )




						def 							__UpperCamelCase				(       self					:      List[str]				,    **_a					:      List[Any]  )							->     str:


										"""simple docstring"""





										kwargs.update(self.special_tokens_map  )
										return self.rust_tokenizer_class.from_pretrained(self.tmpdirname				,    **_a  )




						def 							__UpperCamelCase				(       self					:      Dict				,    _a					:      Any  )							->     Dict:


										"""simple docstring"""





										return "lower newer", "lower newer"




						@cached_property
						def 							__UpperCamelCase				(       self					:      Optional[Any]  )							->     Dict:


										"""simple docstring"""





										return LEDTokenizer.from_pretrained('''allenai/led-base-16384'''  )




						@cached_property
						def 							__UpperCamelCase				(       self					:      List[Any]  )							->     Any:


										"""simple docstring"""





										return LEDTokenizerFast.from_pretrained('''allenai/led-base-16384'''  )




						@require_torch
						def 							__UpperCamelCase				(       self					:      str  )							->     Dict:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
										_SCREAMING_SNAKE_CASE			  =[0, 250, 251, 1_7818, 13, 3_9186, 1938, 4, 2]

										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
														_SCREAMING_SNAKE_CASE			  =tokenizer(_a				,    max_length=len(_a  )				,    padding=_a				,    return_tensors='''pt'''  )
														self.assertIsInstance(_a				,    _a  )

														self.assertEqual((2, 9)				,    batch.input_ids.shape  )
														self.assertEqual((2, 9)				,    batch.attention_mask.shape  )
														_SCREAMING_SNAKE_CASE			  =batch.input_ids.tolist()[0]
														self.assertListEqual(_a				,    _a  )




						@require_torch
						def 							__UpperCamelCase				(       self					:      Dict  )							->     Dict:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
														_SCREAMING_SNAKE_CASE			  =tokenizer(_a				,    padding=_a				,    return_tensors='''pt'''  )
														self.assertIn('''input_ids'''				,    _a  )
														self.assertIn('''attention_mask'''				,    _a  )
														self.assertNotIn('''labels'''				,    _a  )
														self.assertNotIn('''decoder_attention_mask'''				,    _a  )




						@require_torch
						def 							__UpperCamelCase				(       self					:      Dict  )							->     str:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =[
										    '''Summary of the text.''',
										    '''Another summary.''',
										]
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
														_SCREAMING_SNAKE_CASE			  =tokenizer(text_target=_a				,    max_length=32				,    padding='''max_length'''				,    return_tensors='''pt'''  )
														self.assertEqual(32				,    targets['''input_ids'''].shape[1]  )




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


										"""simple docstring"""





										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
														_SCREAMING_SNAKE_CASE			  =tokenizer(
														    ['''I am a small frog''' * 1024, '''I am a small frog''']				,    padding=_a				,    truncation=_a				,    return_tensors='''pt'''  )
														self.assertIsInstance(_a				,    _a  )
														self.assertEqual(batch.input_ids.shape				,    (2, 5122)  )




						@require_torch
						def 							__UpperCamelCase				(       self					:      int  )							->     Dict:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =['''A long paragraph for summarization.''']
										_SCREAMING_SNAKE_CASE			  =[
										    '''Summary of the text.''',
										]
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
														_SCREAMING_SNAKE_CASE			  =tokenizer(_a				,    return_tensors='''pt'''  )
														_SCREAMING_SNAKE_CASE			  =tokenizer(text_target=_a				,    return_tensors='''pt'''  )
														_SCREAMING_SNAKE_CASE			  =inputs['''input_ids''']
														_SCREAMING_SNAKE_CASE			  =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 							__UpperCamelCase				(       self					:      Optional[Any]  )							->     str:


										"""simple docstring"""





										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
														_SCREAMING_SNAKE_CASE			  =['''Summary of the text.''', '''Another summary.''']
														_SCREAMING_SNAKE_CASE			  =[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

														_SCREAMING_SNAKE_CASE			  =tokenizer(_a				,    padding=_a  )
														_SCREAMING_SNAKE_CASE			  =[[0] * len(_a  ) for x in encoded_output['''input_ids''']]
														_SCREAMING_SNAKE_CASE			  =tokenizer.pad(_a  )
														self.assertSequenceEqual(outputs['''global_attention_mask''']				,    _a  )




						def 							__UpperCamelCase				(       self					:      int  )							->     List[str]:


										"""simple docstring"""





										pass




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


										"""simple docstring"""





										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"  ):
																		_SCREAMING_SNAKE_CASE			  =self.rust_tokenizer_class.from_pretrained(_a				,    **_a  )
																		_SCREAMING_SNAKE_CASE			  =self.tokenizer_class.from_pretrained(_a				,    **_a  )
																		_SCREAMING_SNAKE_CASE			  ='''A, <mask> AllenNLP sentence.'''
																		_SCREAMING_SNAKE_CASE			  =tokenizer_r.encode_plus(_a				,    add_special_tokens=_a				,    return_token_type_ids=_a  )
																		_SCREAMING_SNAKE_CASE			  =tokenizer_p.encode_plus(_a				,    add_special_tokens=_a				,    return_token_type_ids=_a  )
																		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''']  )				,    )

																		_SCREAMING_SNAKE_CASE			  =tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']  )
																		_SCREAMING_SNAKE_CASE			  =tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']  )
																		self.assertSequenceEqual(tokens_p['''input_ids''']				,    [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )
																		self.assertSequenceEqual(tokens_r['''input_ids''']				,    [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]  )

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