


'''simple docstring'''

import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowercase__				     =		"▁"

lowercase__				     =		get_tests_dir("fixtures/test_sentencepiece.model")





@require_sentencepiece
class 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ,			unittest.TestCase ):
     UpperCAmelCase 					=				BertGenerationTokenizer
     UpperCAmelCase 					=				False
     UpperCAmelCase 					=				True






     def  a_					(			self		)       ->    Union[str, Any]:
          super().setUp()

          _a						=		BertGenerationTokenizer(__UpperCamelCase     ,							keep_accents=__UpperCamelCase		)
          tokenizer.save_pretrained(self.tmpdirname		)






     def  a_					(			self		)       ->    List[str]:
          _a						=		"<s>"
          _a						=		1

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






     def  a_					(			self		)       ->    Union[str, Any]:
          _a						=		list(self.get_tokenizer().get_vocab().keys()		)

          self.assertEqual(vocab_keys[0]     ,							"<unk>"		)
          self.assertEqual(vocab_keys[1]     ,							"<s>"		)
          self.assertEqual(vocab_keys[-1]     ,							"<pad>"		)
          self.assertEqual(len(__UpperCamelCase		)     ,							1_002		)






     def  a_					(			self		)       ->    List[Any]:
          self.assertEqual(self.get_tokenizer().vocab_size     ,							1_000		)






     def  a_					(			self		)       ->    Optional[int]:
          _a						=		BertGenerationTokenizer(__UpperCamelCase     ,							keep_accents=__UpperCamelCase		)

          _a						=		tokenizer.tokenize("This is a test"		)
          self.assertListEqual(__UpperCamelCase     ,							["▁This", "▁is", "▁a", "▁t", "est"]		)

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(__UpperCamelCase		)     ,							[285, 46, 10, 170, 382]     ,							)

          _a						=		tokenizer.tokenize("I was born in 92000, and this is falsé."		)
          self.assertListEqual(
              __UpperCamelCase     ,							[
                  SPIECE_UNDERLINE + "I",
                  SPIECE_UNDERLINE + "was",
                  SPIECE_UNDERLINE + "b",
                  "or",
                  "n",
                  SPIECE_UNDERLINE + "in",
                  SPIECE_UNDERLINE + "",
                  "9",
                  "2",
                  "0",
                  "0",
                  "0",
                  ",",
                  SPIECE_UNDERLINE + "and",
                  SPIECE_UNDERLINE + "this",
                  SPIECE_UNDERLINE + "is",
                  SPIECE_UNDERLINE + "f",
                  "al",
                  "s",
                  "é",
                  ".",
              ]     ,							)
          _a						=		tokenizer.convert_tokens_to_ids(__UpperCamelCase		)
          self.assertListEqual(
              __UpperCamelCase     ,							[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]     ,							)

          _a						=		tokenizer.convert_ids_to_tokens(__UpperCamelCase		)
          self.assertListEqual(
              __UpperCamelCase     ,							[
                  SPIECE_UNDERLINE + "I",
                  SPIECE_UNDERLINE + "was",
                  SPIECE_UNDERLINE + "b",
                  "or",
                  "n",
                  SPIECE_UNDERLINE + "in",
                  SPIECE_UNDERLINE + "",
                  "<unk>",
                  "2",
                  "0",
                  "0",
                  "0",
                  ",",
                  SPIECE_UNDERLINE + "and",
                  SPIECE_UNDERLINE + "this",
                  SPIECE_UNDERLINE + "is",
                  SPIECE_UNDERLINE + "f",
                  "al",
                  "s",
                  "<unk>",
                  ".",
              ]     ,							)






     @cached_property
     def  a_					(			self		)       ->    Union[str, Any]:
          return BertGenerationTokenizer.from_pretrained("google/bert_for_seq_generation_L-24_bbc_encoder"		)






     @slow
     def  a_					(			self		)       ->    Dict:
          _a						=		"Hello World!"
          _a						=		[18_536, 2_260, 101]

          self.assertListEqual(__UpperCamelCase     ,							self.big_tokenizer.encode(__UpperCamelCase		)		)






     @slow
     def  a_					(			self		)       ->    Dict:
          _a						=		(
              "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
              " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
          )
          _a						=		[
              871,
              419,
              358,
              946,
              991,
              2_521,
              452,
              358,
              1_357,
              387,
              7_751,
              3_536,
              112,
              985,
              456,
              126,
              865,
              938,
              5_400,
              5_734,
              458,
              1_368,
              467,
              786,
              2_462,
              5_246,
              1_159,
              633,
              865,
              4_519,
              457,
              582,
              852,
              2_557,
              427,
              916,
              508,
              405,
              34_324,
              497,
              391,
              408,
              11_342,
              1_244,
              385,
              100,
              938,
              985,
              456,
              574,
              362,
              12_597,
              3_200,
              3_129,
              1_172,
          ]

          self.assertListEqual(__UpperCamelCase     ,							self.big_tokenizer.encode(__UpperCamelCase		)		)






     @require_torch
     @slow
     def  a_					(			self		)       ->    Union[str, Any]:
          import torch

          from transformers import BertGenerationConfig, BertGenerationEncoder

          # Build sequence
          _a						=		list(self.big_tokenizer.get_vocab().keys()		)[:10]
          _a						=		" ".join(__UpperCamelCase		)
          _a						=		self.big_tokenizer.encode_plus(__UpperCamelCase     ,							return_tensors="pt"     ,							return_token_type_ids=__UpperCamelCase		)
          _a						=		self.big_tokenizer.batch_encode_plus(
              [sequence + " " + sequence]     ,							return_tensors="pt"     ,							return_token_type_ids=__UpperCamelCase		)

          _a						=		BertGenerationConfig()
          _a						=		BertGenerationEncoder(__UpperCamelCase		)

          assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

          with torch.no_grad():
               model(**__UpperCamelCase		)
               model(**__UpperCamelCase		)






     @slow
     def  a_					(			self		)       ->    List[str]:
          # fmt: off
          _a						=		{"input_ids": [[39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114], [448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 114, 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], [484, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 114, 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, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0], [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, 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/bert_for_seq_generation_L-24_bbc_encoder"     ,							revision="c817d1fd1be2ffa69431227a1fe320544943d4db"     ,							)





'''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))

