
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


_SCREAMING_SNAKE_CASE    :      Any          =			get_tests_dir('fixtures/test_sentencepiece_no_bos.model')







@require_sentencepiece
@require_tokenizers
class  UpperCamelCase__		(    SCREAMING_SNAKE_CASE_,			unittest.TestCase   ):







	'''simple docstring'''
	_lowerCAmelCase							       =				PegasusTokenizer
	_lowerCAmelCase							       =				PegasusTokenizerFast
	_lowerCAmelCase							       =				True
	_lowerCAmelCase							       =				True





	def   __snake_case				(			self		):
							super().setUp()

							# We have a SentencePiece fixture for testing
							A__  :	List[str]         =							PegasusTokenizer(UpperCamelCase__		)
							tokenizer.save_pretrained(self.tmpdirname		)





	@cached_property
	def   __snake_case				(			self		):
							return PegasusTokenizer.from_pretrained('''google/pegasus-large'''		)





	def   __snake_case				(			self				,       **UpperCamelCase__		):
							return PegasusTokenizer.from_pretrained(self.tmpdirname				,       **UpperCamelCase__		)





	def   __snake_case				(			self				,       UpperCamelCase__		):
							return ("This is a test", "This is a test")





	def   __snake_case				(			self		):
							A__  :	List[Any]         =							'''</s>'''
							A__  :	List[Any]         =							1

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





	def   __snake_case				(			self		):
							A__  :	Optional[int]         =							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   __snake_case				(			self		):
							self.assertEqual(self.get_tokenizer().vocab_size				,       1103		)





	def   __snake_case				(			self		):
							A__  :	Tuple         =							self.rust_tokenizer_class.from_pretrained(self.tmpdirname		)
							A__  :	List[str]         =							self.tokenizer_class.from_pretrained(self.tmpdirname		)
							A__  :	List[Any]         =							(
							    '''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>'''
							)
							A__  :	str         =							rust_tokenizer([raw_input_str]				,       return_tensors=UpperCamelCase__				,       add_special_tokens=UpperCamelCase__		).input_ids[0]
							A__  :	List[str]         =							py_tokenizer([raw_input_str]				,       return_tensors=UpperCamelCase__				,       add_special_tokens=UpperCamelCase__		).input_ids[0]
							self.assertListEqual(UpperCamelCase__				,       UpperCamelCase__		)





	def   __snake_case				(			self		):
							A__  :	List[str]         =							self._large_tokenizer
							# <mask_1> masks whole sentence while <mask_2> masks single word
							A__  :	List[str]         =							'''<mask_1> To ensure a <mask_2> flow of bank resolutions.'''
							A__  :	List[Any]         =							[2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
							A__  :	Union[str, Any]         =							tokenizer([raw_input_str]				,       return_tensors=UpperCamelCase__		).input_ids[0]
							self.assertListEqual(UpperCamelCase__				,       UpperCamelCase__		)





	def   __snake_case				(			self		):
							A__  :	Any         =							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
							A__  :	List[Any]         =							'''To ensure a smooth flow of bank resolutions.'''
							A__  :	Union[str, Any]         =							[413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
							A__  :	List[str]         =							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   __snake_case				(			self		):
							A__  :	Union[str, Any]         =							['''This is going to be way too long.''' * 150, '''short example''']
							A__  :	Tuple         =							['''not super long but more than 5 tokens''', '''tiny''']
							A__  :	Tuple         =							self._large_tokenizer(UpperCamelCase__				,       padding=UpperCamelCase__				,       truncation=UpperCamelCase__				,       return_tensors='''pt'''		)
							A__  :	Any         =							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   __snake_case				(			self		):
							# fmt: off
							A__  :	Optional[Any]         =							{'''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  UpperCamelCase__		(    SCREAMING_SNAKE_CASE_,			unittest.TestCase   ):







	'''simple docstring'''
	_lowerCAmelCase							       =				PegasusTokenizer
	_lowerCAmelCase							       =				PegasusTokenizerFast
	_lowerCAmelCase							       =				True
	_lowerCAmelCase							       =				True





	def   __snake_case				(			self		):
							super().setUp()

							# We have a SentencePiece fixture for testing
							A__  :	Optional[int]         =							PegasusTokenizer(UpperCamelCase__				,       offset=0				,       mask_token_sent=UpperCamelCase__				,       mask_token='''[MASK]'''		)
							tokenizer.save_pretrained(self.tmpdirname		)





	@cached_property
	def   __snake_case				(			self		):
							return PegasusTokenizer.from_pretrained('''google/bigbird-pegasus-large-arxiv'''		)





	def   __snake_case				(			self				,       **UpperCamelCase__		):
							return PegasusTokenizer.from_pretrained(self.tmpdirname				,       **UpperCamelCase__		)





	def   __snake_case				(			self				,       UpperCamelCase__		):
							return ("This is a test", "This is a test")





	def   __snake_case				(			self		):
							A__  :	Any         =							self.rust_tokenizer_class.from_pretrained(self.tmpdirname		)
							A__  :	Tuple         =							self.tokenizer_class.from_pretrained(self.tmpdirname		)
							A__  :	Tuple         =							(
							    '''Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'''
							    ''' <pad> <pad> <pad>'''
							)
							A__  :	List[str]         =							rust_tokenizer([raw_input_str]				,       return_tensors=UpperCamelCase__				,       add_special_tokens=UpperCamelCase__		).input_ids[0]
							A__  :	str         =							py_tokenizer([raw_input_str]				,       return_tensors=UpperCamelCase__				,       add_special_tokens=UpperCamelCase__		).input_ids[0]
							self.assertListEqual(UpperCamelCase__				,       UpperCamelCase__		)





	@require_torch
	def   __snake_case				(			self		):
							A__  :	Dict         =							['''This is going to be way too long.''' * 1000, '''short example''']
							A__  :	str         =							['''not super long but more than 5 tokens''', '''tiny''']
							A__  :	List[Any]         =							self._large_tokenizer(UpperCamelCase__				,       padding=UpperCamelCase__				,       truncation=UpperCamelCase__				,       return_tensors='''pt'''		)
							A__  :	Dict         =							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   __snake_case				(			self		):
							A__  :	Tuple         =							(
							    '''This is an example string that is used to test the original TF implementation against the HF'''
							    ''' implementation'''
							)

							A__  :	List[str]         =							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]				,       )

import numpy as np

_SCREAMING_SNAKE_CASE    :      Any          =			[
    ['a', 'b', 'c', 'd', 'e'],
    ['f', 'g', 'h', 'i', 'k'],
    ['l', 'm', 'n', 'o', 'p'],
    ['q', 'r', 's', 't', 'u'],
    ['v', 'w', 'x', 'y', 'z'],
]







class  UpperCamelCase__		:







	'''simple docstring'''





	def __init__(			self		):
					A__  :	List[Any]         =							np.array(UpperCamelCase__		)





	def   __snake_case				(			self				,       UpperCamelCase__		):
					A__       ,							A__  :	Any         =							np.where(letter == self.SQUARE		)
					A__  :	int         =							np.concatenate([indexa + 1, indexa + 1]		)
					return indexes





	def   __snake_case				(			self				,       UpperCamelCase__				,       UpperCamelCase__		):
					A__  :	Union[str, Any]         =							self.SQUARE[indexa - 1, indexa - 1]
					return letter





	def   __snake_case				(			self				,       UpperCamelCase__		):
					A__  :	List[str]         =							message.lower()
					A__  :	str         =							message.replace(''' '''				,       ''''''		)
					A__  :	Union[str, Any]         =							message.replace('''j'''				,       '''i'''		)

					A__  :	List[Any]         =							np.empty((2, len(UpperCamelCase__		))		)
					for letter_index in range(len(UpperCamelCase__		)		):
									A__  :	Any         =							self.letter_to_numbers(message[letter_index]		)

									A__  :	Optional[Any]         =							numbers[0]
									A__  :	List[str]         =							numbers[1]

					A__  :	List[str]         =							first_step.reshape(2 * len(UpperCamelCase__		)		)
					A__  :	List[Any]         =							''''''
					for numbers_index in range(len(UpperCamelCase__		)		):
									A__  :	Dict         =							int(second_step[numbers_index * 2]		)
									A__  :	List[str]         =							int(second_step[(numbers_index * 2) + 1]		)
									A__  :	Dict         =							self.numbers_to_letter(UpperCamelCase__				,       UpperCamelCase__		)
									A__  :	Tuple         =							encoded_message + letter

					return encoded_message





	def   __snake_case				(			self				,       UpperCamelCase__		):
					A__  :	str         =							message.lower()
					message.replace(''' '''				,       ''''''		)
					A__  :	List[Any]         =							np.empty(2 * len(UpperCamelCase__		)		)
					for letter_index in range(len(UpperCamelCase__		)		):
									A__  :	List[str]         =							self.letter_to_numbers(message[letter_index]		)
									A__  :	Dict         =							numbers[0]
									A__  :	int         =							numbers[1]

					A__  :	Optional[Any]         =							first_step.reshape((2, len(UpperCamelCase__		))		)
					A__  :	int         =							''''''
					for numbers_index in range(len(UpperCamelCase__		)		):
									A__  :	Tuple         =							int(second_step[0, numbers_index]		)
									A__  :	Dict         =							int(second_step[1, numbers_index]		)
									A__  :	List[str]         =							self.numbers_to_letter(UpperCamelCase__				,       UpperCamelCase__		)
									A__  :	Tuple         =							decoded_message + letter

					return decoded_message