





'''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():
  lowerCAmelCase_   :   Optional[Any]       =					"pt"
elif is_tf_available():
  lowerCAmelCase_   :   List[str]       =					"tf"
else:
  lowerCAmelCase_   :   List[Any]       =					"jax"






class       UpperCamelCase__  (		__SCREAMING_SNAKE_CASE	,unittest.TestCase     ):
 lowerCAmelCase__					:			str								=						ByTaTokenizer
 lowerCAmelCase__					:			Union[str, Any]								=						False







 def 						__a   (				self			:   Dict		):




    '''simple docstring'''
    super().setUp()
    a__     = ByTaTokenizer()
    tokenizer.save_pretrained(self.tmpdirname		)







 @cached_property
 def 						__a   (				self			:   Dict		):




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







 def 						__a   (				self			:   Any , **lowerCamelCase			:   List[Any]		):




    '''simple docstring'''
    return self.tokenizer_class.from_pretrained(self.tmpdirname , **__snake_case		)







 def 						__a   (				self			:   Optional[int] , lowerCamelCase			:   Union[str, Any] , lowerCamelCase			:   int=False , lowerCamelCase			:   Union[str, Any]=2_0 , lowerCamelCase			:   Tuple=5		):




    '''simple docstring'''
    # 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(__snake_case		)		):
       try:
          a__     = tokenizer.decode([i] , clean_up_tokenization_spaces=__snake_case		)
       except UnicodeDecodeError:
          pass
       toks.append((i, tok)		)

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







 def 						__a   (				self			:   List[str]		):




    '''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 						__a   (				self			:   Optional[int]		):




    '''simple docstring'''
    a__     = self.ta_base_tokenizer
    a__     = '''Unicode €.'''
    a__     = tokenizer(__snake_case		)
    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"] , __snake_case		)

    # decoding
    a__     = tokenizer.decode(__snake_case		)
    self.assertEqual(__snake_case , "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"] , __snake_case		)
    # decoding
    a__     = tokenizer.decode(__snake_case		)
    self.assertEqual(__snake_case , "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 						__a   (				self			:   Any		):




    '''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(__snake_case , padding=__snake_case , return_tensors=__snake_case		)
    self.assertIsInstance(__snake_case , __snake_case		)

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

    self.assertListEqual(__snake_case , __snake_case		)

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







 def 						__a   (				self			:   Optional[Any]		):




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







 def 						__a   (				self			:   Optional[int]		):




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







 def 						__a   (				self			:   List[str]		):




    '''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(__snake_case , text_target=__snake_case		)

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







 def 						__a   (				self			:   List[str]		):




    '''simple docstring'''
    # 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(__snake_case , add_special_tokens=__snake_case		)
          tokenizer.save_pretrained(__snake_case		)

          a__     = tokenizer.__class__.from_pretrained(__snake_case		)
          a__     = after_tokenizer.encode(__snake_case , add_special_tokens=__snake_case		)
          self.assertListEqual(__snake_case , __snake_case		)

          shutil.rmtree(__snake_case		)

    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(__snake_case , add_special_tokens=__snake_case		)
          tokenizer.save_pretrained(__snake_case		)

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

          shutil.rmtree(__snake_case		)







 def 						__a   (				self			:   List[Any]		):




    '''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(__snake_case		)

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

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

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

          # 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(
              __snake_case , )
          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=__snake_case		)]
          a__     = tokenizer_class.from_pretrained(
              __snake_case , additional_special_tokens=__snake_case , )

          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 						__a   (				self			:   Optional[int]		):




    '''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(__snake_case		)

          a__     = tokenizer_class.from_pretrained(__snake_case		)

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







 def 						__a   (				self			:   Tuple		):




    '''simple docstring'''
    pass







 def 						__a   (				self			:   Dict		):




    '''simple docstring'''
    pass







 def 						__a   (				self			:   Optional[Any]		):




    '''simple docstring'''
    pass







 def 						__a   (				self			:   Union[str, Any]		):




    '''simple docstring'''
    pass







 def 						__a   (				self			:   int		):




    '''simple docstring'''
    # 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=__snake_case , do_lower_case=__snake_case		)
    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(__snake_case		)

          self.assertIsInstance(__snake_case , __snake_case		)







 def 						__a   (				self			:   Tuple		):




    '''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(
              __snake_case , skip_special_tokens=__snake_case		)

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

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

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

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










'''simple docstring'''


import argparse
import json

from tqdm import tqdm







def    _lowerCamelCase  ()   ->    Any:
			a__     = argparse.ArgumentParser()

			# Required parameters
			parser.add_argument(
			    "--src_path"					,  type=__lowerCamelCase					,  default="biencoder-nq-dev.json"					,  help="Path to raw DPR training data"					,  )
			parser.add_argument(
			    "--evaluation_set"					,  type=__lowerCamelCase					,  help="where to store parsed evaluation_set file"					,  )
			parser.add_argument(
			    "--gold_data_path"					,  type=__lowerCamelCase					,  help="where to store parsed gold_data_path file"					,  )
			a__     = parser.parse_args()

			with open(args.src_path					,  "r"     ) as src_file, open(args.evaluation_set					,  "w"     ) as eval_file, open(
			    args.gold_data_path					,  "w"     ) as gold_file:
						a__     = json.load(__lowerCamelCase     )
						for dpr_record in tqdm(__lowerCamelCase     ):
									a__     = dpr_record["question"]
									a__     = [context["title"] for context in dpr_record["positive_ctxs"]]
									eval_file.write(question + "\n"     )
									gold_file.write("\t".join(__lowerCamelCase     ) + "\n"     )


if __name__ == "__main__":
		main()



