





import argparse
import logging
import os
import sys

import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers

import transformers
from transformers import BartForConditionalGeneration, BartTokenizer


logging.basicConfig(
    format="""%(asctime)s | %(levelname)s | %(name)s |  [%(filename)s:%(lineno)d] %(message)s""",
    datefmt="""%Y-%m-%d %H:%M:%S""",
    level=os.environ.get("""LOGLEVEL""", """INFO""").upper(),
    stream=sys.stdout,
)

SCREAMING_SNAKE_CASE_						       =	logging.getLogger(__name__)

SCREAMING_SNAKE_CASE_						       =	{"""facebook/bart-base""": BartForConditionalGeneration}
SCREAMING_SNAKE_CASE_						       =	{"""facebook/bart-base""": BartTokenizer}



def 			__lowercase       (				)			->       Dict:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						argparse.ArgumentParser(description="""Export Bart model + Beam Search to ONNX graph."""     )
      parser.add_argument(
          """--validation_file"""			,						type=_SCREAMING_SNAKE_CASE			,						default=_SCREAMING_SNAKE_CASE			,						help="""A csv or a json file containing the validation data."""     )
      parser.add_argument(
          """--max_length"""			,						type=_SCREAMING_SNAKE_CASE			,						default=5			,						help="""The maximum total input sequence length after tokenization."""			,						)
      parser.add_argument(
          """--num_beams"""			,						type=_SCREAMING_SNAKE_CASE			,						default=_SCREAMING_SNAKE_CASE			,						help=(
              """Number of beams to use for evaluation. This argument will be """
              """passed to ``model.generate``, which is used during ``evaluate`` and ``predict``."""
          )			,						)
      parser.add_argument(
          """--model_name_or_path"""			,						type=_SCREAMING_SNAKE_CASE			,						help="""Path to pretrained model or model identifier from huggingface.co/models."""			,						required=_SCREAMING_SNAKE_CASE			,						)
      parser.add_argument(
          """--config_name"""			,						type=_SCREAMING_SNAKE_CASE			,						default=_SCREAMING_SNAKE_CASE			,						help="""Pretrained config name or path if not the same as model_name"""			,						)
      parser.add_argument(
          """--device"""			,						type=_SCREAMING_SNAKE_CASE			,						default="""cpu"""			,						help="""Device where the model will be run"""			,						)
      parser.add_argument("""--output_file_path"""			,						type=_SCREAMING_SNAKE_CASE			,						default=_SCREAMING_SNAKE_CASE			,						help="""Where to store the final ONNX file."""     )

      SCREAMING_SNAKE_CASE		=						parser.parse_args()

      return args



def 			__lowercase       (				_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE="cpu"     )			->       int:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						model_dict[model_name].from_pretrained(_SCREAMING_SNAKE_CASE     ).to(_SCREAMING_SNAKE_CASE     )
      SCREAMING_SNAKE_CASE		=						tokenizer_dict[model_name].from_pretrained(_SCREAMING_SNAKE_CASE     )

      if model_name in ["facebook/bart-base"]:
            SCREAMING_SNAKE_CASE		=						0
            SCREAMING_SNAKE_CASE		=						None
            SCREAMING_SNAKE_CASE		=						0

      return huggingface_model, tokenizer



def 			__lowercase       (				_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )			->       str:


      '''simple docstring'''


      model.eval()

      SCREAMING_SNAKE_CASE		=						None
      SCREAMING_SNAKE_CASE		=						torch.jit.script(BARTBeamSearchGenerator(_SCREAMING_SNAKE_CASE     )     )

      with torch.no_grad():
            SCREAMING_SNAKE_CASE		=						"""My friends are cool but they eat too many carbs."""
            SCREAMING_SNAKE_CASE		=						tokenizer([ARTICLE_TO_SUMMARIZE]			,						max_length=10_24			,						return_tensors="""pt"""     ).to(model.device     )

            SCREAMING_SNAKE_CASE		=						model.generate(
                inputs["""input_ids"""]			,						attention_mask=inputs["""attention_mask"""]			,						num_beams=_SCREAMING_SNAKE_CASE			,						max_length=_SCREAMING_SNAKE_CASE			,						early_stopping=_SCREAMING_SNAKE_CASE			,						decoder_start_token_id=model.config.decoder_start_token_id			,						)

            torch.onnx.export(
                _SCREAMING_SNAKE_CASE			,						(
                    inputs["""input_ids"""],
                    inputs["""attention_mask"""],
                    num_beams,
                    max_length,
                    model.config.decoder_start_token_id,
                )			,						_SCREAMING_SNAKE_CASE			,						opset_version=14			,						input_names=["""input_ids""", """attention_mask""", """num_beams""", """max_length""", """decoder_start_token_id"""]			,						output_names=["""output_ids"""]			,						dynamic_axes={
                    """input_ids""": {0: """batch""", 1: """seq"""},
                    """output_ids""": {0: """batch""", 1: """seq_out"""},
                }			,						example_outputs=_SCREAMING_SNAKE_CASE			,						)

            logger.info("""Model exported to {}""".format(_SCREAMING_SNAKE_CASE     )     )

            SCREAMING_SNAKE_CASE		=						remove_dup_initializers(os.path.abspath(_SCREAMING_SNAKE_CASE     )     )

            logger.info("""Deduplicated and optimized model written to {}""".format(_SCREAMING_SNAKE_CASE     )     )

            SCREAMING_SNAKE_CASE		=						onnxruntime.InferenceSession(_SCREAMING_SNAKE_CASE     )
            SCREAMING_SNAKE_CASE		=						ort_sess.run(
                _SCREAMING_SNAKE_CASE			,						{
                    """input_ids""": inputs["""input_ids"""].cpu().numpy(),
                    """attention_mask""": inputs["""attention_mask"""].cpu().numpy(),
                    """num_beams""": np.array(_SCREAMING_SNAKE_CASE     ),
                    """max_length""": np.array(_SCREAMING_SNAKE_CASE     ),
                    """decoder_start_token_id""": np.array(model.config.decoder_start_token_id     ),
                }			,						)

            np.testing.assert_allclose(summary_ids.cpu().numpy()			,						ort_out[0]			,						rtol=1E-3			,						atol=1E-3     )

            logger.info("""Model outputs from torch and ONNX Runtime are similar."""     )
            logger.info("""Success."""     )



def 			__lowercase       (				)			->       Dict:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						parse_args()
      SCREAMING_SNAKE_CASE		=						5
      SCREAMING_SNAKE_CASE		=						4

      # Make one log on every process with the configuration for debugging.
      logging.basicConfig(
          format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s"""			,						datefmt="""%m/%d/%Y %H:%M:%S"""			,						level=logging.INFO			,						)

      logger.setLevel(logging.INFO     )
      transformers.utils.logging.set_verbosity_error()

      SCREAMING_SNAKE_CASE		=						torch.device(args.device     )

      SCREAMING_SNAKE_CASE, SCREAMING_SNAKE_CASE		=						load_model_tokenizer(args.model_name_or_path			,						_SCREAMING_SNAKE_CASE     )

      if model.config.decoder_start_token_id is None:
            raise ValueError("""Make sure that `config.decoder_start_token_id` is correctly defined"""     )

      model.to(_SCREAMING_SNAKE_CASE     )

      if args.max_length:
            SCREAMING_SNAKE_CASE		=						args.max_length

      if args.num_beams:
            SCREAMING_SNAKE_CASE		=						args.num_beams

      if args.output_file_path:
            SCREAMING_SNAKE_CASE		=						args.output_file_path
      else:
            SCREAMING_SNAKE_CASE		=						"""BART.onnx"""

      logger.info("""Exporting model to ONNX"""     )
      export_and_validate_model(_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )


if __name__ == "__main__":
      main()









import os
import unittest

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    BertTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english

@require_tokenizers
class 		UpperCamelCase__			(				lowerCAmelCase_							,				unittest.TestCase       ):



     '''simple docstring'''

     __snake_case   :     Any		     =      BertTokenizer
     __snake_case   :     Dict		     =      BertTokenizerFast
     __snake_case   :     Tuple		     =      True
     __snake_case   :     List[Any]		     =      True
     __snake_case   :     Optional[Any]		     =      filter_non_english






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




           '''simple docstring'''


           super().setUp()

           SCREAMING_SNAKE_CASE		=						[
               """[UNK]""",
               """[CLS]""",
               """[SEP]""",
               """[PAD]""",
               """[MASK]""",
               """want""",
               """##want""",
               """##ed""",
               """wa""",
               """un""",
               """runn""",
               """##ing""",
               """,""",
               """low""",
               """lowest""",
           ]
           SCREAMING_SNAKE_CASE		=						os.path.join(self.tmpdirname						,VOCAB_FILES_NAMES["""vocab_file"""]	)
           with open(self.vocab_file						,"""w"""						,encoding="""utf-8"""	) as vocab_writer:
                 vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]	)	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   str						,lowerCamelCase__						:   List[Any]	)					->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						"""UNwant\u00E9d,running"""
           SCREAMING_SNAKE_CASE		=						"""unwanted, running"""
           return input_text, output_text






     def     SCREAMING_SNAKE_CASE__  (							self						:   Dict	)					->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						self.tokenizer_class(self.vocab_file	)

           SCREAMING_SNAKE_CASE		=						tokenizer.tokenize("""UNwant\u00E9d,running"""	)
           self.assertListEqual(lowerCamelCase__						,["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]	)
           self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase__	)						,[9, 6, 7, 12, 10, 11]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[Any]	)					->		List[Any]:




           '''simple docstring'''


           if not self.test_rust_tokenizer:
                 return

           SCREAMING_SNAKE_CASE		=						self.get_tokenizer()
           SCREAMING_SNAKE_CASE		=						self.get_rust_tokenizer()

           SCREAMING_SNAKE_CASE		=						"""UNwant\u00E9d,running"""

           SCREAMING_SNAKE_CASE		=						tokenizer.tokenize(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.tokenize(lowerCamelCase__	)
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)

           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)

           SCREAMING_SNAKE_CASE		=						self.get_rust_tokenizer()
           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__	)
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)

           # With lower casing
           SCREAMING_SNAKE_CASE		=						self.get_tokenizer(do_lower_case=lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						self.get_rust_tokenizer(do_lower_case=lowerCamelCase__	)

           SCREAMING_SNAKE_CASE		=						"""UNwant\u00E9d,running"""

           SCREAMING_SNAKE_CASE		=						tokenizer.tokenize(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.tokenize(lowerCamelCase__	)
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)

           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)

           SCREAMING_SNAKE_CASE		=						self.get_rust_tokenizer()
           SCREAMING_SNAKE_CASE		=						tokenizer.encode(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						rust_tokenizer.encode(lowerCamelCase__	)
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   int	)					->		Optional[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer()

           self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz"""	)						,["""ah""", """\u535A""", """\u63A8""", """zz"""]	)






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




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """	)						,["""hello""", """!""", """how""", """are""", """you""", """?"""]	)
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	)						,["""hello"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Any	)					->		Dict:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__						,strip_accents=lowerCamelCase__	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	)						,["""hällo""", """!""", """how""", """are""", """you""", """?"""]	)
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	)						,["""h\u00E9llo"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   str	)					->		List[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__						,strip_accents=lowerCamelCase__	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	)						,["""hallo""", """!""", """how""", """are""", """you""", """?"""]	)
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	)						,["""hello"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[str]	)					->		Any:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	)						,["""hallo""", """!""", """how""", """are""", """you""", """?"""]	)
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""	)						,["""hello"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]	)					->		Union[str, Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """	)						,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Dict	)					->		Optional[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__						,strip_accents=lowerCamelCase__	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	)						,["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   int	)					->		List[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__						,strip_accents=lowerCamelCase__	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """	)						,["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]	)					->		Optional[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer(do_lower_case=lowerCamelCase__						,never_split=["""[UNK]"""]	)

           self.assertListEqual(
               tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]"""	)						,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[Any]	)					->		Any:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BasicTokenizer()
           SCREAMING_SNAKE_CASE		=						"""a\n'll !!to?'d of, can't."""
           SCREAMING_SNAKE_CASE		=						["""a""", """'""", """ll""", """!""", """!""", """to""", """?""", """'""", """d""", """of""", """,""", """can""", """'""", """t""", """."""]
           self.assertListEqual(tokenizer.tokenize(lowerCamelCase__	)						,lowerCamelCase__	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Dict	)					->		int:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

           SCREAMING_SNAKE_CASE		=						{}
           for i, token in enumerate(lowerCamelCase__	):
                 SCREAMING_SNAKE_CASE		=						i
           SCREAMING_SNAKE_CASE		=						WordpieceTokenizer(vocab=lowerCamelCase__						,unk_token="""[UNK]"""	)

           self.assertListEqual(tokenizer.tokenize(""""""	)						,[]	)

           self.assertListEqual(tokenizer.tokenize("""unwanted running"""	)						,["""un""", """##want""", """##ed""", """runn""", """##ing"""]	)

           self.assertListEqual(tokenizer.tokenize("""unwantedX running"""	)						,["""[UNK]""", """runn""", """##ing"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]	)					->		Dict:




           '''simple docstring'''


           self.assertTrue(_is_whitespace(""" """	)	)
           self.assertTrue(_is_whitespace("""\t"""	)	)
           self.assertTrue(_is_whitespace("""\r"""	)	)
           self.assertTrue(_is_whitespace("""\n"""	)	)
           self.assertTrue(_is_whitespace("""\u00A0"""	)	)

           self.assertFalse(_is_whitespace("""A"""	)	)
           self.assertFalse(_is_whitespace("""-"""	)	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]	)					->		Optional[int]:




           '''simple docstring'''


           self.assertTrue(_is_control("""\u0005"""	)	)

           self.assertFalse(_is_control("""A"""	)	)
           self.assertFalse(_is_control(""" """	)	)
           self.assertFalse(_is_control("""\t"""	)	)
           self.assertFalse(_is_control("""\r"""	)	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Tuple	)					->		List[str]:




           '''simple docstring'''


           self.assertTrue(_is_punctuation("""-"""	)	)
           self.assertTrue(_is_punctuation("""$"""	)	)
           self.assertTrue(_is_punctuation("""`"""	)	)
           self.assertTrue(_is_punctuation("""."""	)	)

           self.assertFalse(_is_punctuation("""A"""	)	)
           self.assertFalse(_is_punctuation(""" """	)	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[Any]	)					->		Any:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						self.get_tokenizer()
           SCREAMING_SNAKE_CASE		=						self.get_rust_tokenizer()

           # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
           self.assertListEqual([tokenizer.tokenize(lowerCamelCase__	) for t in ["""Test""", """\xad""", """test"""]]						,[["""[UNK]"""], [], ["""[UNK]"""]]	)

           self.assertListEqual(
               [rust_tokenizer.tokenize(lowerCamelCase__	) for t in ["""Test""", """\xad""", """test"""]]						,[["""[UNK]"""], [], ["""[UNK]"""]]	)






     @slow
     def     SCREAMING_SNAKE_CASE__  (							self						:   Any	)					->		Optional[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						self.tokenizer_class.from_pretrained("""bert-base-uncased"""	)

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

           SCREAMING_SNAKE_CASE		=						tokenizer.build_inputs_with_special_tokens(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						tokenizer.build_inputs_with_special_tokens(lowerCamelCase__						,lowerCamelCase__	)

           assert encoded_sentence == [101] + text + [102]
           assert encoded_pair == [101] + text + [102] + text_a + [102]






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]	)					->		str:




           '''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(lowerCamelCase__						,**lowerCamelCase__	)

                       SCREAMING_SNAKE_CASE		=						F"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
                       SCREAMING_SNAKE_CASE		=						tokenizer_r.encode_plus(
                           lowerCamelCase__						,return_attention_mask=lowerCamelCase__						,return_token_type_ids=lowerCamelCase__						,return_offsets_mapping=lowerCamelCase__						,add_special_tokens=lowerCamelCase__						,)

                       SCREAMING_SNAKE_CASE		=						tokenizer_r.do_lower_case if hasattr(lowerCamelCase__						,"""do_lower_case"""	) else False
                       SCREAMING_SNAKE_CASE		=						(
                           [
                               ((0, 0), tokenizer_r.cls_token),
                               ((0, 1), """A"""),
                               ((1, 2), ""","""),
                               ((3, 5), """na"""),
                               ((5, 6), """##ï"""),
                               ((6, 8), """##ve"""),
                               ((9, 15), tokenizer_r.mask_token),
                               ((16, 21), """Allen"""),
                               ((21, 23), """##NL"""),
                               ((23, 24), """##P"""),
                               ((25, 33), """sentence"""),
                               ((33, 34), """."""),
                               ((0, 0), tokenizer_r.sep_token),
                           ]
                           if not do_lower_case
                           else [
                               ((0, 0), tokenizer_r.cls_token),
                               ((0, 1), """a"""),
                               ((1, 2), ""","""),
                               ((3, 8), """naive"""),
                               ((9, 15), tokenizer_r.mask_token),
                               ((16, 21), """allen"""),
                               ((21, 23), """##nl"""),
                               ((23, 24), """##p"""),
                               ((25, 33), """sentence"""),
                               ((33, 34), """."""),
                               ((0, 0), tokenizer_r.sep_token),
                           ]
                       )

                       self.assertEqual(
                           [e[1] for e in expected_results]						,tokenizer_r.convert_ids_to_tokens(tokens["""input_ids"""]	)	)
                       self.assertEqual([e[0] for e in expected_results]						,tokens["""offset_mapping"""]	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Any	)					->		List[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						["""的""", """人""", """有"""]
           SCREAMING_SNAKE_CASE		=						"""""".join(lowerCamelCase__	)
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""	):
                       SCREAMING_SNAKE_CASE		=						True
                       SCREAMING_SNAKE_CASE		=						self.tokenizer_class.from_pretrained(lowerCamelCase__						,**lowerCamelCase__	)
                       SCREAMING_SNAKE_CASE		=						self.rust_tokenizer_class.from_pretrained(lowerCamelCase__						,**lowerCamelCase__	)

                       SCREAMING_SNAKE_CASE		=						tokenizer_p.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)
                       SCREAMING_SNAKE_CASE		=						tokenizer_r.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)

                       SCREAMING_SNAKE_CASE		=						tokenizer_r.convert_ids_to_tokens(lowerCamelCase__	)
                       SCREAMING_SNAKE_CASE		=						tokenizer_p.convert_ids_to_tokens(lowerCamelCase__	)

                       # it is expected that each Chinese character is not preceded by "##"
                       self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)
                       self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)

                       SCREAMING_SNAKE_CASE		=						False
                       SCREAMING_SNAKE_CASE		=						self.rust_tokenizer_class.from_pretrained(lowerCamelCase__						,**lowerCamelCase__	)
                       SCREAMING_SNAKE_CASE		=						self.tokenizer_class.from_pretrained(lowerCamelCase__						,**lowerCamelCase__	)

                       SCREAMING_SNAKE_CASE		=						tokenizer_r.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)
                       SCREAMING_SNAKE_CASE		=						tokenizer_p.encode(lowerCamelCase__						,add_special_tokens=lowerCamelCase__	)

                       SCREAMING_SNAKE_CASE		=						tokenizer_r.convert_ids_to_tokens(lowerCamelCase__	)
                       SCREAMING_SNAKE_CASE		=						tokenizer_p.convert_ids_to_tokens(lowerCamelCase__	)

                       # it is expected that only the first Chinese character is not preceded by "##".
                       SCREAMING_SNAKE_CASE		=						[
                           F"""##{token}""" if idx != 0 else token for idx, token in enumerate(lowerCamelCase__	)
                       ]
                       self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)
                       self.assertListEqual(lowerCamelCase__						,lowerCamelCase__	)


