






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    :   Union[str, Any]        =			[
    {"""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__							(							UpperCAmelCase							:  List[Any]=True       ):



				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=lowercase_		)		)
class 	_UpperCAmelCase  (  lowercase_		):




						"""simple docstring"""



						A          =    None
						A          =    None
						def 			snake_case_      (   self    ,	_lowerCAmelCase    ,	_lowerCAmelCase		):



										'''simple docstring'''



										with TemporaryDirectory() as tmp_dir:
														lowerCAmelCase__   :Optional[Any]      							=				dataset_module_factory(lowerCamelCase_    ,	cache_dir=lowerCamelCase_		)

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

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

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





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


@pytest.mark.integration
def 				snake_case__							(							UpperCAmelCase							:  Dict       ):
				lowerCAmelCase__   :Optional[Any]      							=				dataset_module_factory("wikipedia"    ,			cache_dir=lowerCamelCase_       )
				lowerCAmelCase__   :Tuple      							=				import_main_class(dataset_module.module_path    ,			dataset=lowerCamelCase_       )
				lowerCAmelCase__   :DatasetBuilder      							=				builder_cls(
				    cache_dir=lowerCamelCase_    ,			config_name="20220301.frr"    ,			hash=dataset_module.hash    ,			)
				lowerCAmelCase__   :Any      							=				builder_instance.as_streaming_dataset()
				assert ds
				assert isinstance(lowerCamelCase_    ,			lowerCamelCase_       )
				assert "train" in ds
				assert isinstance(ds["train"]    ,			lowerCamelCase_       )
				assert next(iter(ds["train"]       )       )











from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean


def 				snake_case__							(							UpperCAmelCase							:  int       ):

    # A local function to see if a dot lands in the circle.
    def is_in_circle(UpperCAmelCase							:  float    ,			UpperCAmelCase							:  float       ) -> bool:
        lowerCAmelCase__   :Optional[int]      							=				sqrt((x**2) + (y**2)       )
        # Our circle has a radius of 1, so a distance
        # greater than 1 would land outside the circle.
        return distance_from_centre <= 1

    # The proportion of guesses that landed in the circle
    lowerCAmelCase__   :Union[str, Any]      							=				mean(
        int(is_in_circle(uniform(-1.0    ,			1.0       )    ,			uniform(-1.0    ,			1.0       )       )       )
        for _ in range(UpperCAmelCase       )       )
    # The ratio of the area for circle to square is pi/4.
    lowerCAmelCase__   :List[Any]      							=				proportion * 4
    print(F'''The estimated value of pi is {pi_estimate}'''       )
    print(F'''The numpy value of pi is {pi}'''       )
    print(F'''The total error is {abs(pi - pi_estimate       )}'''       )


def 				snake_case__							(							UpperCAmelCase							:  int    ,			UpperCAmelCase							:  Callable[[float], float]    ,			UpperCAmelCase							:  float = 0.0    ,			UpperCAmelCase							:  float = 1.0    ,			):
    return mean(
        function_to_integrate(uniform(UpperCAmelCase    ,			UpperCAmelCase       )       ) for _ in range(UpperCAmelCase       )       ) * (max_value - min_value)


def 				snake_case__							(							UpperCAmelCase							:  int    ,			UpperCAmelCase							:  float = 0.0    ,			UpperCAmelCase							:  float = 1.0       ):

    def identity_function(UpperCAmelCase							:  float       ) -> float:
        return x

    lowerCAmelCase__   :List[str]      							=				area_under_curve_estimator(
        UpperCAmelCase    ,			UpperCAmelCase    ,			UpperCAmelCase    ,			UpperCAmelCase       )
    lowerCAmelCase__   :Tuple      							=				(max_value * max_value - min_value * min_value) / 2

    print("******************"       )
    print(F'''Estimating area under y=x where x varies from {min_value} to {max_value}'''       )
    print(F'''Estimated value is {estimated_value}'''       )
    print(F'''Expected value is {expected_value}'''       )
    print(F'''Total error is {abs(estimated_value - expected_value       )}'''       )
    print("******************"       )


def 				snake_case__							(							UpperCAmelCase							:  int       ):

    def function_to_integrate(UpperCAmelCase							:  float       ) -> float:
        return sqrt(4.0 - x * x       )

    lowerCAmelCase__   :int      							=				area_under_curve_estimator(
        UpperCAmelCase    ,			UpperCAmelCase    ,			0.0    ,			2.0       )

    print("******************"       )
    print("Estimating pi using area_under_curve_estimator"       )
    print(F'''Estimated value is {estimated_value}'''       )
    print(F'''Expected value is {pi}'''       )
    print(F'''Total error is {abs(estimated_value - pi       )}'''       )
    print("******************"       )


if __name__ == "__main__":
 import doctest

 doctest.testmod()



