


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


__lowerCAmelCase			=							[
    {'''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        snake_case_					(  snake_case=True					)  ->    Any:
       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=__UpperCamelCase				)				)
class   __a      (   __UpperCamelCase				):
 __lowercase			:							Union[str, Any]       					=			None
 __lowercase			:							Union[str, Any]       					=			None
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__    ,			lowerCAmelCase__			) ->    str:




        '''simple docstring'''
        with TemporaryDirectory() as tmp_dir:
               lowercase__:       List[Any]        =       dataset_module_factory(lowerCAmelCase__    ,			cache_dir=lowerCAmelCase__			)

               lowercase__:       Any        =       import_main_class(dataset_module.module_path    ,			dataset=lowerCAmelCase__			)

               lowercase__:       DatasetBuilder        =       builder_cls(
                   cache_dir=lowerCAmelCase__    ,			config_name=lowerCAmelCase__    ,			hash=dataset_module.hash    ,			)

               lowercase__:       List[Any]        =       '/'.join(
                   [
                       HF_GCP_BASE_URL,
                       builder_instance._relative_data_dir(with_hash=lowerCAmelCase__			).replace(os.sep    ,			'/'			),
                       config.DATASET_INFO_FILENAME,
                   ]			)
               lowercase__:       int        =       cached_path(lowerCAmelCase__    ,			cache_dir=lowerCAmelCase__			)
               self.assertTrue(os.path.exists(lowerCAmelCase__			)			)





@pytest.mark.integration
def        snake_case_					(  snake_case					)  ->    Tuple:
       lowercase__:       List[str]        =       tmp_path_factory.mktemp('test_hf_gcp'					) / 'test_wikipedia_simple'
       lowercase__:       List[str]        =       dataset_module_factory('wikipedia'      ,							cache_dir=snake_case					)
       lowercase__:       str        =       import_main_class(dataset_module.module_path					)
       lowercase__:       DatasetBuilder        =       builder_cls(
           cache_dir=snake_case      ,							config_name='20220301.frr'      ,							hash=dataset_module.hash      ,							)
       # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
       lowercase__:       str        =       None
       builder_instance.download_and_prepare()
       lowercase__:       List[str]        =       builder_instance.as_dataset()
       assert ds




@pytest.mark.integration
def        snake_case_					(  snake_case					)  ->    List[Any]:
       lowercase__:       str        =       dataset_module_factory('wikipedia'      ,							cache_dir=snake_case					)
       lowercase__:       Any        =       import_main_class(dataset_module.module_path      ,							dataset=snake_case					)
       lowercase__:       DatasetBuilder        =       builder_cls(
           cache_dir=snake_case      ,							config_name='20220301.frr'      ,							hash=dataset_module.hash      ,							)
       lowercase__:       Tuple        =       builder_instance.as_streaming_dataset()
       assert ds
       assert isinstance(snake_case      ,							snake_case					)
       assert "train" in ds
       assert isinstance(ds['train']      ,							snake_case					)
       assert next(iter(ds['train']					)					)



from math import pow




def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case      ,							snake_case      ,							snake_case      ,							)  ->    tuple[int, int]:
       if current_sum == needed_sum:
              # If the sum of the powers is equal to needed_sum, then we have a solution.
              solutions_count += 1
              return current_sum, solutions_count

       lowercase__:       int        =       int(pow(snake_case      ,							snake_case					)					)
       if current_sum + i_to_n <= needed_sum:
              # If the sum of the powers is less than needed_sum, then continue adding powers.
              current_sum += i_to_n
              lowercase__      ,						lowercase__:       Any        =       backtrack(
                  snake_case      ,							snake_case      ,							current_number + 1      ,							snake_case      ,							snake_case					)
              current_sum -= i_to_n
       if i_to_n < needed_sum:
              # If the power of i is less than needed_sum, then try with the next power.
              lowercase__      ,						lowercase__:       Optional[int]        =       backtrack(
                  snake_case      ,							snake_case      ,							current_number + 1      ,							snake_case      ,							snake_case					)
       return current_sum, solutions_count




def        snake_case_					(  snake_case      ,							snake_case					)  ->    int:
       if not (1 <= needed_sum <= 10_00 and 2 <= power <= 10):
              raise ValueError(
                  'Invalid input\n'
                  'needed_sum must be between 1 and 1000, power between 2 and 10.'					)

       return backtrack(snake_case      ,							snake_case      ,							1      ,							0      ,							0					)[1]  # Return the solutions_count


if __name__ == "__main__":
 import doctest

 doctest.testmod()


