


'''simple docstring'''

import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ,			unittest.TestCase ):
     UpperCAmelCase 					=				OpenAIGPTTokenizer
     UpperCAmelCase 					=				OpenAIGPTTokenizerFast
     UpperCAmelCase 					=				True
     UpperCAmelCase 					=				False






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

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          _a						=		[
              "l",
              "o",
              "w",
              "e",
              "r",
              "s",
              "t",
              "i",
              "d",
              "n",
              "w</w>",
              "r</w>",
              "t</w>",
              "lo",
              "low",
              "er</w>",
              "low</w>",
              "lowest</w>",
              "newer</w>",
              "wider</w>",
              "<unk>",
          ]
          _a						=		dict(zip(__UpperCamelCase     ,							range(len(__UpperCamelCase		)		)		)		)
          _a						=		["#version: 0.2", "l o", "lo w", "e r</w>", ""]

          _a						=		os.path.join(self.tmpdirname     ,							VOCAB_FILES_NAMES["vocab_file"]		)
          _a						=		os.path.join(self.tmpdirname     ,							VOCAB_FILES_NAMES["merges_file"]		)
          with open(self.vocab_file     ,							"w"		) as fp:
               fp.write(json.dumps(__UpperCamelCase		)		)
          with open(self.merges_file     ,							"w"		) as fp:
               fp.write("\n".join(__UpperCamelCase		)		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Tuple:
          return "lower newer", "lower newer"






     def  a_					(			self		)       ->    str:
          _a						=		OpenAIGPTTokenizer(self.vocab_file     ,							self.merges_file		)

          _a						=		"lower"
          _a						=		["low", "er</w>"]
          _a						=		tokenizer.tokenize(__UpperCamelCase		)
          self.assertListEqual(__UpperCamelCase     ,							__UpperCamelCase		)

          _a						=		tokens + ["<unk>"]
          _a						=		[14, 15, 20]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase		)     ,							__UpperCamelCase		)






     def  a_					(			self     ,							__UpperCamelCase=15		)       ->    Any:
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"		):
                    _a						=		self.rust_tokenizer_class.from_pretrained(__UpperCamelCase     ,							**__UpperCamelCase		)

                    # Simple input
                    _a						=		"This is a simple input"
                    _a						=		["This is a simple input 1", "This is a simple input 2"]
                    _a						=		("This is a simple input", "This is a pair")
                    _a						=		[
                        ("This is a simple input 1", "This is a simple input 2"),
                        ("This is a simple pair 1", "This is a simple pair 2"),
                    ]

                    # Simple input tests
                    self.assertRaises(__UpperCamelCase     ,							tokenizer_r.encode     ,							__UpperCamelCase     ,							max_length=__UpperCamelCase     ,							padding="max_length"		)

                    # Simple input
                    self.assertRaises(__UpperCamelCase     ,							tokenizer_r.encode_plus     ,							__UpperCamelCase     ,							max_length=__UpperCamelCase     ,							padding="max_length"		)

                    # Simple input
                    self.assertRaises(
                        __UpperCamelCase     ,							tokenizer_r.batch_encode_plus     ,							__UpperCamelCase     ,							max_length=__UpperCamelCase     ,							padding="max_length"     ,							)

                    # Pair input
                    self.assertRaises(__UpperCamelCase     ,							tokenizer_r.encode     ,							__UpperCamelCase     ,							max_length=__UpperCamelCase     ,							padding="max_length"		)

                    # Pair input
                    self.assertRaises(__UpperCamelCase     ,							tokenizer_r.encode_plus     ,							__UpperCamelCase     ,							max_length=__UpperCamelCase     ,							padding="max_length"		)

                    # Pair input
                    self.assertRaises(
                        __UpperCamelCase     ,							tokenizer_r.batch_encode_plus     ,							__UpperCamelCase     ,							max_length=__UpperCamelCase     ,							padding="max_length"     ,							)






     def  a_					(			self		)       ->    Optional[int]:
          pass







@require_ftfy
@require_spacy
@require_tokenizers
class 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ):
     pass





'''simple docstring'''

from math import factorial, pi






def __UpperCamelCase   (			__lowerCamelCase		: float      ,  __lowerCamelCase		: int = 30				)      ->     float:







     '''simple docstring'''






     if not isinstance(__lowerCamelCase      ,  (int, float)				):
          raise ValueError("maclaurin_sin() requires either an int or float for theta"				)

     if not isinstance(__lowerCamelCase      ,  __lowerCamelCase				) or accuracy <= 0:
          raise ValueError("maclaurin_sin() requires a positive int for accuracy"				)

     _a						=		float(__lowerCamelCase				)
     _a						=		theta // (2 * pi)
     theta -= 2 * div * pi
     return sum(
         (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1				) for r in range(__lowerCamelCase				)				)






def __UpperCamelCase   (			__lowerCamelCase		: float      ,  __lowerCamelCase		: int = 30				)      ->     float:







     '''simple docstring'''






     if not isinstance(__lowerCamelCase      ,  (int, float)				):
          raise ValueError("maclaurin_cos() requires either an int or float for theta"				)

     if not isinstance(__lowerCamelCase      ,  __lowerCamelCase				) or accuracy <= 0:
          raise ValueError("maclaurin_cos() requires a positive int for accuracy"				)

     _a						=		float(__lowerCamelCase				)
     _a						=		theta // (2 * pi)
     theta -= 2 * div * pi
     return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r				) for r in range(__lowerCamelCase				)				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   print(maclaurin_sin(10))
   print(maclaurin_sin(-10))
   print(maclaurin_sin(10, 15))
   print(maclaurin_sin(-10, 15))

   print(maclaurin_cos(5))
   print(maclaurin_cos(-5))
   print(maclaurin_cos(10, 15))
   print(maclaurin_cos(-10, 15))

