






def        lowerCAmelCase (      UpperCamelCase_:							Tuple     , UpperCamelCase_:							Optional[Any]					)       ->							str:







  '''simple docstring'''







  assert x is not None
  assert y is not None

  _a							=	len(_lowerCamelCase					)
  _a							=	len(_lowerCamelCase					)

  # declaring the array for storing the dp values
  _a							=	[[0] * (n + 1) for _ in range(m + 1					)]  # noqa: E741

  for i in range(1     , m + 1					):
    for j in range(1     , n + 1					):
      _a							=	1 if x[i - 1] == y[j - 1] else 0

      _a							=	max(l[i - 1][j]     , l[i][j - 1]     , l[i - 1][j - 1] + match					)

  _a							=	""
  _a							=	m, n
  while i > 0 and j > 0:
    _a							=	1 if x[i - 1] == y[j - 1] else 0

    if l[i][j] == l[i - 1][j - 1] + match:
      if match == 1:
        _a							=	x[i - 1] + seq
      i -= 1
      j -= 1
    elif l[i][j] == l[i - 1][j]:
      i -= 1
    else:
      j -= 1

  return l[m][n], seq


if __name__ == "__main__":
     UpperCamelCase							       =    """AGGTAB"""
     UpperCamelCase							       =    """GXTXAYB"""
     UpperCamelCase							       =    4
     UpperCamelCase							       =    """GTAB"""

     UpperCamelCase       ,							UpperCamelCase							       =    longest_common_subsequence(a, b)
     print("""len =""", ln, """, sub-sequence =""", subseq)
     import doctest

     doctest.testmod()










"""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    lowercase_    (_UpperCAmelCase,    unittest.TestCase     ):
      A__	:		List[str]       			=				ByTaTokenizer
      A__	:		List[Any]       			=				False






      def 			lowerCamelCase__    (    self	)	->Any:







        '''simple docstring'''


        super().setUp()
        _a							=	ByTaTokenizer()
        tokenizer.save_pretrained(self.tmpdirname	)






      @cached_property
      def 			lowerCamelCase__    (    self	)	->List[str]:







        '''simple docstring'''


        return ByTaTokenizer.from_pretrained("google/byt5-small"	)






      def 			lowerCamelCase__    (    self     ,     **a_	)	->ByTaTokenizer:







        '''simple docstring'''


        return self.tokenizer_class.from_pretrained(self.tmpdirname     ,     **a_	)






      def 			lowerCamelCase__    (    self     ,     a_     ,     a_=False     ,     a_=2_0     ,     a_=5	)	->Tuple[str, list]:







        '''simple docstring'''


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

        _a							=	list(filter(lambda a_	: re.match(R"^[ a-zA-Z]+$"     ,     t[1]	)     ,     a_	)	)
        _a							=	list(filter(lambda a_	: [t[0]] == tokenizer.encode(t[1]     ,     add_special_tokens=a_	)     ,     a_	)	)
        if max_length is not None and len(a_	) > max_length:
          _a							=	toks[:max_length]
        if min_length is not None and len(a_	) < min_length and len(a_	) > 0:
          while len(a_	) < 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(a_     ,     clean_up_tokenization_spaces=a_	)
        if " " not in output_txt and len(a_	) > 1:
          _a							=	(
              tokenizer.decode([toks_ids[0]]     ,     clean_up_tokenization_spaces=a_	)
              + " "
              + tokenizer.decode(toks_ids[1:]     ,     clean_up_tokenization_spaces=a_	)
          )
        if with_prefix_space:
          _a							=	" " + output_txt
        _a							=	tokenizer.encode(a_     ,     add_special_tokens=a_	)
        return output_txt, output_ids






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







        '''simple docstring'''


        _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 			lowerCamelCase__    (    self	)	->Tuple:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	"Unicode €."
        _a							=	tokenizer(a_	)
        _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"]     ,     a_	)

        # decoding
        _a							=	tokenizer.decode(a_	)
        self.assertEqual(a_     ,     "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"]     ,     a_	)
        # decoding
        _a							=	tokenizer.decode(a_	)
        self.assertEqual(a_     ,     "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 			lowerCamelCase__    (    self	)	->int:







        '''simple docstring'''


        _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(a_     ,     padding=a_     ,     return_tensors=a_	)
        self.assertIsInstance(a_     ,     a_	)

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

        self.assertListEqual(a_     ,     a_	)

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






      def 			lowerCamelCase__    (    self	)	->Dict:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	["A long paragraph for summarization.", "Another paragraph for summarization."]
        _a							=	tokenizer(a_     ,     padding=a_     ,     return_tensors=a_	)
        # check if input_ids are returned and no decoder_input_ids
        self.assertIn("input_ids"     ,     a_	)
        self.assertIn("attention_mask"     ,     a_	)
        self.assertNotIn("decoder_input_ids"     ,     a_	)
        self.assertNotIn("decoder_attention_mask"     ,     a_	)






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







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	[
            "Summary of the text.",
            "Another summary.",
        ]
        _a							=	tokenizer(
            text_target=a_     ,     max_length=3_2     ,     padding="max_length"     ,     truncation=a_     ,     return_tensors=a_	)
        self.assertEqual(3_2     ,     targets["input_ids"].shape[1]	)






      def 			lowerCamelCase__    (    self	)	->Dict:







        '''simple docstring'''


        _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(a_     ,     text_target=a_	)

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






      def 			lowerCamelCase__    (    self	)	->int:







        '''simple docstring'''


        _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(a_     ,     add_special_tokens=a_	)
            tokenizer.save_pretrained(a_	)

            _a							=	tokenizer.__class__.from_pretrained(a_	)
            _a							=	after_tokenizer.encode(a_     ,     add_special_tokens=a_	)
            self.assertListEqual(a_     ,     a_	)

            shutil.rmtree(a_	)

        _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(a_     ,     add_special_tokens=a_	)
            tokenizer.save_pretrained(a_	)

            _a							=	tokenizer.__class__.from_pretrained(a_	)
            _a							=	after_tokenizer.encode(a_     ,     add_special_tokens=a_	)
            self.assertListEqual(a_     ,     a_	)
            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(a_     ,     model_max_length=4_3	)
            self.assertEqual(tokenizer.model_max_length     ,     4_3	)

            shutil.rmtree(a_	)






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







        '''simple docstring'''


        _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(a_	)

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

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

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

            # 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(
                a_     ,     )
            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=a_	)]
            _a							=	tokenizer_class.from_pretrained(
                a_     ,     additional_special_tokens=a_     ,     )

            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 			lowerCamelCase__    (    self	)	->List[str]:







        '''simple docstring'''


        _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(a_	)

            _a							=	tokenizer_class.from_pretrained(a_	)

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






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







        '''simple docstring'''


        pass






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







        '''simple docstring'''


        pass






      def 			lowerCamelCase__    (    self	)	->Tuple:







        '''simple docstring'''


        pass






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







        '''simple docstring'''


        pass






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







        '''simple docstring'''


        _a							=	self.get_tokenizers(fast=a_     ,     do_lower_case=a_	)
        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(a_	)

            self.assertIsInstance(a_     ,     a_	)






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







        '''simple docstring'''


        _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(
                a_     ,     skip_special_tokens=a_	)

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

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

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

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


