

"""simple docstring"""


import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
  UpperCAmelCase													="pt"
elif is_tf_available():
  UpperCAmelCase													="tf"
else:
  UpperCAmelCase													="jax"





class lowerCamelCase__   (				SCREAMING_SNAKE_CASE     ,   unittest.TestCase    ):



    '''simple docstring'''




    _lowerCamelCase					=   ByTaTokenizer
    _lowerCamelCase					=   False




    def UpperCamelCase__		( self    )    ->      List[Any]:
          super().setUp()
          A				  =		ByTaTokenizer()
          tokenizer.save_pretrained(self.tmpdirname    )




    @cached_property
    def UpperCamelCase__		( self    )    ->      Union[str, Any]:
          return ByTaTokenizer.from_pretrained("""google/byt5-small"""    )




    def UpperCamelCase__		( self ,**lowerCamelCase_    )    ->      ByTaTokenizer:
          return self.tokenizer_class.from_pretrained(self.tmpdirname ,**lowerCamelCase_    )




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_=False ,lowerCamelCase_=2_0 ,lowerCamelCase_=5    )    ->      Tuple[str, list]:
          # XXX The default common tokenizer tests assume that every ID is decodable on its own.
          # This assumption is invalid for ByT5 because single bytes might not be
          # valid utf-8 (byte 128 for instance).
          # Here we're overriding the smallest possible method to provide
          # a clean sequence without making the same assumption.

          A				  =		[]
          for i in range(len(lowerCamelCase_    )    ):
                try:
                      A				  =		tokenizer.decode([i] ,clean_up_tokenization_spaces=lowerCamelCase_    )
                except UnicodeDecodeError:
                      pass
                toks.append((i, tok)    )

          A				  =		list(filter(lambda lowerCamelCase_    : re.match(r"""^[ a-zA-Z]+$""" ,t[1]    ) ,lowerCamelCase_    )    )
          A				  =		list(filter(lambda lowerCamelCase_    : [t[0]] == tokenizer.encode(t[1] ,add_special_tokens=lowerCamelCase_    ) ,lowerCamelCase_    )    )
          if max_length is not None and len(lowerCamelCase_    ) > max_length:
                A				  =		toks[:max_length]
          if min_length is not None and len(lowerCamelCase_    ) < min_length and len(lowerCamelCase_    ) > 0:
                while len(lowerCamelCase_    ) < min_length:
                      A				  =		toks + toks
        # toks_str = [t[1] for t in toks]
          A				  =		[t[0] for t in toks]

          # Ensure consistency
          A				  =		tokenizer.decode(lowerCamelCase_ ,clean_up_tokenization_spaces=lowerCamelCase_    )
          if " " not in output_txt and len(lowerCamelCase_    ) > 1:
                A				  =		(
                    tokenizer.decode([toks_ids[0]] ,clean_up_tokenization_spaces=lowerCamelCase_    )
                    + """ """
                    + tokenizer.decode(toks_ids[1:] ,clean_up_tokenization_spaces=lowerCamelCase_    )
                )
          if with_prefix_space:
                A				  =		""" """ + output_txt
          A				  =		tokenizer.encode(lowerCamelCase_ ,add_special_tokens=lowerCamelCase_    )
          return output_txt, output_ids




    def UpperCamelCase__		( self    )    ->      Optional[int]:
          A				  =		self.ta_base_tokenizer
          A				  =		tokenizer(["""hi</s>""", """I went to the gym</s>""", """</s>"""]    )
          A				  =		tokenizer(["""hi""", """I went to the gym""", """"""]    )
          self.assertListEqual(batch_with_eos_added["""input_ids"""] ,batch_without_eos_added["""input_ids"""]    )




    def UpperCamelCase__		( self    )    ->      List[str]:
          A				  =		self.ta_base_tokenizer
          A				  =		"""Unicode €."""
          A				  =		tokenizer(lowerCamelCase_    )
          A				  =		[8_8, 1_1_3, 1_0_8, 1_0_2, 1_1_4, 1_0_3, 1_0_4, 3_5, 2_2_9, 1_3_3, 1_7_5, 4_9, 1]
          self.assertEqual(encoded["""input_ids"""] ,lowerCamelCase_    )

          # decoding
          A				  =		tokenizer.decode(lowerCamelCase_    )
          self.assertEqual(lowerCamelCase_ ,"""Unicode €.</s>"""    )

          A				  =		tokenizer("""e è é ê ë"""    )
          A				  =		[1_0_4, 3_5, 1_9_8, 1_7_1, 3_5, 1_9_8, 1_7_2, 3_5, 1_9_8, 1_7_3, 3_5, 1_9_8, 1_7_4, 1]
          self.assertEqual(encoded["""input_ids"""] ,lowerCamelCase_    )
          # decoding
          A				  =		tokenizer.decode(lowerCamelCase_    )
          self.assertEqual(lowerCamelCase_ ,"""e è é ê ë</s>"""    )

          # encode/decode, but with `encode` instead of `__call__`
          self.assertEqual(tokenizer.decode(tokenizer.encode("""e è é ê ë"""    )    ) ,"""e è é ê ë</s>"""    )




    def UpperCamelCase__		( self    )    ->      Any:
          A				  =		self.ta_base_tokenizer
          A				  =		["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
          # fmt: off
          A				  =		[6_8, 3_5, 1_1_1, 1_1_4, 1_1_3, 1_0_6, 3_5, 1_1_5, 1_0_0, 1_1_7, 1_0_0, 1_0_6, 1_1_7, 1_0_0, 1_1_5, 1_0_7, 3_5, 1_0_5, 1_1_4, 1_1_7, 3_5, 1_1_8, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_0_8, 1_2_5, 1_0_0, 1_1_9, 1_0_8, 1_1_4, 1_1_3, 4_9, 1, 0]
          # fmt: on
          A				  =		tokenizer(lowerCamelCase_ ,padding=lowerCamelCase_ ,return_tensors=lowerCamelCase_    )
          self.assertIsInstance(lowerCamelCase_ ,lowerCamelCase_    )

          if FRAMEWORK != "jax":
                A				  =		list(batch.input_ids.numpy()[0]    )
          else:
                A				  =		list(batch.input_ids.tolist()[0]    )

          self.assertListEqual(lowerCamelCase_ ,lowerCamelCase_    )

          self.assertEqual((2, 3_7) ,batch.input_ids.shape    )
          self.assertEqual((2, 3_7) ,batch.attention_mask.shape    )




    def UpperCamelCase__		( self    )    ->      List[str]:
          A				  =		self.ta_base_tokenizer
          A				  =		["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
          A				  =		tokenizer(lowerCamelCase_ ,padding=lowerCamelCase_ ,return_tensors=lowerCamelCase_    )
          # check if input_ids are returned and no decoder_input_ids
          self.assertIn("""input_ids""" ,lowerCamelCase_    )
          self.assertIn("""attention_mask""" ,lowerCamelCase_    )
          self.assertNotIn("""decoder_input_ids""" ,lowerCamelCase_    )
          self.assertNotIn("""decoder_attention_mask""" ,lowerCamelCase_    )




    def UpperCamelCase__		( self    )    ->      Optional[int]:
          A				  =		self.ta_base_tokenizer
          A				  =		[
              """Summary of the text.""",
              """Another summary.""",
          ]
          A				  =		tokenizer(
              text_target=lowerCamelCase_ ,max_length=3_2 ,padding="""max_length""" ,truncation=lowerCamelCase_ ,return_tensors=lowerCamelCase_    )
          self.assertEqual(3_2 ,targets["""input_ids"""].shape[1]    )




    def UpperCamelCase__		( self    )    ->      List[str]:
          A				  =		self.ta_base_tokenizer
          A				  =		["""A long paragraph for summarization. </s>"""]
          A				  =		["""Summary of the text. </s>"""]
          # fmt: off
          A				  =		[6_8, 3_5, 1_1_1, 1_1_4, 1_1_3, 1_0_6, 3_5, 1_1_5, 1_0_0, 1_1_7, 1_0_0, 1_0_6, 1_1_7, 1_0_0, 1_1_5, 1_0_7, 3_5, 1_0_5, 1_1_4, 1_1_7, 3_5, 1_1_8, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_0_8, 1_2_5, 1_0_0, 1_1_9, 1_0_8, 1_1_4, 1_1_3, 4_9, 3_5, 1]
          A				  =		[8_6, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_2_4, 3_5, 1_1_4, 1_0_5, 3_5, 1_1_9, 1_0_7, 1_0_4, 3_5, 1_1_9, 1_0_4, 1_2_3, 1_1_9, 4_9, 3_5, 1]
          # fmt: on

          A				  =		tokenizer(lowerCamelCase_ ,text_target=lowerCamelCase_    )

          self.assertEqual(lowerCamelCase_ ,batch["""input_ids"""][0]    )
          self.assertEqual(lowerCamelCase_ ,batch["""labels"""][0]    )




    def UpperCamelCase__		( self    )    ->      Optional[Any]:
          # safety check on max_len default value so we are sure the test works
          A				  =		self.get_tokenizers()
          for tokenizer in tokenizers:
                with self.subTest(f'{tokenizer.__class__.__name__}'    ):
                      self.assertNotEqual(tokenizer.model_max_length ,4_2    )

        # Now let's start the test
          A				  =		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
                      A				  =		tempfile.mkdtemp()

                      A				  =		""" He is very happy, UNwant\u00E9d,running"""
                      A				  =		tokenizer.encode(lowerCamelCase_ ,add_special_tokens=lowerCamelCase_    )
                      tokenizer.save_pretrained(lowerCamelCase_    )

                      A				  =		tokenizer.__class__.from_pretrained(lowerCamelCase_    )
                      A				  =		after_tokenizer.encode(lowerCamelCase_ ,add_special_tokens=lowerCamelCase_    )
                      self.assertListEqual(lowerCamelCase_ ,lowerCamelCase_    )

                      shutil.rmtree(lowerCamelCase_    )

          A				  =		self.get_tokenizers(model_max_length=4_2    )
          for tokenizer in tokenizers:
                with self.subTest(f'{tokenizer.__class__.__name__}'    ):
                      # Isolate this from the other tests because we save additional tokens/etc
                      A				  =		tempfile.mkdtemp()

                      A				  =		""" He is very happy, UNwant\u00E9d,running"""
                      tokenizer.add_tokens(["""bim""", """bambam"""]    )
                      A				  =		tokenizer.additional_special_tokens
                      additional_special_tokens.append("""new_additional_special_token"""    )
                      tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}    )
                      A				  =		tokenizer.encode(lowerCamelCase_ ,add_special_tokens=lowerCamelCase_    )
                      tokenizer.save_pretrained(lowerCamelCase_    )

                      A				  =		tokenizer.__class__.from_pretrained(lowerCamelCase_    )
                      A				  =		after_tokenizer.encode(lowerCamelCase_ ,add_special_tokens=lowerCamelCase_    )
                      self.assertListEqual(lowerCamelCase_ ,lowerCamelCase_    )
                      self.assertIn("""new_additional_special_token""" ,after_tokenizer.additional_special_tokens    )
                      self.assertEqual(after_tokenizer.model_max_length ,4_2    )

                      A				  =		tokenizer.__class__.from_pretrained(lowerCamelCase_ ,model_max_length=4_3    )
                      self.assertEqual(tokenizer.model_max_length ,4_3    )

                      shutil.rmtree(lowerCamelCase_    )




    def UpperCamelCase__		( self    )    ->      Tuple:
          A				  =		[]
          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(lowerCamelCase_    )

                      with open(os.path.join(lowerCamelCase_ ,"""special_tokens_map.json"""    ) ,encoding="""utf-8"""    ) as json_file:
                            A				  =		json.load(lowerCamelCase_    )

                      with open(os.path.join(lowerCamelCase_ ,"""tokenizer_config.json"""    ) ,encoding="""utf-8"""    ) as json_file:
                            A				  =		json.load(lowerCamelCase_    )

                      A				  =		[f'<extra_id_{i}>' for i in range(1_2_5    )]

                      A				  =		added_tokens_extra_ids + [
                          """an_additional_special_token"""
                      ]
                      A				  =		added_tokens_extra_ids + [
                          """an_additional_special_token"""
                      ]

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

                      # 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
                      A				  =		tokenizer_class.from_pretrained(
                          lowerCamelCase_ ,)
                      self.assertIn(
                          """an_additional_special_token""" ,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(
                          ["""an_additional_special_token"""] ,tokenizer_without_change_in_init.convert_ids_to_tokens(
                              tokenizer_without_change_in_init.convert_tokens_to_ids(["""an_additional_special_token"""]    )    ) ,)

                      # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                      A				  =		added_tokens_extra_ids + [AddedToken("""a_new_additional_special_token""" ,lstrip=lowerCamelCase_    )]
                      A				  =		tokenizer_class.from_pretrained(
                          lowerCamelCase_ ,additional_special_tokens=lowerCamelCase_ ,)

                      self.assertIn("""a_new_additional_special_token""" ,tokenizer.additional_special_tokens    )
                      self.assertEqual(
                          ["""a_new_additional_special_token"""] ,tokenizer.convert_ids_to_tokens(
                              tokenizer.convert_tokens_to_ids(["""a_new_additional_special_token"""]    )    ) ,)




    def UpperCamelCase__		( self    )    ->      Optional[int]:
          A				  =		[]
          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(lowerCamelCase_    )

                      A				  =		tokenizer_class.from_pretrained(lowerCamelCase_    )

                      self.assertTrue(tokenizer.decode([2_5_5]    ) == """"""    )




    def UpperCamelCase__		( self    )    ->      int:
          pass




    def UpperCamelCase__		( self    )    ->      int:
          pass




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




    def UpperCamelCase__		( self    )    ->      Optional[int]:
          pass




    def UpperCamelCase__		( self    )    ->      Any:
          # The default common tokenizer tests uses invalid tokens for ByT5 that can only accept one-character strings
          # and special added tokens as tokens
          A				  =		self.get_tokenizers(fast=lowerCamelCase_ ,do_lower_case=lowerCamelCase_    )
          for tokenizer in tokenizers:
                with self.subTest(f'{tokenizer.__class__.__name__}'    ):
                      A				  =		["""t""", """h""", """i""", """s""", """ """, """i""", """s""", """ """, """a""", """ """, """t""", """e""", """x""", """t""", """</s>"""]
                      A				  =		tokenizer.convert_tokens_to_string(lowerCamelCase_    )

                      self.assertIsInstance(lowerCamelCase_ ,lowerCamelCase_    )




    def UpperCamelCase__		( self    )    ->      Union[str, Any]:
          A				  =		self.get_tokenizers()
          for tokenizer in tokenizers:
                with self.subTest(f'{tokenizer.__class__.__name__}'    ):
                      A				  =		[
                          """bos_token""",
                          """eos_token""",
                          """unk_token""",
                          """sep_token""",
                          """pad_token""",
                          """cls_token""",
                          """mask_token""",
                      ]

                      A				  =		0
                      A				  =		tokenizer.convert_ids_to_tokens(
                          lowerCamelCase_ ,skip_special_tokens=lowerCamelCase_    )

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

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

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

                      setattr(lowerCamelCase_ ,"""additional_special_tokens_ids""" ,[token_id_to_test_setters]    )
                      self.assertListEqual(getattr(lowerCamelCase_ ,"""additional_special_tokens"""    ) ,[token_to_test_setters]    )
                      self.assertListEqual(getattr(lowerCamelCase_ ,"""additional_special_tokens_ids"""    ) ,[token_id_to_test_setters]    )







"""simple docstring"""


import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase													=get_tests_dir("fixtures/test_sentencepiece_bpe.model")





class lowerCamelCase__   (				SCREAMING_SNAKE_CASE     ,   unittest.TestCase    ):



    '''simple docstring'''




    _lowerCamelCase					=   BartphoTokenizer
    _lowerCamelCase					=   False
    _lowerCamelCase					=   True




    def UpperCamelCase__		( self    )    ->      str:
          super().setUp()

          A				  =		["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]
          A				  =		dict(zip(lowerCamelCase_ ,range(len(lowerCamelCase_    )    )    )    )
          A				  =		{"""unk_token""": """<unk>"""}

          A				  =		os.path.join(self.tmpdirname ,VOCAB_FILES_NAMES["""monolingual_vocab_file"""]    )
          with open(self.monolingual_vocab_file ,"""w""" ,encoding="""utf-8"""    ) as fp:
                for token in vocab_tokens:
                      fp.write(f'{token} {vocab_tokens[token]}\n'    )

          A				  =		BartphoTokenizer(lowerCamelCase_ ,self.monolingual_vocab_file ,**self.special_tokens_map    )
          tokenizer.save_pretrained(self.tmpdirname    )




    def UpperCamelCase__		( self ,**lowerCamelCase_    )    ->      Tuple:
          kwargs.update(self.special_tokens_map    )
          return BartphoTokenizer.from_pretrained(self.tmpdirname ,**lowerCamelCase_    )




    def UpperCamelCase__		( self ,lowerCamelCase_    )    ->      Optional[Any]:
          A				  =		"""This is a là test"""
          A				  =		"""This is a<unk><unk> test"""
          return input_text, output_text




    def UpperCamelCase__		( self    )    ->      int:
          A				  =		BartphoTokenizer(lowerCamelCase_ ,self.monolingual_vocab_file ,**self.special_tokens_map    )
          A				  =		"""This is a là test"""
          A				  =		"""▁This ▁is ▁a ▁l à ▁t est""".split()
          A				  =		tokenizer.tokenize(lowerCamelCase_    )
          self.assertListEqual(lowerCamelCase_ ,lowerCamelCase_    )

          A				  =		tokens + [tokenizer.unk_token]
          A				  =		[4, 5, 6, 3, 3, 7, 8, 3]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase_    ) ,lowerCamelCase_    )




