



'''simple docstring'''






import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class     __snake_case		(   UpperCamelCase__    ,   unittest.TestCase):
					_lowerCAmelCase			     =	RobertaTokenizer
					_lowerCAmelCase			     =	RobertaTokenizerFast
					_lowerCAmelCase			     =	True
					_lowerCAmelCase			     =	{'''cls_token''': '''<s>'''}
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									super().setUp()

									# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
									lowerCamelCase					:			List[Any]									= [
									    'l',
									    'o',
									    'w',
									    'e',
									    'r',
									    's',
									    't',
									    'i',
									    'd',
									    'n',
									    '\u0120',
									    '\u0120l',
									    '\u0120n',
									    '\u0120lo',
									    '\u0120low',
									    'er',
									    '\u0120lowest',
									    '\u0120newer',
									    '\u0120wider',
									    '<unk>',
									]
									lowerCamelCase					:			Any									= dict(zip(__A,    range(len(__A      )      )      )      )
									lowerCamelCase					:			Any									= ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
									lowerCamelCase					:			int									= {'unk_token': '<unk>'}

									lowerCamelCase					:			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(__A      ) + '\n'      )
									with open(self.merges_file,    'w',    encoding='utf-8'      ) as fp:
													fp.write('\n'.join(__A      )      )
					def     UpperCAmelCase_							(     self,    **A      ):

									"""simple docstring"""


									kwargs.update(self.special_tokens_map      )
									return self.tokenizer_class.from_pretrained(self.tmpdirname,    **__A      )
					def     UpperCAmelCase_							(     self,    **A      ):

									"""simple docstring"""


									kwargs.update(self.special_tokens_map      )
									return RobertaTokenizerFast.from_pretrained(self.tmpdirname,    **__A      )
					def     UpperCAmelCase_							(     self,    A      ):

									"""simple docstring"""


									lowerCamelCase					:			List[Any]									= 'lower newer'
									lowerCamelCase					:			List[str]									= 'lower newer'
									return input_text, output_text
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Tuple									= self.tokenizer_class(self.vocab_file,    self.merges_file,    **self.special_tokens_map      )
									lowerCamelCase					:			List[str]									= 'lower newer'
									lowerCamelCase					:			List[Any]									= ['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
									lowerCamelCase					:			str									= tokenizer.tokenize(__A      )  # , add_prefix_space=True)
									self.assertListEqual(__A,    __A      )

									lowerCamelCase					:			List[Any]									= tokens + [tokenizer.unk_token]
									lowerCamelCase					:			str									= [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(__A      ),    __A      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Union[str, Any]									= self.get_tokenizer()

									self.assertListEqual(tokenizer.encode('Hello world!',    add_special_tokens=__A      ),    [0, 3_1414, 232, 328, 2]      )
									self.assertListEqual(
									    tokenizer.encode('Hello world! cécé herlolip 418',    add_special_tokens=__A      ),    [0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2],    )
					@slow
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Union[str, Any]									= self.tokenizer_class.from_pretrained('roberta-base'      )

									lowerCamelCase					:			List[Any]									= tokenizer.encode('sequence builders',    add_special_tokens=__A      )
									lowerCamelCase					:			Dict									= tokenizer.encode('multi-sequence build',    add_special_tokens=__A      )

									lowerCamelCase					:			List[Any]									= tokenizer.encode(
									    'sequence builders',    add_special_tokens=__A,    add_prefix_space=__A      )
									lowerCamelCase					:			str									= tokenizer.encode(
									    'sequence builders',    'multi-sequence build',    add_special_tokens=__A,    add_prefix_space=__A      )

									lowerCamelCase					:			Tuple									= tokenizer.build_inputs_with_special_tokens(__A      )
									lowerCamelCase					:			Tuple									= tokenizer.build_inputs_with_special_tokens(__A,    __A      )

									assert encoded_sentence == encoded_text_from_decode
									assert encoded_pair == encoded_pair_from_decode
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			Tuple									= self.get_tokenizer()

									lowerCamelCase					:			Tuple									= 'Encode this sequence.'
									lowerCamelCase					:			str									= tokenizer.byte_encoder[' '.encode('utf-8'      )[0]]

									# Testing encoder arguments
									lowerCamelCase					:			Any									= tokenizer.encode(__A,    add_special_tokens=__A,    add_prefix_space=__A      )
									lowerCamelCase					:			Dict									= tokenizer.convert_ids_to_tokens(encoded[0]      )[0]
									self.assertNotEqual(__A,    __A      )

									lowerCamelCase					:			int									= tokenizer.encode(__A,    add_special_tokens=__A,    add_prefix_space=__A      )
									lowerCamelCase					:			Tuple									= tokenizer.convert_ids_to_tokens(encoded[0]      )[0]
									self.assertEqual(__A,    __A      )

									tokenizer.add_special_tokens({'bos_token': '<s>'}      )
									lowerCamelCase					:			Dict									= tokenizer.encode(__A,    add_special_tokens=__A      )
									lowerCamelCase					:			List[Any]									= tokenizer.convert_ids_to_tokens(encoded[1]      )[0]
									self.assertNotEqual(__A,    __A      )

									# Testing spaces after special tokens
									lowerCamelCase					:			Tuple									= '<mask>'
									tokenizer.add_special_tokens(
									    {'mask_token': AddedToken(__A,    lstrip=__A,    rstrip=__A      )}      )  # mask token has a left space
									lowerCamelCase					:			List[str]									= tokenizer.convert_tokens_to_ids(__A      )

									lowerCamelCase					:			Optional[Any]									= 'Encode <mask> sequence'
									lowerCamelCase					:			List[str]									= 'Encode <mask>sequence'

									lowerCamelCase					:			List[Any]									= tokenizer.encode(__A      )
									lowerCamelCase					:			str									= encoded.index(__A      )
									lowerCamelCase					:			Optional[int]									= tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]      )[0]
									self.assertEqual(__A,    __A      )

									lowerCamelCase					:			Tuple									= tokenizer.encode(__A      )
									lowerCamelCase					:			Optional[int]									= encoded.index(__A      )
									lowerCamelCase					:			List[str]									= tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]      )[0]
									self.assertNotEqual(__A,    __A      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									pass
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
																	lowerCamelCase					:			Union[str, Any]									= self.rust_tokenizer_class.from_pretrained(__A,    **__A      )
																	lowerCamelCase					:			List[Any]									= self.tokenizer_class.from_pretrained(__A,    **__A      )
																	lowerCamelCase					:			List[Any]									= 'A, <mask> AllenNLP sentence.'
																	lowerCamelCase					:			int									= tokenizer_r.encode_plus(__A,    add_special_tokens=__A,    return_token_type_ids=__A      )
																	lowerCamelCase					:			Optional[int]									= tokenizer_p.encode_plus(__A,    add_special_tokens=__A,    return_token_type_ids=__A      )

																	# token_type_ids should put 0 everywhere
																	self.assertEqual(sum(tokens_r['token_type_ids']      ),    sum(tokens_p['token_type_ids']      )      )

																	# attention_mask should put 1 everywhere, so sum over length should be 1
																	self.assertEqual(
																	    sum(tokens_r['attention_mask']      ) / len(tokens_r['attention_mask']      ),    sum(tokens_p['attention_mask']      ) / len(tokens_p['attention_mask']      ),    )

																	lowerCamelCase					:			List[str]									= tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']      )
																	lowerCamelCase					:			str									= tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids']      )

																	# Rust correctly handles the space before the mask while python doesnt
																	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>']      )
					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									for trim_offsets, add_prefix_space in itertools.product([True, False],    repeat=2      ):
													lowerCamelCase					:			Tuple									= self.rust_tokenizer_class.from_pretrained(
													    self.tmpdirname,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )

													lowerCamelCase					:			Union[str, Any]									= json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()      )
													lowerCamelCase					:			str									= json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()      )

													self.assertEqual(pre_tokenizer_state['add_prefix_space'],    __A      )

													self.assertEqual(post_processor_state['add_prefix_space'],    __A      )
													self.assertEqual(post_processor_state['trim_offsets'],    __A      )




					def     UpperCAmelCase_							(     self      ):

									"""simple docstring"""


									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
																	lowerCamelCase					:			Dict									= 'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
																	lowerCamelCase					:			List[str]									= F'''{text_of_1_token} {text_of_1_token}'''

																	lowerCamelCase					:			Any									= self.rust_tokenizer_class.from_pretrained(
																	    __A,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )
																	lowerCamelCase					:			Any									= tokenizer_r(__A,    return_offsets_mapping=__A,    add_special_tokens=__A      )
																	self.assertEqual(encoding.offset_mapping[0],    (0, len(__A      ))      )
																	self.assertEqual(
																	    encoding.offset_mapping[1],    (len(__A      ) + 1, len(__A      ) + 1 + len(__A      )),    )

																	lowerCamelCase					:			str									= self.rust_tokenizer_class.from_pretrained(
																	    __A,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )
																	lowerCamelCase					:			List[str]									= tokenizer_r(__A,    return_offsets_mapping=__A,    add_special_tokens=__A      )
																	self.assertEqual(encoding.offset_mapping[0],    (0, len(__A      ))      )
																	self.assertEqual(
																	    encoding.offset_mapping[1],    (len(__A      ) + 1, len(__A      ) + 1 + len(__A      )),    )

																	lowerCamelCase					:			List[Any]									= self.rust_tokenizer_class.from_pretrained(
																	    __A,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )
																	lowerCamelCase					:			List[Any]									= tokenizer_r(__A,    return_offsets_mapping=__A,    add_special_tokens=__A      )
																	self.assertEqual(encoding.offset_mapping[0],    (0, len(__A      ))      )
																	self.assertEqual(
																	    encoding.offset_mapping[1],    (len(__A      ), len(__A      ) + 1 + len(__A      )),    )

																	lowerCamelCase					:			Any									= self.rust_tokenizer_class.from_pretrained(
																	    __A,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )
																	lowerCamelCase					:			str									= tokenizer_r(__A,    return_offsets_mapping=__A,    add_special_tokens=__A      )
																	self.assertEqual(encoding.offset_mapping[0],    (0, len(__A      ))      )
																	self.assertEqual(
																	    encoding.offset_mapping[1],    (len(__A      ), len(__A      ) + 1 + len(__A      )),    )

																	lowerCamelCase					:			Dict									= F''' {text}'''

																	# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																	#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																	# )
																	# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																	# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																	# self.assertEqual(
																	#     encoding.offset_mapping[1],
																	#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																	# )

																	lowerCamelCase					:			Optional[Any]									= self.rust_tokenizer_class.from_pretrained(
																	    __A,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )
																	lowerCamelCase					:			str									= tokenizer_r(__A,    return_offsets_mapping=__A,    add_special_tokens=__A      )
																	self.assertEqual(encoding.offset_mapping[0],    (1, 1 + len(__A      ))      )
																	self.assertEqual(
																	    encoding.offset_mapping[1],    (1 + len(__A      ) + 1, 1 + len(__A      ) + 1 + len(__A      )),    )

																	lowerCamelCase					:			int									= self.rust_tokenizer_class.from_pretrained(
																	    __A,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )
																	lowerCamelCase					:			Dict									= tokenizer_r(__A,    return_offsets_mapping=__A,    add_special_tokens=__A      )
																	self.assertEqual(encoding.offset_mapping[0],    (0, 1 + len(__A      ))      )
																	self.assertEqual(
																	    encoding.offset_mapping[1],    (1 + len(__A      ), 1 + len(__A      ) + 1 + len(__A      )),    )

																	lowerCamelCase					:			Tuple									= self.rust_tokenizer_class.from_pretrained(
																	    __A,    use_fast=__A,    add_prefix_space=__A,    trim_offsets=__A      )
																	lowerCamelCase					:			Optional[int]									= tokenizer_r(__A,    return_offsets_mapping=__A,    add_special_tokens=__A      )
																	self.assertEqual(encoding.offset_mapping[0],    (0, 1 + len(__A      ))      )
																	self.assertEqual(
																	    encoding.offset_mapping[1],    (1 + len(__A      ), 1 + len(__A      ) + 1 + len(__A      )),    )


'''simple docstring'''






import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
A			      =      {
    'E': 12.70,
    'T': 9.06,
    'A': 8.17,
    'O': 7.51,
    'I': 6.97,
    'N': 6.75,
    'S': 6.33,
    'H': 6.09,
    'R': 5.99,
    'D': 4.25,
    'L': 4.03,
    'C': 2.78,
    'U': 2.76,
    'M': 2.41,
    'W': 2.36,
    'F': 2.23,
    'G': 2.02,
    'Y': 1.97,
    'P': 1.93,
    'B': 1.29,
    'V': 0.98,
    'K': 0.77,
    'J': 0.15,
    'X': 0.15,
    'Q': 0.10,
    'Z': 0.07,
}
A			      =      'ETAOINSHRDLCUMWFGYPBVKJXQZ'
A			      =      'ABCDEFGHIJKLMNOPQRSTUVWXYZ'





def    UpperCAmelCase							(  UpperCAmelCase__							:							str):
				lowerCamelCase					:			Optional[Any]									= {letter: 0 for letter in string.ascii_uppercase}
				for letter in message.upper():
								if letter in LETTERS:
												letter_count[letter] += 1

				return letter_count





def    UpperCAmelCase							(  UpperCAmelCase__							:							tuple):
				return x[0]





def    UpperCAmelCase							(  UpperCAmelCase__							:							str):
				lowerCamelCase					:			Optional[Any]									= get_letter_count(UpperCAmelCase__)
				lowerCamelCase					:			dict[int, list[str]]									= {
				    freq: [] for letter, freq in letter_to_freq.items()
				}
				for letter in LETTERS:
								freq_to_letter[letter_to_freq[letter]].append(UpperCAmelCase__)

				lowerCamelCase					:			dict[int, str]									= {}

				for freq in freq_to_letter:
								freq_to_letter[freq].sort(key=ETAOIN.find       ,							reverse=UpperCAmelCase__)
								lowerCamelCase					:			int									= ''.join(freq_to_letter[freq])

				lowerCamelCase					:			Any									= list(freq_to_letter_str.items())
				freq_pairs.sort(key=UpperCAmelCase__       ,							reverse=UpperCAmelCase__)

				lowerCamelCase					:			list[str]									= [freq_pair[1] for freq_pair in freq_pairs]

				return "".join(UpperCAmelCase__)





def    UpperCAmelCase							(  UpperCAmelCase__							:							str):
				lowerCamelCase					:			Optional[Any]									= get_frequency_order(UpperCAmelCase__)
				lowerCamelCase					:			Optional[Any]									= 0
				for common_letter in ETAOIN[:6]:
								if common_letter in freq_order[:6]:
												match_score += 1

				for uncommon_letter in ETAOIN[-6:]:
								if uncommon_letter in freq_order[-6:]:
												match_score += 1

				return match_score


if __name__ == "__main__":
					import doctest

					doctest.testmod()
