





import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin



class 					A__   (       __snake_case       ,   unittest.TestCase			):
      _UpperCAmelCase	:Union[str, Any]						    =   CanineTokenizer
      _UpperCAmelCase	:Optional[Any]						    =   False





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       super().setUp()
       UpperCamelCase	:					Optional[int]       	=   CanineTokenizer()
       tokenizer.save_pretrained(self.tmpdirname   )





      @cached_property
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       return CanineTokenizer.from_pretrained("google/canine-s"   )





      def        __UpperCamelCase( self       ,							**A_   ):
       '''simple docstring'''




       UpperCamelCase	:					Any       	=   self.tokenizer_class.from_pretrained(self.tmpdirname       ,							**A_   )
       UpperCamelCase	:					Tuple       	=   1024
       return tokenizer





      @require_torch
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					Union[str, Any]       	=   self.canine_tokenizer
       UpperCamelCase	:					str       	=   ["Life is like a box of chocolates.", "You never know what you're gonna get."]
       # fmt: off
       UpperCamelCase	:					List[Any]       	=   [5_7344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 5_7345, 0, 0, 0, 0]
       # fmt: on
       UpperCamelCase	:					Optional[Any]       	=   tokenizer(A_       ,							padding=A_       ,							return_tensors="pt"   )
       self.assertIsInstance(A_       ,							A_   )

       UpperCamelCase	:					Dict       	=   list(batch.input_ids.numpy()[0]   )

       self.assertListEqual(A_       ,							A_   )

       self.assertEqual((2, 39)       ,							batch.input_ids.shape   )
       self.assertEqual((2, 39)       ,							batch.attention_mask.shape   )





      @require_torch
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					Any       	=   self.canine_tokenizer
       UpperCamelCase	:					str       	=   ["Once there was a man.", "He wrote a test in HuggingFace Tranformers."]
       UpperCamelCase	:					Optional[Any]       	=   tokenizer(A_       ,							padding=A_       ,							return_tensors="pt"   )
       # check if input_ids, attention_mask and token_type_ids are returned
       self.assertIn("input_ids"       ,							A_   )
       self.assertIn("attention_mask"       ,							A_   )
       self.assertIn("token_type_ids"       ,							A_   )





      @require_torch
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					str       	=   self.canine_tokenizer
       UpperCamelCase	:					List[Any]       	=   [
           "What's the weater?",
           "It's about 25 degrees.",
       ]
       UpperCamelCase	:					Any       	=   tokenizer(
           text_target=A_       ,							max_length=32       ,							padding="max_length"       ,							truncation=A_       ,							return_tensors="pt"   )
       self.assertEqual(32       ,							targets["input_ids"].shape[1]   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					Any       	=   self.get_tokenizers()
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         self.assertNotEqual(tokenizer.model_max_length       ,							42   )

        # Now let's start the test
       UpperCamelCase	:					int       	=   self.get_tokenizers()
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         # Isolate this from the other tests because we save additional tokens/etc
         UpperCamelCase	:					Dict       	=   tempfile.mkdtemp()

         UpperCamelCase	:					Optional[Any]       	=   " He is very happy, UNwant\u00E9d,running"
         UpperCamelCase	:					Union[str, Any]       	=   tokenizer.encode(A_       ,							add_special_tokens=A_   )
         tokenizer.save_pretrained(A_   )

         UpperCamelCase	:					int       	=   tokenizer.__class__.from_pretrained(A_   )
         UpperCamelCase	:					Any       	=   after_tokenizer.encode(A_       ,							add_special_tokens=A_   )
         self.assertListEqual(A_       ,							A_   )

         shutil.rmtree(A_   )

       UpperCamelCase	:					List[str]       	=   self.get_tokenizers(model_max_length=42   )
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         # Isolate this from the other tests because we save additional tokens/etc
         UpperCamelCase	:					Union[str, Any]       	=   tempfile.mkdtemp()

         UpperCamelCase	:					List[str]       	=   " He is very happy, UNwant\u00E9d,running"

         UpperCamelCase	:					List[Any]       	=   tokenizer.additional_special_tokens

         # We can add a new special token for Canine as follows:
         UpperCamelCase	:					Dict       	=   chr(0xE_0_0_7   )
         additional_special_tokens.append(A_   )
         tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}   )
         UpperCamelCase	:					int       	=   tokenizer.encode(A_       ,							add_special_tokens=A_   )
         tokenizer.save_pretrained(A_   )

         UpperCamelCase	:					List[str]       	=   tokenizer.__class__.from_pretrained(A_   )
         UpperCamelCase	:					List[str]       	=   after_tokenizer.encode(A_       ,							add_special_tokens=A_   )
         self.assertListEqual(A_       ,							A_   )
         self.assertIn(A_       ,							after_tokenizer.additional_special_tokens   )
         self.assertEqual(after_tokenizer.model_max_length       ,							42   )

         UpperCamelCase	:					str       	=   tokenizer.__class__.from_pretrained(A_       ,							model_max_length=43   )
         self.assertEqual(tokenizer.model_max_length       ,							43   )

         shutil.rmtree(A_   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					List[Any]       	=   self.get_tokenizers(do_lower_case=A_   )
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         UpperCamelCase	,    UpperCamelCase	:					Dict       	=   self.get_clean_sequence(A_   )

         # a special token for Canine can be defined as follows:
         UpperCamelCase	:					Dict       	=   0xE_0_0_5
         UpperCamelCase	:					List[Any]       	=   chr(A_   )

         tokenizer.add_special_tokens({"cls_token": special_token}   )
         UpperCamelCase	:					Any       	=   tokenizer.encode(A_       ,							add_special_tokens=A_   )
         self.assertEqual(len(A_   )       ,							1   )

         UpperCamelCase	:					Union[str, Any]       	=   tokenizer.decode(ids + encoded_special_token       ,							clean_up_tokenization_spaces=A_   )
         UpperCamelCase	:					Optional[int]       	=   tokenizer.encode(A_       ,							add_special_tokens=A_   )

         UpperCamelCase	:					Tuple       	=   tokenizer.encode(A_       ,							add_special_tokens=A_   )
         UpperCamelCase	:					Optional[Any]       	=   tokenizer.encode(A_       ,							add_special_tokens=A_   )
         self.assertEqual(A_       ,							input_encoded + special_token_id   )

         UpperCamelCase	:					List[str]       	=   tokenizer.decode(A_       ,							skip_special_tokens=A_   )
         self.assertTrue(special_token not in decoded   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					str       	=   self.get_tokenizers(do_lower_case=A_   )
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         UpperCamelCase	:					str       	=   chr(0xE_0_0_5   )
         UpperCamelCase	:					Optional[int]       	=   chr(0xE_0_0_6   )

         # `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
         tokenizer.add_tokens([SPECIAL_TOKEN_1]       ,							special_tokens=A_   )
         # `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
         # which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
         tokenizer.add_special_tokens({"additional_special_tokens": [SPECIAL_TOKEN_2]}   )

         UpperCamelCase	:					Any       	=   tokenizer.tokenize(A_   )
         UpperCamelCase	:					List[Any]       	=   tokenizer.tokenize(A_   )

         self.assertEqual(len(A_   )       ,							1   )
         self.assertEqual(len(A_   )       ,							1   )
         self.assertEqual(token_a[0]       ,							A_   )
         self.assertEqual(token_a[0]       ,							A_   )





      @require_tokenizers
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					int       	=   self.get_tokenizers(do_lower_case=A_   )
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         # a special token for Canine can be defined as follows:
         UpperCamelCase	:					Union[str, Any]       	=   0xE_0_0_6
         UpperCamelCase	:					Tuple       	=   chr(A_   )

         UpperCamelCase	:					Optional[Any]       	=   AddedToken(A_       ,							lstrip=A_   )
         tokenizer.add_special_tokens({"additional_special_tokens": [new_token]}   )

         with tempfile.TemporaryDirectory() as tmp_dir_name:
          tokenizer.save_pretrained(A_   )
          tokenizer.from_pretrained(A_   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					Union[str, Any]       	=   []
       if self.test_slow_tokenizer:
        tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())   )

       if self.test_rust_tokenizer:
        tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())   )

       for tokenizer_class, tokenizer_utils in tokenizer_list:
        with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer_utils.save_pretrained(A_   )

         with open(os.path.join(A_       ,							"special_tokens_map.json"   )       ,							encoding="utf-8"   ) as json_file:
          UpperCamelCase	:					List[Any]       	=   json.load(A_   )

         with open(os.path.join(A_       ,							"tokenizer_config.json"   )       ,							encoding="utf-8"   ) as json_file:
          UpperCamelCase	:					Optional[int]       	=   json.load(A_   )

         # a special token for Canine can be defined as follows:
         UpperCamelCase	:					Dict       	=   0xE_0_0_6
         UpperCamelCase	:					Any       	=   chr(A_   )

         UpperCamelCase	:					Tuple       	=   [new_token_a]
         UpperCamelCase	:					Union[str, Any]       	=   [new_token_a]

         with open(os.path.join(A_       ,							"special_tokens_map.json"   )       ,							"w"       ,							encoding="utf-8"   ) as outfile:
          json.dump(A_       ,							A_   )
         with open(os.path.join(A_       ,							"tokenizer_config.json"   )       ,							"w"       ,							encoding="utf-8"   ) as outfile:
          json.dump(A_       ,							A_   )

         # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
         # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
         # "special_tokens_map.json" files
         UpperCamelCase	:					Optional[Any]       	=   tokenizer_class.from_pretrained(A_       ,							extra_ids=0   )
         self.assertIn(A_       ,							tokenizer_without_change_in_init.additional_special_tokens   )
         # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
         self.assertEqual(
             [new_token_a]       ,							tokenizer_without_change_in_init.convert_ids_to_tokens(
                 tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]   )   )       ,							)

         UpperCamelCase	:					Optional[int]       	=   0xE_0_0_7
         UpperCamelCase	:					Union[str, Any]       	=   chr(A_   )
         # Now we test that we can change the value of additional_special_tokens in the from_pretrained
         UpperCamelCase	:					List[str]       	=   [AddedToken(A_       ,							lstrip=A_   )]
         UpperCamelCase	:					Optional[int]       	=   tokenizer_class.from_pretrained(
             A_       ,							additional_special_tokens=A_       ,							extra_ids=0   )

         self.assertIn(A_       ,							tokenizer.additional_special_tokens   )
         # self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
         self.assertEqual(
             [new_token_a]       ,							tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]   )   )   )





      @require_tokenizers
      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					Optional[Any]       	=   self.get_tokenizers(do_lower_case=A_   )
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         UpperCamelCase	:					Optional[Any]       	=   "hello world"
         if self.space_between_special_tokens:
          UpperCamelCase	:					Optional[Any]       	=   "[CLS] hello world [SEP]"
         else:
          UpperCamelCase	:					Dict       	=   input
         UpperCamelCase	:					Optional[int]       	=   tokenizer.encode(A_       ,							add_special_tokens=A_   )
         UpperCamelCase	:					Tuple       	=   tokenizer.decode(A_       ,							spaces_between_special_tokens=self.space_between_special_tokens   )
         self.assertIn(A_       ,							[output, output.lower()]   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					int       	=   self.get_tokenizers()
       for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
         UpperCamelCase	:					List[str]       	=   [
             "bos_token",
             "eos_token",
             "unk_token",
             "sep_token",
             "pad_token",
             "cls_token",
             "mask_token",
         ]

       UpperCamelCase	:					Optional[int]       	=   "a"
       UpperCamelCase	:					Tuple       	=   ord(A_   )

       for attr in attributes_list:
        setattr(A_       ,							attr + "_id"       ,							A_   )
        self.assertEqual(getattr(A_       ,							A_   )       ,							A_   )
        self.assertEqual(getattr(A_       ,							attr + "_id"   )       ,							A_   )

        setattr(A_       ,							attr + "_id"       ,							A_   )
        self.assertEqual(getattr(A_       ,							A_   )       ,							A_   )
        self.assertEqual(getattr(A_       ,							attr + "_id"   )       ,							A_   )

       setattr(A_       ,							"additional_special_tokens_ids"       ,							[]   )
       self.assertListEqual(getattr(A_       ,							"additional_special_tokens"   )       ,							[]   )
       self.assertListEqual(getattr(A_       ,							"additional_special_tokens_ids"   )       ,							[]   )

       UpperCamelCase	:					Union[str, Any]       	=   0xE_0_0_6
       UpperCamelCase	:					List[Any]       	=   chr(A_   )
       setattr(A_       ,							"additional_special_tokens_ids"       ,							[additional_special_token_id]   )
       self.assertListEqual(getattr(A_       ,							"additional_special_tokens"   )       ,							[additional_special_token]   )
       self.assertListEqual(getattr(A_       ,							"additional_special_tokens_ids"   )       ,							[additional_special_token_id]   )





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       pass








from math import factorial





class 			__a  :







 def __init__(		self					:   Union[str, Any]							,   SCREAMING_SNAKE_CASE					:   Tuple							,   SCREAMING_SNAKE_CASE					:   Optional[int]						):


      '''simple docstring'''






      UpperCamelCase__			:   Tuple       				=  real
      if isinstance(SCREAMING_SNAKE_CASE							,   SCREAMING_SNAKE_CASE						):
           UpperCamelCase__			:   Union[str, Any]       				=  [1] * rank
      else:
           UpperCamelCase__			:   int       				=  rank







 def __repr__(		self					:   Tuple						):


      '''simple docstring'''






      return (
          F'{self.real}+'
          F'{"+".join(str(SCREAMING_SNAKE_CASE						)+"E"+str(n+1						)for n,dual in enumerate(self.duals						)						)}'
      )







 def 					__lowercase					(		self					:   Tuple						):


      '''simple docstring'''






      UpperCamelCase__			:   Optional[Any]       				=  self.duals.copy()
      while cur[-1] == 0:
           cur.pop(-1						)
      return Dual(self.real							,   SCREAMING_SNAKE_CASE						)







 def __add__(		self					:   Union[str, Any]							,   SCREAMING_SNAKE_CASE					:   Dict						):


      '''simple docstring'''






      if not isinstance(SCREAMING_SNAKE_CASE							,   SCREAMING_SNAKE_CASE						):
           return Dual(self.real + other							,   self.duals						)
      UpperCamelCase__			:   Optional[int]       				=  self.duals.copy()
      UpperCamelCase__			:   Any       				=  other.duals.copy()
      if len(SCREAMING_SNAKE_CASE						) > len(SCREAMING_SNAKE_CASE						):
           o_dual.extend([1] * (len(SCREAMING_SNAKE_CASE						) - len(SCREAMING_SNAKE_CASE						))						)
      elif len(SCREAMING_SNAKE_CASE						) < len(SCREAMING_SNAKE_CASE						):
           s_dual.extend([1] * (len(SCREAMING_SNAKE_CASE						) - len(SCREAMING_SNAKE_CASE						))						)
      UpperCamelCase__			:   Optional[int]       				=  []
      for i in range(len(SCREAMING_SNAKE_CASE						)						):
           new_duals.append(s_dual[i] + o_dual[i]						)
      return Dual(self.real + other.real							,   SCREAMING_SNAKE_CASE						)

 _lowerCAmelCase       :       Dict        = __add__







 def __sub__(		self					:   Tuple							,   SCREAMING_SNAKE_CASE					:   Tuple						):


      '''simple docstring'''






      return self + other * -1







 def __mul__(		self					:   int							,   SCREAMING_SNAKE_CASE					:   Dict						):


      '''simple docstring'''






      if not isinstance(SCREAMING_SNAKE_CASE							,   SCREAMING_SNAKE_CASE						):
           UpperCamelCase__			:   str       				=  []
           for i in self.duals:
                new_duals.append(i * other						)
           return Dual(self.real * other							,   SCREAMING_SNAKE_CASE						)
      UpperCamelCase__			:   List[Any]       				=  [0] * (len(self.duals						) + len(other.duals						) + 1)
      for i, item in enumerate(self.duals						):
           for j, jtem in enumerate(other.duals						):
                new_duals[i + j + 1] += item * jtem
      for k in range(len(self.duals						)						):
           new_duals[k] += self.duals[k] * other.real
      for index in range(len(other.duals						)						):
           new_duals[index] += other.duals[index] * self.real
      return Dual(self.real * other.real							,   SCREAMING_SNAKE_CASE						)

 _lowerCAmelCase       :       Union[str, Any]        = __mul__







 def __truediv__(		self					:   List[Any]							,   SCREAMING_SNAKE_CASE					:   Any						):


      '''simple docstring'''






      if not isinstance(SCREAMING_SNAKE_CASE							,   SCREAMING_SNAKE_CASE						):
           UpperCamelCase__			:   str       				=  []
           for i in self.duals:
                new_duals.append(i / other						)
           return Dual(self.real / other							,   SCREAMING_SNAKE_CASE						)
      raise ValueError







 def __floordiv__(		self					:   Union[str, Any]							,   SCREAMING_SNAKE_CASE					:   Tuple						):


      '''simple docstring'''






      if not isinstance(SCREAMING_SNAKE_CASE							,   SCREAMING_SNAKE_CASE						):
           UpperCamelCase__			:   Dict       				=  []
           for i in self.duals:
                new_duals.append(i // other						)
           return Dual(self.real // other							,   SCREAMING_SNAKE_CASE						)
      raise ValueError







 def __pow__(		self					:   str							,   SCREAMING_SNAKE_CASE					:   int						):


      '''simple docstring'''






      if n < 0 or isinstance(SCREAMING_SNAKE_CASE							,   SCREAMING_SNAKE_CASE						):
           raise ValueError("power must be a positive integer"						)
      if n == 0:
           return 1
      if n == 1:
           return self
      UpperCamelCase__			:   str       				=  self
      for _ in range(n - 1						):
           x *= self
      return x







def 		SCREAMING_SNAKE_CASE							(					__lowerCAmelCase					,    __lowerCAmelCase					,    __lowerCAmelCase			) ->	str:
     if not callable(__lowerCAmelCase			):
          raise ValueError("differentiate() requires a function as input for func"			)
     if not isinstance(__lowerCAmelCase					,    (float, int)			):
          raise ValueError("differentiate() requires a float as input for position"			)
     if not isinstance(__lowerCAmelCase					,    __lowerCAmelCase			):
          raise ValueError("differentiate() requires an int as input for order"			)
     UpperCamelCase__			:   Optional[Any]       				=  Dual(__lowerCAmelCase					,    1			)
     UpperCamelCase__			:   Any       				=  func(__lowerCAmelCase			)
     if order == 0:
          return result.real
     return result.duals[order - 1] * factorial(__lowerCAmelCase			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()







 def 		SCREAMING_SNAKE_CASE							(					__lowerCAmelCase			) ->	List[Any]:
      return y**2 * y**4




 print(differentiate(f, 9, 2))