





import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


__A									=				[
    {"dataset": "wikipedia", "config_name": "20220301.de"},
    {"dataset": "wikipedia", "config_name": "20220301.en"},
    {"dataset": "wikipedia", "config_name": "20220301.fr"},
    {"dataset": "wikipedia", "config_name": "20220301.frr"},
    {"dataset": "wikipedia", "config_name": "20220301.it"},
    {"dataset": "wikipedia", "config_name": "20220301.simple"},
    {"dataset": "snli", "config_name": "plain_text"},
    {"dataset": "eli5", "config_name": "LFQA_reddit"},
    {"dataset": "wiki40b", "config_name": "en"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.compressed"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.no_index"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.multiset.no_index"},
    {"dataset": "natural_questions", "config_name": "default"},
]





def      lowerCAmelCase_ (       __a=True		)     ->		int:







  """simple docstring"""





  if with_config:
    return [
        {
            "testcase_name": d["dataset"] + "/" + d["config_name"],
            "dataset": d["dataset"],
            "config_name": d["config_name"],
        }
        for d in DATASETS_ON_HF_GCP
    ]
  else:
    return [
        {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
    ]



@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=__SCREAMING_SNAKE_CASE    )    )
class    _SCREAMING_SNAKE_CASE						(	__SCREAMING_SNAKE_CASE    ):







 '''simple docstring'''
 lowercase_		=			None
 lowercase_		=			None

 def 							SCREAMING_SNAKE_CASE_					(self				:   Tuple       , UpperCAmelCase_				:   Any       , UpperCAmelCase_				:   Tuple)       ->Optional[int]:



   '''simple docstring'''



   with TemporaryDirectory() as tmp_dir:
     lowerCamelCase__:      List[str]			  =dataset_module_factory(UpperCAmelCase_       , cache_dir=UpperCAmelCase_)

     lowerCamelCase__:      List[Any]			  =import_main_class(dataset_module.module_path       , dataset=UpperCAmelCase_)

     lowerCamelCase__:      DatasetBuilder			  =builder_cls(
         cache_dir=UpperCAmelCase_       , config_name=UpperCAmelCase_       , hash=dataset_module.hash       , )

     lowerCamelCase__:      int			  ="/".join(
         [
             HF_GCP_BASE_URL,
             builder_instance._relative_data_dir(with_hash=UpperCAmelCase_).replace(os.sep       , "/"),
             config.DATASET_INFO_FILENAME,
         ])
     lowerCamelCase__:      str			  =cached_path(UpperCAmelCase_       , cache_dir=UpperCAmelCase_)
     self.assertTrue(os.path.exists(UpperCAmelCase_))





@pytest.mark.integration
def      lowerCAmelCase_ (       __a		)     ->		Dict:







  """simple docstring"""





  lowerCamelCase__:      int			  =tmp_path_factory.mktemp("test_hf_gcp"		) / "test_wikipedia_simple"
  lowerCamelCase__:      List[str]			  =dataset_module_factory("wikipedia"	,    cache_dir=__a		)
  lowerCamelCase__:      Optional[Any]			  =import_main_class(dataset_module.module_path		)
  lowerCamelCase__:      DatasetBuilder			  =builder_cls(
      cache_dir=__a	,    config_name="20220301.frr"	,    hash=dataset_module.hash	,    )
  # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
  lowerCamelCase__:      Union[str, Any]			  =None
  builder_instance.download_and_prepare()
  lowerCamelCase__:      int			  =builder_instance.as_dataset()
  assert ds






@pytest.mark.integration
def      lowerCAmelCase_ (       __a		)     ->		List[str]:







  """simple docstring"""





  lowerCamelCase__:      int			  =dataset_module_factory("wikipedia"	,    cache_dir=__a		)
  lowerCamelCase__:      Dict			  =import_main_class(dataset_module.module_path	,    dataset=__a		)
  lowerCamelCase__:      DatasetBuilder			  =builder_cls(
      cache_dir=__a	,    config_name="20220301.frr"	,    hash=dataset_module.hash	,    )
  lowerCamelCase__:      Tuple			  =builder_instance.as_streaming_dataset()
  assert ds
  assert isinstance(__a	,    __a		)
  assert "train" in ds
  assert isinstance(ds["train"]	,    __a		)
  assert next(iter(ds["train"]		)		)








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


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



class    _SCREAMING_SNAKE_CASE						(	__SCREAMING_SNAKE_CASE    ,							unittest.TestCase    ):







 '''simple docstring'''
 lowercase_		=			BartphoTokenizer
 lowercase_		=			False
 lowercase_		=			True

 def 							SCREAMING_SNAKE_CASE_					(self				:   List[Any])       ->Tuple:



   '''simple docstring'''



   super().setUp()

   lowerCamelCase__:      int			  =["▁This", "▁is", "▁a", "▁t", "est"]
   lowerCamelCase__:      Tuple			  =dict(zip(UpperCAmelCase_       , range(len(UpperCAmelCase_))))
   lowerCamelCase__:      List[Any]			  ={"unk_token": "<unk>"}

   lowerCamelCase__:      Dict			  =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""")

   lowerCamelCase__:      Dict			  =BartphoTokenizer(UpperCAmelCase_       , self.monolingual_vocab_file       , **self.special_tokens_map)
   tokenizer.save_pretrained(self.tmpdirname)

 def 							SCREAMING_SNAKE_CASE_					(self				:   Optional[int]       , **UpperCAmelCase_				:   Optional[Any])       ->str:



   '''simple docstring'''



   kwargs.update(self.special_tokens_map)
   return BartphoTokenizer.from_pretrained(self.tmpdirname       , **UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_					(self				:   Union[str, Any]       , UpperCAmelCase_				:   Optional[Any])       ->List[Any]:



   '''simple docstring'''



   lowerCamelCase__:      Optional[int]			  ="This is a là test"
   lowerCamelCase__:      Optional[Any]			  ="This is a<unk><unk> test"
   return input_text, output_text







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



   '''simple docstring'''



   lowerCamelCase__:      str			  =BartphoTokenizer(UpperCAmelCase_       , self.monolingual_vocab_file       , **self.special_tokens_map)
   lowerCamelCase__:      List[Any]			  ="This is a là test"
   lowerCamelCase__:      Optional[int]			  ="▁This ▁is ▁a ▁l à ▁t est".split()
   lowerCamelCase__:      Optional[int]			  =tokenizer.tokenize(UpperCAmelCase_)
   self.assertListEqual(UpperCAmelCase_       , UpperCAmelCase_)

   lowerCamelCase__:      Tuple			  =tokens + [tokenizer.unk_token]
   lowerCamelCase__:      List[Any]			  =[4, 5, 6, 3, 3, 7, 8, 3]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_)       , UpperCAmelCase_)

