





'''simple docstring'''




import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__SCREAMING_SNAKE_CASE     :str       =				get_tests_dir('''fixtures/test_sentencepiece.model''')







@require_sentencepiece
@require_tokenizers
class   A_	(  lowerCAmelCase_							,						unittest.TestCase			):
 _lowerCamelCase  : Any           =							ReformerTokenizer
 _lowerCamelCase  : str           =							ReformerTokenizerFast
 _lowerCamelCase  : Union[str, Any]           =							True
 _lowerCamelCase  : Union[str, Any]           =							False
 _lowerCamelCase  : Any           =							True




 def      lowercase	(					self       :    List[str]    ):
      super().setUp()

      _UpperCAmelCase     							=   ReformerTokenizer(snake_case_	,			keep_accents=snake_case_    )
      tokenizer.save_pretrained(self.tmpdirname    )




 def      lowercase	(					self       :    Dict    ):
      _UpperCAmelCase     							=   "<s>"
      _UpperCAmelCase     							=   1

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




 def      lowercase	(					self       :    Optional[int]    ):
      _UpperCAmelCase     							=   list(self.get_tokenizer().get_vocab().keys()    )

      self.assertEqual(vocab_keys[0]	,			"<unk>"    )
      self.assertEqual(vocab_keys[1]	,			"<s>"    )
      self.assertEqual(vocab_keys[-1]	,			"j"    )
      self.assertEqual(len(snake_case_    )	,			1_0_0_0    )




 def      lowercase	(					self       :    Any    ):
      self.assertEqual(self.get_tokenizer().vocab_size	,			1_0_0_0    )




 def      lowercase	(					self       :    Tuple    ):
      if not self.test_rust_tokenizer:
           return

      _UpperCAmelCase     							=   self.get_tokenizer()
      _UpperCAmelCase     							=   self.get_rust_tokenizer()

      _UpperCAmelCase     							=   "I was born in 92000, and this is falsé."

      _UpperCAmelCase     							=   tokenizer.tokenize(snake_case_    )
      _UpperCAmelCase     							=   rust_tokenizer.tokenize(snake_case_    )
      self.assertListEqual(snake_case_	,			snake_case_    )

      _UpperCAmelCase     							=   tokenizer.encode(snake_case_	,			add_special_tokens=snake_case_    )
      _UpperCAmelCase     							=   rust_tokenizer.encode(snake_case_	,			add_special_tokens=snake_case_    )
      self.assertListEqual(snake_case_	,			snake_case_    )

      _UpperCAmelCase     							=   self.get_rust_tokenizer()
      _UpperCAmelCase     							=   tokenizer.encode(snake_case_    )
      _UpperCAmelCase     							=   rust_tokenizer.encode(snake_case_    )
      self.assertListEqual(snake_case_	,			snake_case_    )




 def      lowercase	(					self       :    Optional[Any]	,			snake_case_       :    Dict=1_5    ):
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'    ):
                _UpperCAmelCase     							=   self.rust_tokenizer_class.from_pretrained(snake_case_	,			**snake_case_    )

                # Simple input
                _UpperCAmelCase     							=   "This is a simple input"
                _UpperCAmelCase     							=   ["This is a simple input 1", "This is a simple input 2"]
                _UpperCAmelCase     							=   ("This is a simple input", "This is a pair")
                _UpperCAmelCase     							=   [
                    ("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(snake_case_	,			tokenizer_r.encode	,			snake_case_	,			max_length=snake_case_	,			padding="max_length"    )

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

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

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

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

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




 def      lowercase	(					self       :    List[str]    ):
      pass




 def      lowercase	(					self       :    List[Any]    ):
      _UpperCAmelCase     							=   ReformerTokenizer(snake_case_	,			keep_accents=snake_case_    )

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

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(snake_case_    )	,			[2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]	,			)

      _UpperCAmelCase     							=   tokenizer.tokenize("I was born in 92000, and this is falsé."    )
      self.assertListEqual(
          snake_case_	,			[
              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",
              ".",
          ]	,			)
      _UpperCAmelCase     							=   tokenizer.convert_tokens_to_ids(snake_case_    )
      self.assertListEqual(
          snake_case_	,			[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]	,			)

      _UpperCAmelCase     							=   tokenizer.convert_ids_to_tokens(snake_case_    )
      self.assertListEqual(
          snake_case_	,			[
              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      lowercase	(					self       :    int    ):
      return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment"    )




 @slow
 def      lowercase	(					self       :    List[Any]    ):
      _UpperCAmelCase     							=   "Hello World!"
      _UpperCAmelCase     							=   [1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

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




 @slow
 def      lowercase	(					self       :    Tuple    ):
      _UpperCAmelCase     							=   (
          "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"
      )
      _UpperCAmelCase     							=   [
          1_0_8,
          2_6_5,
          2_4,
          1_1_1,
          4,
          2_5_8,
          1_5_6,
          3_5,
          2_8,
          2_7_5,
          3,
          2_5_9,
          2_9_7,
          2_6_0,
          8_4,
          4,
          3_5,
          1_1_0,
          4_4,
          8,
          2_5_9,
          9_1,
          2_6_8,
          2_1,
          1_1,
          2_0_9,
          2_7_4,
          1_0_9,
          2_6_6,
          2_7_7,
          1_1_7,
          8_6,
          9_3,
          3_1_5,
          2_5_8,
          2_7_8,
          2_5_8,
          2_7_7,
          2_5_8,
          0,
          2_5_8,
          2_8_8,
          2_5_8,
          3_1_9,
          2_5_8,
          0,
          2_5_8,
          0,
          2_5_8,
          0,
          2_5_8,
          0,
          2_5_8,
          2_8_7,
          2_5_8,
          3_1_5,
          2_5_8,
          2_8_9,
          2_5_8,
          2_7_8,
          9_9,
          2_6_9,
          2_6_6,
          2_6_2,
          8,
          2_5_9,
          2_4_1,
          4,
          2_1_7,
          2_3_0,
          2_6_8,
          2_6_6,
          5_5,
          1_6_8,
          1_0_6,
          7_5,
          1_9_3,
          2_6_6,
          2_2_3,
          2_7,
          4_9,
          2_6,
          2_8_2,
          2_5,
          2_6_4,
          2_9_9,
          1_9,
          2_6,
          0,
          2_5_8,
          2_7_7,
          1_1_7,
          8_6,
          9_3,
          1_7_6,
          1_8_3,
          2_7_0,
          1_1,
          2_6_2,
          4_2,
          6_1,
          2_6_5,
      ]

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




 @require_torch
 @slow
 def      lowercase	(					self       :    str    ):
      import torch

      from transformers import ReformerConfig, ReformerModel

      # Build sequence
      _UpperCAmelCase     							=   list(self.big_tokenizer.get_vocab().keys()    )[:1_0]
      _UpperCAmelCase     							=   " ".join(snake_case_    )
      _UpperCAmelCase     							=   self.big_tokenizer.encode_plus(snake_case_	,			return_tensors="pt"    )
      _UpperCAmelCase     							=   self.big_tokenizer.batch_encode_plus([sequence, sequence]	,			return_tensors="pt"    )

      _UpperCAmelCase     							=   ReformerConfig()
      # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
      _UpperCAmelCase     							=   encoded_sequence["input_ids"].shape
      _UpperCAmelCase     							=   ReformerModel(snake_case_    )

      # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
      assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

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




 @slow
 def      lowercase	(					self       :    Optional[int]    ):
      # fmt: off
      _UpperCAmelCase     							=   {"input_ids": [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], "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]]}  # noqa: E501
      # fmt: on

      # This tokenizer does not know some characters like ")".
      # That is the reason why we use very simple texts here.
      # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
      _UpperCAmelCase     							=   [
          "This is a very simple sentence.",
          "The quick brown fox jumps over the lazy dog.",
      ]

      self.tokenizer_integration_test_util(
          expected_encoding=snake_case_	,			model_name="google/reformer-crime-and-punishment"	,			revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"	,			padding=snake_case_	,			sequences=snake_case_	,			)











'''simple docstring'''




import string
from math import logaa
def 	UpperCAmelCase_							(					__lowercase							:      str			,     __lowercase							:      str       )		->       int:


     '''simple docstring'''



     _UpperCAmelCase     							=   document.translate(
         str.maketrans(""			,     ""			,     string.punctuation       )       ).replace("\n"			,     ""       )
     _UpperCAmelCase     							=   document_without_punctuation.split(" "       )  # word tokenization
     return len([word for word in tokenize_document if word.lower() == term.lower()]       )
def 	UpperCAmelCase_							(					__lowercase							:      str			,     __lowercase							:      str       )		->       tuple[int, int]:


     '''simple docstring'''



     _UpperCAmelCase     							=   corpus.lower().translate(
         str.maketrans(""			,     ""			,     string.punctuation       )       )  # strip all punctuation and replace it with ''
     _UpperCAmelCase     							=   corpus_without_punctuation.split("\n"       )
     _UpperCAmelCase     							=   term.lower()
     return (len([doc for doc in docs if term in doc]       ), len(__lowercase       ))
def 	UpperCAmelCase_							(					__lowercase							:      int			,     __lowercase							:      int			,     __lowercase							:      Union[str, Any]=False       )		->       float:


     '''simple docstring'''



     if smoothing:
          if n == 0:
               raise ValueError("log10(0) is undefined."       )
          return round(1 + logaa(n / (1 + df)       )			,     3       )

     if df == 0:
          raise ZeroDivisionError("df must be > 0"       )
     elif n == 0:
          raise ValueError("log10(0) is undefined."       )
     return round(logaa(n / df       )			,     3       )






def 	UpperCAmelCase_							(					__lowercase							:      int			,     __lowercase							:      int       )		->       float:


     '''simple docstring'''



     return round(tf * idf			,     3       )




