





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 					A_					(   UpperCAmelCase       ,						unittest.TestCase						):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_   :			Any  			=	RobertaTokenizer
       SCREAMING_SNAKE_CASE_   :			Union[str, Any]  			=	RobertaTokenizerFast
       SCREAMING_SNAKE_CASE_   :			int  			=	True
       SCREAMING_SNAKE_CASE_   :			Any  			=	{'''cls_token''': '''<s>'''}







       def  __UpperCAmelCase			(     self						:						List[Any]	)    ->       List[str]:
         super().setUp()

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

         _lowercase						    =			os.path.join(self.tmpdirname    ,VOCAB_FILES_NAMES['vocab_file']	)
         _lowercase						    =			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						:						List[str]    ,**__A						:						List[Any]	)    ->       Union[str, Any]:
         kwargs.update(self.special_tokens_map	)
         return self.tokenizer_class.from_pretrained(self.tmpdirname    ,**__A	)







       def  __UpperCAmelCase			(     self						:						Union[str, Any]    ,**__A						:						Any	)    ->       str:
         kwargs.update(self.special_tokens_map	)
         return RobertaTokenizerFast.from_pretrained(self.tmpdirname    ,**__A	)







       def  __UpperCAmelCase			(     self						:						str    ,__A						:						List[str]	)    ->       List[Any]:
         _lowercase						    =			'lower newer'
         _lowercase						    =			'lower newer'
         return input_text, output_text







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

         _lowercase						    =			tokens + [tokenizer.unk_token]
         _lowercase						    =			[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(__A	)    ,__A	)







       def  __UpperCAmelCase			(     self						:						Dict	)    ->       Optional[int]:
         _lowercase						    =			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						:						Optional[Any]	)    ->       Optional[Any]:
         _lowercase						    =			self.tokenizer_class.from_pretrained('roberta-base'	)

         _lowercase						    =			tokenizer.encode('sequence builders'    ,add_special_tokens=__A	)
         _lowercase						    =			tokenizer.encode('multi-sequence build'    ,add_special_tokens=__A	)

         _lowercase						    =			tokenizer.encode(
             'sequence builders'    ,add_special_tokens=__A    ,add_prefix_space=__A	)
         _lowercase						    =			tokenizer.encode(
             'sequence builders'    ,'multi-sequence build'    ,add_special_tokens=__A    ,add_prefix_space=__A	)

         _lowercase						    =			tokenizer.build_inputs_with_special_tokens(__A	)
         _lowercase						    =			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						:						List[Any]	)    ->       List[Any]:
         _lowercase						    =			self.get_tokenizer()

         _lowercase						    =			'Encode this sequence.'
         _lowercase						    =			tokenizer.byte_encoder[' '.encode('utf-8'	)[0]]

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

         _lowercase						    =			tokenizer.encode(__A    ,add_special_tokens=__A    ,add_prefix_space=__A	)
         _lowercase						    =			tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
         self.assertEqual(__A    ,__A	)

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

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

         _lowercase						    =			'Encode <mask> sequence'
         _lowercase						    =			'Encode <mask>sequence'

         _lowercase						    =			tokenizer.encode(__A	)
         _lowercase						    =			encoded.index(__A	)
         _lowercase						    =			tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
         self.assertEqual(__A    ,__A	)

         _lowercase						    =			tokenizer.encode(__A	)
         _lowercase						    =			encoded.index(__A	)
         _lowercase						    =			tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
         self.assertNotEqual(__A    ,__A	)







       def  __UpperCAmelCase			(     self						:						List[Any]	)    ->       Dict:
         pass







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

             _lowercase						    =			tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']	)
             _lowercase						    =			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						:						int	)    ->       Any:
         for trim_offsets, add_prefix_space in itertools.product([True, False]    ,repeat=2	):
           _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
               self.tmpdirname    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)

           _lowercase						    =			json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()	)
           _lowercase						    =			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						:						List[str]	)    ->       List[Any]:
         # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
         # `trim_offsets`
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""	):
             _lowercase						    =			'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
             _lowercase						    =			F"""{text_of_1_token} {text_of_1_token}"""

             _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
                 __A    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)
             _lowercase						    =			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	))    ,)

             _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
                 __A    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)
             _lowercase						    =			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	))    ,)

             _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
                 __A    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)
             _lowercase						    =			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	))    ,)

             _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
                 __A    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)
             _lowercase						    =			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	))    ,)

             _lowercase						    =			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)),
             # )

             _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
                 __A    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)
             _lowercase						    =			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	))    ,)

             _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
                 __A    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)
             _lowercase						    =			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	))    ,)

             _lowercase						    =			self.rust_tokenizer_class.from_pretrained(
                 __A    ,use_fast=__A    ,add_prefix_space=__A    ,trim_offsets=__A	)
             _lowercase						    =			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	))    ,)





from __future__ import annotations

import math

__a							     =					'2020.9.26'
__a							     =					'xcodz-dot, cclaus, dhruvmanila'







def lowerCamelCase__  (     _lowercase					,		_lowercase					,		_lowercase					,		_lowercase					,		_lowercase ):

     '''simple docstring'''


     if not all(isinstance(_lowercase					,		(float, int) ) for val in locals().values() ):
          UpperCAmelCase_     :				Optional[int]  =     f'''Input values must either be float or int: {list(locals().values() )}'''
          raise TypeError(_lowercase )
     UpperCAmelCase_     :				Tuple  =     ((x * distance) / (z + distance)) * scale
     UpperCAmelCase_     :				str  =     ((y * distance) / (z + distance)) * scale
     return projected_x, projected_y







def lowerCamelCase__  (     _lowercase					,		_lowercase					,		_lowercase					,		_lowercase					,		_lowercase ):

     '''simple docstring'''


     if not isinstance(_lowercase					,		_lowercase ):
          raise TypeError('''Axis must be a str''' )
     UpperCAmelCase_     :				Optional[Any]  =     locals()
     del input_variables["axis"]
     if not all(isinstance(_lowercase					,		(float, int) ) for val in input_variables.values() ):
          UpperCAmelCase_     :				List[Any]  =     (
              '''Input values except axis must either be float or int: '''
              f'''{list(input_variables.values() )}'''
          )
          raise TypeError(_lowercase )
     UpperCAmelCase_     :				Dict  =     (angle % 360) / 450 * 180 / math.pi
     if axis == "z":
          UpperCAmelCase_     :				Optional[int]  =     x * math.cos(_lowercase ) - y * math.sin(_lowercase )
          UpperCAmelCase_     :				List[Any]  =     y * math.cos(_lowercase ) + x * math.sin(_lowercase )
          UpperCAmelCase_     :				Optional[int]  =     z
     elif axis == "x":
          UpperCAmelCase_     :				Any  =     y * math.cos(_lowercase ) - z * math.sin(_lowercase )
          UpperCAmelCase_     :				int  =     z * math.cos(_lowercase ) + y * math.sin(_lowercase )
          UpperCAmelCase_     :				Dict  =     x
     elif axis == "y":
          UpperCAmelCase_     :				Union[str, Any]  =     x * math.cos(_lowercase ) - z * math.sin(_lowercase )
          UpperCAmelCase_     :				Optional[int]  =     z * math.cos(_lowercase ) + x * math.sin(_lowercase )
          UpperCAmelCase_     :				Optional[int]  =     y
     else:
          raise ValueError('''not a valid axis, choose one of \'x\', \'y\', \'z\'''' )

     return new_x, new_y, new_z


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(F"""{convert_to_ad(1.0, 2.0, 3.0, 10.0, 10.0) = }""")
     print(F"""{rotate(1.0, 2.0, 3.0, "y", 90.0) = }""")