




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


UpperCAmelCase__				     = [
    {"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 		_A(       UpperCamelCase__							:			List[Any]=True				)    -> Optional[Any]:
       '''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 a (     __SCREAMING_SNAKE_CASE  ):
      """simple docstring"""

      UpperCamelCase_	:       Dict       	=		None
      UpperCamelCase_	:       List[str]       	=		None






      def     UpperCAmelCase_      ( self :     str				,							lowerCamelCase__ :     Tuple				,							lowerCamelCase__ :     Optional[Any]				)    ->						Optional[Any]:
             """simple docstring"""


             with TemporaryDirectory() as tmp_dir:
                    __lowercase      =    dataset_module_factory(lowerCamelCase__				,							cache_dir=lowerCamelCase__				)

                    __lowercase      =    import_main_class(dataset_module.module_path				,							dataset=lowerCamelCase__				)

                    __lowercase      =    builder_cls(
                        cache_dir=lowerCamelCase__				,							config_name=lowerCamelCase__				,							hash=dataset_module.hash				,							)

                    __lowercase      =    '''/'''.join(
                        [
                            HF_GCP_BASE_URL,
                            builder_instance._relative_data_dir(with_hash=lowerCamelCase__				).replace(os.sep				,							'''/'''				),
                            config.DATASET_INFO_FILENAME,
                        ]				)
                    __lowercase      =    cached_path(lowerCamelCase__				,							cache_dir=lowerCamelCase__				)
                    self.assertTrue(os.path.exists(lowerCamelCase__				)				)







@pytest.mark.integration
def 		_A(       UpperCamelCase__							:			Any				)    -> int:
       '''simple docstring'''


       __lowercase      =    tmp_path_factory.mktemp('''test_hf_gcp'''				) / '''test_wikipedia_simple'''
       __lowercase      =    dataset_module_factory('''wikipedia'''				,       cache_dir=UpperCamelCase__				)
       __lowercase      =    import_main_class(dataset_module.module_path				)
       __lowercase      =    builder_cls(
           cache_dir=UpperCamelCase__				,       config_name='''20220301.frr'''				,       hash=dataset_module.hash				,       )
       # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
       __lowercase      =    None
       builder_instance.download_and_prepare()
       __lowercase      =    builder_instance.as_dataset()
       assert ds







@pytest.mark.integration
def 		_A(       UpperCamelCase__							:			List[Any]				)    -> str:
       '''simple docstring'''


       __lowercase      =    dataset_module_factory('''wikipedia'''				,       cache_dir=UpperCamelCase__				)
       __lowercase      =    import_main_class(dataset_module.module_path				,       dataset=UpperCamelCase__				)
       __lowercase      =    builder_cls(
           cache_dir=UpperCamelCase__				,       config_name='''20220301.frr'''				,       hash=dataset_module.hash				,       )
       __lowercase      =    builder_instance.as_streaming_dataset()
       assert ds
       assert isinstance(UpperCamelCase__				,       UpperCamelCase__				)
       assert "train" in ds
       assert isinstance(ds['''train''']				,       UpperCamelCase__				)
       assert next(iter(ds['''train''']				)				)












import os







def 		_A(       UpperCamelCase__							:			str = "matrix.txt"				)    -> int:
							'''simple docstring'''


							with open(os.path.join(os.path.dirname(UpperCamelCase__				)				,       UpperCamelCase__				)				) as in_file:
														__lowercase      =    in_file.read()

							__lowercase      =    [[int(UpperCamelCase__				) for cell in row.split(''','''				)] for row in data.strip().splitlines()]
							__lowercase      =    [[0 for cell in row] for row in grid]
							__lowercase      =    len(grid[0]				)

							__lowercase      =    [[0 for i in range(UpperCamelCase__				)] for j in range(UpperCamelCase__				)]
							__lowercase      =    grid[0][0]
							for i in range(1				,       UpperCamelCase__				):
														__lowercase      =    grid[0][i] + dp[0][i - 1]
							for i in range(1				,       UpperCamelCase__				):
														__lowercase      =    grid[i][0] + dp[i - 1][0]

							for i in range(1				,       UpperCamelCase__				):
														for j in range(1				,       UpperCamelCase__				):
																					__lowercase      =    grid[i][j] + min(dp[i - 1][j]				,       dp[i][j - 1]				)

							return dp[-1][-1]


if __name__ == "__main__":
			print(F"""{solution() = }""")






