





import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors





@require_tokenizers
class  lowerCAmelCase							(       lowercase_							,							unittest.TestCase ):
  __lowerCamelCase		=      MvpTokenizer
  __lowerCamelCase		=      MvpTokenizerFast
  __lowerCamelCase		=      True
  __lowerCamelCase		=      filter_roberta_detectors







  def   UpperCAmelCase					(      self  :List[str] ):






     '''simple docstring'''





     super().setUp()
     lowercase__			       =  [
         "l",
         "o",
         "w",
         "e",
         "r",
         "s",
         "t",
         "i",
         "d",
         "n",
         "\u0120",
         "\u0120l",
         "\u0120n",
         "\u0120lo",
         "\u0120low",
         "er",
         "\u0120lowest",
         "\u0120newer",
         "\u0120wider",
         "<unk>",
     ]
     lowercase__			       =  dict(zip(_lowercase   ,							range(len(_lowercase ) ) ) )
     lowercase__			       =  ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
     lowercase__			       =  {"unk_token": "<unk>"}

     lowercase__			       =  os.path.join(self.tmpdirname   ,							VOCAB_FILES_NAMES["vocab_file"] )
     lowercase__			       =  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(_lowercase ) + "\n" )
     with open(self.merges_file   ,							"w"   ,							encoding="utf-8" ) as fp:
        fp.write("\n".join(_lowercase ) )







  def   UpperCAmelCase					(      self  :Optional[Any]   ,							**_lowercase  :Optional[int] ):






     '''simple docstring'''





     kwargs.update(self.special_tokens_map )
     return self.tokenizer_class.from_pretrained(self.tmpdirname   ,							**_lowercase )







  def   UpperCAmelCase					(      self  :Tuple   ,							**_lowercase  :Dict ):






     '''simple docstring'''





     kwargs.update(self.special_tokens_map )
     return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,							**_lowercase )







  def   UpperCAmelCase					(      self  :Any   ,							_lowercase  :Tuple ):






     '''simple docstring'''





     return "lower newer", "lower newer"







  @cached_property
  def   UpperCAmelCase					(      self  :int ):






     '''simple docstring'''





     return MvpTokenizer.from_pretrained("RUCAIBox/mvp" )







  @cached_property
  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     return MvpTokenizerFast.from_pretrained("RUCAIBox/mvp" )







  @require_torch
  def   UpperCAmelCase					(      self  :Dict ):






     '''simple docstring'''





     lowercase__			       =  ["A long paragraph for summarization.", "Another paragraph for summarization."]
     lowercase__			       =  [0, 2_50, 2_51, 1_78_18, 13, 3_91_86, 19_38, 4, 2]

     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase__			       =  tokenizer(_lowercase   ,							max_length=len(_lowercase )   ,							padding=_lowercase   ,							return_tensors="pt" )
        self.assertIsInstance(_lowercase   ,							_lowercase )

        self.assertEqual((2, 9)   ,							batch.input_ids.shape )
        self.assertEqual((2, 9)   ,							batch.attention_mask.shape )
        lowercase__			       =  batch.input_ids.tolist()[0]
        self.assertListEqual(_lowercase   ,							_lowercase )
        # Test that special tokens are reset







  @require_torch
  def   UpperCAmelCase					(      self  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  ["A long paragraph for summarization.", "Another paragraph for summarization."]
     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase__			       =  tokenizer(_lowercase   ,							padding=_lowercase   ,							return_tensors="pt" )
        # check if input_ids are returned and no labels
        self.assertIn("input_ids"   ,							_lowercase )
        self.assertIn("attention_mask"   ,							_lowercase )
        self.assertNotIn("labels"   ,							_lowercase )
        self.assertNotIn("decoder_attention_mask"   ,							_lowercase )







  @require_torch
  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     lowercase__			       =  [
         "Summary of the text.",
         "Another summary.",
     ]
     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase__			       =  tokenizer(text_target=_lowercase   ,							max_length=32   ,							padding="max_length"   ,							return_tensors="pt" )
        self.assertEqual(32   ,							targets["input_ids"].shape[1] )







  @require_torch
  def   UpperCAmelCase					(      self  :Dict ):






     '''simple docstring'''





     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase__			       =  tokenizer(
            ["I am a small frog" * 10_24, "I am a small frog"]   ,							padding=_lowercase   ,							truncation=_lowercase   ,							return_tensors="pt" )
        self.assertIsInstance(_lowercase   ,							_lowercase )
        self.assertEqual(batch.input_ids.shape   ,							(2, 10_24) )







  @require_torch
  def   UpperCAmelCase					(      self  :List[str] ):






     '''simple docstring'''





     lowercase__			       =  ["A long paragraph for summarization."]
     lowercase__			       =  [
         "Summary of the text.",
     ]
     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase__			       =  tokenizer(_lowercase   ,							text_target=_lowercase   ,							return_tensors="pt" )
        lowercase__			       =  inputs["input_ids"]
        lowercase__			       =  inputs["labels"]
        self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item() )
        self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item() )
        self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item() )
        self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item() )







  def   UpperCAmelCase					(      self  :Dict ):






     '''simple docstring'''





     pass







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





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

           # 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"] )   ,							)

           lowercase__			       =  tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"] )
           lowercase__			       =  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, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2] )
           self.assertSequenceEqual(tokens_r["input_ids"]   ,							[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2] )

           self.assertSequenceEqual(
               _lowercase   ,							["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"] )
           self.assertSequenceEqual(
               _lowercase   ,							["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"] )













from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments


def _A       (   ):
   lowercase__			       =  HfArgumentParser(__magic_name__	)
   lowercase__			       =  parser.parse_args_into_dataclasses()[0]
   lowercase__			       =  TensorFlowBenchmark(args=__magic_name__	)
   try:
      lowercase__			       =  parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      lowercase__			       =  "Arg --no_{0} is no longer used, please use --no-{0} instead."
      lowercase__			       =  " ".join(str(__magic_name__	).split(" "	)[:-1]	)
      lowercase__			       =  ""
      lowercase__			       =  eval(str(__magic_name__	).split(" "	)[-1]	)
      lowercase__			       =  []
      for arg in depreciated_args:
         # arg[2:] removes '--'
         if arg[2:] in TensorFlowBenchmark.deprecated_args:
            # arg[5:] removes '--no_'
            full_error_msg += arg_error_msg.format(arg[5:]	)
         else:
            wrong_args.append(__magic_name__	)
      if len(__magic_name__	) > 0:
         lowercase__			       =  full_error_msg + begin_error_msg + str(__magic_name__	)
      raise ValueError(__magic_name__	)
   benchmark.run()


if __name__ == "__main__":
  main()






