

'''simple docstring'''



import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 		lowerCAmelCase__  ( a					,   unittest.TestCase   ):



 """simple docstring"""



 lowerCAmelCase__       = LongformerTokenizer
 lowerCAmelCase__       = True
 lowerCAmelCase__       = LongformerTokenizerFast
 lowerCAmelCase__       = True
 def  UpperCAmelCase__						(						self   :			Optional[int]     )    ->					Union[str, Any]:


      """simple docstring"""




      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      __SCREAMING_SNAKE_CASE      = [
          """l""",
          """o""",
          """w""",
          """e""",
          """r""",
          """s""",
          """t""",
          """i""",
          """d""",
          """n""",
          """\u0120""",
          """\u0120l""",
          """\u0120n""",
          """\u0120lo""",
          """\u0120low""",
          """er""",
          """\u0120lowest""",
          """\u0120newer""",
          """\u0120wider""",
          """<unk>""",
      ]
      __SCREAMING_SNAKE_CASE      = dict(zip(__SCREAMING_SNAKE_CASE   ,				range(len(__SCREAMING_SNAKE_CASE     )     )     )     )
      __SCREAMING_SNAKE_CASE      = ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
      __SCREAMING_SNAKE_CASE      = {"""unk_token""": """<unk>"""}

      __SCREAMING_SNAKE_CASE      = os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES["""vocab_file"""]     )
      __SCREAMING_SNAKE_CASE      = 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(__SCREAMING_SNAKE_CASE     ) + """\n"""     )
      with open(self.merges_file   ,				"""w"""   ,				encoding="""utf-8"""     ) as fp:
           fp.write("""\n""".join(__SCREAMING_SNAKE_CASE     )     )
 def  UpperCAmelCase__						(						self   :			str   ,				**__SCREAMING_SNAKE_CASE   :			Optional[int]     )    ->					Tuple:


      """simple docstring"""




      kwargs.update(self.special_tokens_map     )
      return self.tokenizer_class.from_pretrained(self.tmpdirname   ,				**__SCREAMING_SNAKE_CASE     )
 def  UpperCAmelCase__						(						self   :			Tuple   ,				**__SCREAMING_SNAKE_CASE   :			int     )    ->					List[str]:


      """simple docstring"""




      kwargs.update(self.special_tokens_map     )
      return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,				**__SCREAMING_SNAKE_CASE     )
 def  UpperCAmelCase__						(						self   :			Union[str, Any]   ,				__SCREAMING_SNAKE_CASE   :			List[str]     )    ->					Optional[int]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = """lower newer"""
      __SCREAMING_SNAKE_CASE      = """lower newer"""
      return input_text, output_text
 def  UpperCAmelCase__						(						self   :			List[Any]     )    ->					List[Any]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = self.tokenizer_class(self.vocab_file   ,				self.merges_file   ,				**self.special_tokens_map     )
      __SCREAMING_SNAKE_CASE      = """lower newer"""
      __SCREAMING_SNAKE_CASE      = ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
      __SCREAMING_SNAKE_CASE      = tokenizer.tokenize(__SCREAMING_SNAKE_CASE     )  # , add_prefix_space=True)
      self.assertListEqual(__SCREAMING_SNAKE_CASE   ,				__SCREAMING_SNAKE_CASE     )

      __SCREAMING_SNAKE_CASE      = tokens + [tokenizer.unk_token]
      __SCREAMING_SNAKE_CASE      = [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE     )   ,				__SCREAMING_SNAKE_CASE     )
 def  UpperCAmelCase__						(						self   :			Union[str, Any]     )    ->					Tuple:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = self.get_tokenizer()

      self.assertListEqual(tokenizer.encode("""Hello world!"""   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )   ,				[0, 31_414, 232, 328, 2]     )
      self.assertListEqual(
          tokenizer.encode("""Hello world! cécé herlolip 418"""   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )   ,				[0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]   ,				)
 @slow
 def  UpperCAmelCase__						(						self   :			List[Any]     )    ->					List[str]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""     )

      __SCREAMING_SNAKE_CASE      = tokenizer.encode("""sequence builders"""   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
      __SCREAMING_SNAKE_CASE      = tokenizer.encode("""multi-sequence build"""   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )

      __SCREAMING_SNAKE_CASE      = tokenizer.encode(
          """sequence builders"""   ,				add_special_tokens=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE     )
      __SCREAMING_SNAKE_CASE      = tokenizer.encode(
          """sequence builders"""   ,				"""multi-sequence build"""   ,				add_special_tokens=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE     )

      __SCREAMING_SNAKE_CASE      = tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE     )
      __SCREAMING_SNAKE_CASE      = tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE   ,				__SCREAMING_SNAKE_CASE     )

      assert encoded_sentence == encoded_text_from_decode
      assert encoded_pair == encoded_pair_from_decode
 def  UpperCAmelCase__						(						self   :			Dict     )    ->					str:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = self.get_tokenizer()

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

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

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

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

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

      __SCREAMING_SNAKE_CASE      = """Encode <mask> sequence"""
      __SCREAMING_SNAKE_CASE      = """Encode <mask>sequence"""

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

      __SCREAMING_SNAKE_CASE      = tokenizer.encode(__SCREAMING_SNAKE_CASE     )
      __SCREAMING_SNAKE_CASE      = encoded.index(__SCREAMING_SNAKE_CASE     )
      __SCREAMING_SNAKE_CASE      = tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
      self.assertNotEqual(__SCREAMING_SNAKE_CASE   ,				__SCREAMING_SNAKE_CASE     )
 def  UpperCAmelCase__						(						self   :			Dict     )    ->					str:


      """simple docstring"""




      pass
 def  UpperCAmelCase__						(						self   :			int     )    ->					Tuple:


      """simple docstring"""




      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'     ):
                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE   ,				**__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = self.tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE   ,				**__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = """A, <mask> AllenNLP sentence."""
                __SCREAMING_SNAKE_CASE      = tokenizer_r.encode_plus(__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE   ,				return_token_type_ids=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_p.encode_plus(__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE   ,				return_token_type_ids=__SCREAMING_SNAKE_CASE     )

                # 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"""]     )   ,				)

                __SCREAMING_SNAKE_CASE      = tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]     )
                __SCREAMING_SNAKE_CASE      = 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, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]     )
                self.assertSequenceEqual(tokens_r["""input_ids"""]   ,				[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]     )

                self.assertSequenceEqual(
                    __SCREAMING_SNAKE_CASE   ,				["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]     )
                self.assertSequenceEqual(
                    __SCREAMING_SNAKE_CASE   ,				["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]     )
 def  UpperCAmelCase__						(						self   :			Optional[int]     )    ->					List[Any]:


      """simple docstring"""




      for trim_offsets, add_prefix_space in itertools.product([True, False]   ,				repeat=2     ):
           __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
               self.tmpdirname   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )

           __SCREAMING_SNAKE_CASE      = json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()     )
           __SCREAMING_SNAKE_CASE      = json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()     )

           self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]   ,				__SCREAMING_SNAKE_CASE     )

           self.assertEqual(post_processor_state["""add_prefix_space"""]   ,				__SCREAMING_SNAKE_CASE     )
           self.assertEqual(post_processor_state["""trim_offsets"""]   ,				__SCREAMING_SNAKE_CASE     )


 def  UpperCAmelCase__						(						self   :			Any     )    ->					Union[str, Any]:


      """simple docstring"""




      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'     ):
                __SCREAMING_SNAKE_CASE      = """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                __SCREAMING_SNAKE_CASE      = f'{text_of_1_token} {text_of_1_token}'

                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
                    __SCREAMING_SNAKE_CASE   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_r(__SCREAMING_SNAKE_CASE   ,				return_offsets_mapping=__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
                self.assertEqual(encoding.offset_mapping[0]   ,				(0, len(__SCREAMING_SNAKE_CASE     ))     )
                self.assertEqual(
                    encoding.offset_mapping[1]   ,				(len(__SCREAMING_SNAKE_CASE     ) + 1, len(__SCREAMING_SNAKE_CASE     ) + 1 + len(__SCREAMING_SNAKE_CASE     ))   ,				)

                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
                    __SCREAMING_SNAKE_CASE   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_r(__SCREAMING_SNAKE_CASE   ,				return_offsets_mapping=__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
                self.assertEqual(encoding.offset_mapping[0]   ,				(0, len(__SCREAMING_SNAKE_CASE     ))     )
                self.assertEqual(
                    encoding.offset_mapping[1]   ,				(len(__SCREAMING_SNAKE_CASE     ) + 1, len(__SCREAMING_SNAKE_CASE     ) + 1 + len(__SCREAMING_SNAKE_CASE     ))   ,				)

                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
                    __SCREAMING_SNAKE_CASE   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_r(__SCREAMING_SNAKE_CASE   ,				return_offsets_mapping=__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
                self.assertEqual(encoding.offset_mapping[0]   ,				(0, len(__SCREAMING_SNAKE_CASE     ))     )
                self.assertEqual(
                    encoding.offset_mapping[1]   ,				(len(__SCREAMING_SNAKE_CASE     ), len(__SCREAMING_SNAKE_CASE     ) + 1 + len(__SCREAMING_SNAKE_CASE     ))   ,				)

                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
                    __SCREAMING_SNAKE_CASE   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_r(__SCREAMING_SNAKE_CASE   ,				return_offsets_mapping=__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
                self.assertEqual(encoding.offset_mapping[0]   ,				(0, len(__SCREAMING_SNAKE_CASE     ))     )
                self.assertEqual(
                    encoding.offset_mapping[1]   ,				(len(__SCREAMING_SNAKE_CASE     ), len(__SCREAMING_SNAKE_CASE     ) + 1 + len(__SCREAMING_SNAKE_CASE     ))   ,				)

                __SCREAMING_SNAKE_CASE      = 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)),
                # )

                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
                    __SCREAMING_SNAKE_CASE   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_r(__SCREAMING_SNAKE_CASE   ,				return_offsets_mapping=__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
                self.assertEqual(encoding.offset_mapping[0]   ,				(1, 1 + len(__SCREAMING_SNAKE_CASE     ))     )
                self.assertEqual(
                    encoding.offset_mapping[1]   ,				(1 + len(__SCREAMING_SNAKE_CASE     ) + 1, 1 + len(__SCREAMING_SNAKE_CASE     ) + 1 + len(__SCREAMING_SNAKE_CASE     ))   ,				)

                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
                    __SCREAMING_SNAKE_CASE   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_r(__SCREAMING_SNAKE_CASE   ,				return_offsets_mapping=__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
                self.assertEqual(encoding.offset_mapping[0]   ,				(0, 1 + len(__SCREAMING_SNAKE_CASE     ))     )
                self.assertEqual(
                    encoding.offset_mapping[1]   ,				(1 + len(__SCREAMING_SNAKE_CASE     ), 1 + len(__SCREAMING_SNAKE_CASE     ) + 1 + len(__SCREAMING_SNAKE_CASE     ))   ,				)

                __SCREAMING_SNAKE_CASE      = self.rust_tokenizer_class.from_pretrained(
                    __SCREAMING_SNAKE_CASE   ,				use_fast=__SCREAMING_SNAKE_CASE   ,				add_prefix_space=__SCREAMING_SNAKE_CASE   ,				trim_offsets=__SCREAMING_SNAKE_CASE     )
                __SCREAMING_SNAKE_CASE      = tokenizer_r(__SCREAMING_SNAKE_CASE   ,				return_offsets_mapping=__SCREAMING_SNAKE_CASE   ,				add_special_tokens=__SCREAMING_SNAKE_CASE     )
                self.assertEqual(encoding.offset_mapping[0]   ,				(0, 1 + len(__SCREAMING_SNAKE_CASE     ))     )
                self.assertEqual(
                    encoding.offset_mapping[1]   ,				(1 + len(__SCREAMING_SNAKE_CASE     ), 1 + len(__SCREAMING_SNAKE_CASE     ) + 1 + len(__SCREAMING_SNAKE_CASE     ))   ,				)









'''simple docstring'''



import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase					:			int       =	get_tests_dir('fixtures/test_sentencepiece.model')







@require_sentencepiece
class 		lowerCAmelCase__  ( a					,   unittest.TestCase   ):



 """simple docstring"""



 lowerCAmelCase__       = XLMProphetNetTokenizer
 lowerCAmelCase__       = False
 lowerCAmelCase__       = True
 def  UpperCAmelCase__						(						self   :			str     )    ->					Optional[int]:


      """simple docstring"""




      super().setUp()

      # We have a SentencePiece fixture for testing
      __SCREAMING_SNAKE_CASE      = XLMProphetNetTokenizer(__SCREAMING_SNAKE_CASE   ,				keep_accents=__SCREAMING_SNAKE_CASE     )
      tokenizer.save_pretrained(self.tmpdirname     )
 def  UpperCAmelCase__						(						self   :			Dict     )    ->					Tuple:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = """[PAD]"""
      __SCREAMING_SNAKE_CASE      = 0

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(__SCREAMING_SNAKE_CASE     )   ,				__SCREAMING_SNAKE_CASE     )
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(__SCREAMING_SNAKE_CASE     )   ,				__SCREAMING_SNAKE_CASE     )
 def  UpperCAmelCase__						(						self   :			Tuple     )    ->					Optional[int]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = list(self.get_tokenizer().get_vocab().keys()     )

      self.assertEqual(vocab_keys[0]   ,				"""[PAD]"""     )
      self.assertEqual(vocab_keys[1]   ,				"""[CLS]"""     )
      self.assertEqual(vocab_keys[-1]   ,				"""j"""     )
      self.assertEqual(len(__SCREAMING_SNAKE_CASE     )   ,				1_012     )
 def  UpperCAmelCase__						(						self   :			Any     )    ->					List[str]:


      """simple docstring"""




      self.assertEqual(self.get_tokenizer().vocab_size   ,				1_012     )
 def  UpperCAmelCase__						(						self   :			int     )    ->					List[Any]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = XLMProphetNetTokenizer(__SCREAMING_SNAKE_CASE   ,				keep_accents=__SCREAMING_SNAKE_CASE     )

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

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE     )   ,				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,				)

      __SCREAMING_SNAKE_CASE      = tokenizer.tokenize("""I was born in 92000, and this is falsé."""     )
      self.assertListEqual(
          __SCREAMING_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""",
              """.""",
          ]   ,				)
      __SCREAMING_SNAKE_CASE      = tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE     )
      self.assertListEqual(
          __SCREAMING_SNAKE_CASE   ,				[
              value + tokenizer.fairseq_offset
              for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
          ]   ,				)

      __SCREAMING_SNAKE_CASE      = tokenizer.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE     )
      self.assertListEqual(
          __SCREAMING_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  UpperCAmelCase__						(						self   :			str     )    ->					str:


      """simple docstring"""




      return XLMProphetNetTokenizer.from_pretrained("""microsoft/xprophetnet-large-wiki100-cased"""     )
 @slow
 def  UpperCAmelCase__						(						self   :			Dict     )    ->					Optional[Any]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = """Hello World!"""
      __SCREAMING_SNAKE_CASE      = [35_389, 6_672, 49, 2]
      self.assertListEqual(__SCREAMING_SNAKE_CASE   ,				self.big_tokenizer.encode(__SCREAMING_SNAKE_CASE     )     )


 @slow
 def  UpperCAmelCase__						(						self   :			Dict     )    ->					str:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = {"""input_ids""": [[11_073, 82_783, 18, 26, 82_783, 549, 51_540, 248, 17_209, 1_301, 217, 20, 215_186, 1_325, 147, 17_209, 1_301, 217, 20, 56_370, 53, 122_020, 20, 16_477, 27, 87_355, 4_548, 20, 4_728, 78_392, 17, 159_969, 18, 26, 24_491, 629, 15, 538, 22_704, 5_439, 15, 2_788, 24_491, 9_885, 15, 43_534, 605, 15, 814, 18_403, 33_200, 29, 15, 43_534, 24_458, 12_410, 111, 24_966, 83_669, 9_637, 144_068, 26, 850, 22_346, 27, 147, 24_966, 83_669, 83_490, 26, 39_113, 735, 27, 689, 656, 2_800, 1_339, 4_600, 53, 122_020, 115_785, 34, 816, 1_339, 46_887, 18, 147, 53_905, 1_951, 42_238, 41_170, 17_732, 834, 436, 15, 27_523, 98_733, 217, 147, 5_542, 4_981, 930, 17_347, 16, 2], [20_091, 629, 94, 82_786, 58, 490, 20, 1_528, 84, 53_905, 344, 80_592, 110_128, 18_822, 5_267, 1_306, 62, 152_537, 308, 7_997, 401, 124_427, 549, 35_442, 225, 109, 15_055, 25_748, 147, 7_119, 43_712, 34, 767, 135_366, 18, 16, 2, 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], [592, 63_784, 119_466, 17, 147_808, 88_214, 18, 656, 81, 32, 3_296, 10_280, 16, 2, 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, 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, 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, 0, 0, 0, 0, 0], [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, 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=__SCREAMING_SNAKE_CASE   ,				model_name="""microsoft/xprophetnet-large-wiki100-cased"""   ,				revision="""1acad1643ddd54a44df6a1b797ada8373685d90e"""   ,				)






