
"""simple docstring"""

import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


SCREAMING_SNAKE_CASE_         =  1000_0000_0000
SCREAMING_SNAKE_CASE_         =  1_0000

SCREAMING_SNAKE_CASE_   ,  SCREAMING_SNAKE_CASE_         =  os.path.split(__file__)
SCREAMING_SNAKE_CASE_         =  os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))




def       lowercase__  (   lowerCAmelCase			:   int	,			lowerCAmelCase			:   int	)	-> datasets.Dataset:






    """simple docstring"""




    UpperCAmelCase       =   pa.Table.from_pydict({'col': [0] * chunk_size}	)
    UpperCAmelCase       =   pa.concat_tables([table] * (num_examples // chunk_size)	)
    return datasets.Dataset(lowerCAmelCase	,			fingerprint='table_100B'	)
@dataclass
class        _UpperCAmelCase							:
      __SCREAMING_SNAKE_CASE				:							int
      __SCREAMING_SNAKE_CASE				:							int
      __SCREAMING_SNAKE_CASE				:							int
      __SCREAMING_SNAKE_CASE				:							int




      def       a_ (							self							)  ->   List[str]:
          UpperCAmelCase       =   np.random.default_rng(self.seed							)
          UpperCAmelCase       =   rng.integers(low=self.low				,    high=self.high				,    size=self.size							).tolist()




      def __iter__(							self							)  ->   List[str]:
          return iter(self._sampled_values							)




      def __len__(							self							)  ->   Optional[Any]:
          return self.size




@get_duration
def       lowercase__  (   lowerCAmelCase			:   datasets.Dataset	)	-> Any:






    """simple docstring"""




    UpperCAmelCase       =   dataset[0]




@get_duration
def       lowercase__  (   lowerCAmelCase			:   datasets.Dataset	)	-> int:






    """simple docstring"""




    UpperCAmelCase       =   dataset[-1]




@get_duration
def       lowercase__  (   lowerCAmelCase			:   datasets.Dataset	)	-> Dict:






    """simple docstring"""




    UpperCAmelCase       =   dataset[range(len(lowerCAmelCase	) // 2	,			len(lowerCAmelCase	) // 2 + 1_024	)]




@get_duration
def       lowercase__  (   lowerCAmelCase			:   datasets.Dataset	)	-> int:






    """simple docstring"""




    UpperCAmelCase       =   dataset[RandIter(0	,			len(lowerCAmelCase	)	,			1_024	,			seed=42	)]




def       lowercase__  (   )	-> Optional[int]:






    """simple docstring"""




    UpperCAmelCase       =   {'num examples': SPEED_TEST_N_EXAMPLES}
    UpperCAmelCase       =   (get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
    print('generating dataset'	)
    UpperCAmelCase       =   generate_100B_dataset(num_examples=lowerCAmelCase	,			chunk_size=lowerCAmelCase	)
    print('Functions'	)
    for func in functions:
        print(func.__name__	)
        UpperCAmelCase       =   func(lowerCAmelCase	)

    with open(lowerCAmelCase	,			'wb'	) as f:
        f.write(json.dumps(lowerCAmelCase	).encode('utf-8'	)	)


if __name__ == "__main__":  # useful to run the profiler
   benchmark_table_100B()





"""simple docstring"""

SCREAMING_SNAKE_CASE_         =  {
    0: '''underwear''',
    1: '''pants''',
    2: '''belt''',
    3: '''suit''',
    4: '''shoe''',
    5: '''socks''',
    6: '''shirt''',
    7: '''tie''',
    8: '''watch''',
}

SCREAMING_SNAKE_CASE_         =  [[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

SCREAMING_SNAKE_CASE_         =  [0 for x in range(len(graph))]
SCREAMING_SNAKE_CASE_         =  []




def       lowercase__  (   lowerCAmelCase			:   Optional[int]	,			lowerCAmelCase			:   Any	)	-> List[str]:






    """simple docstring"""




    UpperCAmelCase       =   1
    while stack:
        UpperCAmelCase       =   stack.pop()
        print(lowerCAmelCase	,			clothes[current_clothing]	)
        order += 1




def       lowercase__  (   lowerCAmelCase			:   List[Any]	,			lowerCAmelCase			:   Any	,			lowerCAmelCase			:   Dict	)	-> Optional[Any]:






    """simple docstring"""




    UpperCAmelCase       =   1
    for v in graph[u]:
        if not visited[v]:
            depth_first_search(lowerCAmelCase	,			lowerCAmelCase	,			lowerCAmelCase	)

    stack.append(lowerCAmelCase	)




def       lowercase__  (   lowerCAmelCase			:   Tuple	,			lowerCAmelCase			:   Dict	)	-> Optional[Any]:






    """simple docstring"""




    for v in range(len(lowerCAmelCase	)	):
        if not visited[v]:
            depth_first_search(lowerCAmelCase	,			lowerCAmelCase	,			lowerCAmelCase	)


if __name__ == "__main__":
   topological_sort(graph, visited)
   print(stack)
   print_stack(stack, clothes)



