
'''simple docstring'''



from __future__ import annotations

from random import random





class 	A							:



			def __init__(    self				,   lowerCamelCase__ = None				)	->						str:




									'''simple docstring'''



									lowercase__							       =				value
									lowercase__							       =				random()
									lowercase__							       =				None
									lowercase__							       =				None



			def __repr__(    self				)	->						Dict:




									'''simple docstring'''



									from pprint import pformat

									if self.left is None and self.right is None:
															return F'''\'{self.value}: {self.prior:.5}\''''
									else:
															return pformat(
															    {F'''{self.value}: {self.prior:.5}''': (self.left, self.right)}				,   indent=1				)



			def __str__(    self				)	->						Dict:




									'''simple docstring'''



									lowercase__							       =				str(self.value				) + ''' '''
									lowercase__							       =				str(self.left or """"""				)
									lowercase__							       =				str(self.right or """"""				)
									return value + left + right





def        _A						(							lowercase__						,						lowercase__		):







						if root is None:  # None tree is split into 2 Nones
												return None, None
						elif root.value is None:
												return None, None
						else:
												if value < root.value:
																		lowercase__							       =				split(root.left						,						snake_case_		)
																		return left, root
												else:
																		lowercase__							       =				split(root.right						,						snake_case_		)
																		return root, right





def        _A						(							lowercase__						,						lowercase__		):







						if (not left) or (not right):  # If one node is None, return the other
												return left or right
						elif left.prior < right.prior:
												lowercase__							       =				merge(left.right						,						snake_case_		)
												return left
						else:
												lowercase__							       =				merge(snake_case_						,						right.left		)
												return right





def        _A						(							lowercase__						,						lowercase__		):
						lowercase__							       =				Node(snake_case_		)
						lowercase__							       =				split(snake_case_						,						snake_case_		)
						return merge(merge(snake_case_						,						snake_case_		)						,						snake_case_		)





def        _A						(							lowercase__						,						lowercase__		):
						lowercase__							       =				split(snake_case_						,						value - 1		)
						lowercase__							       =				split(snake_case_						,						snake_case_		)
						return merge(snake_case_						,						snake_case_		)





def        _A						(							lowercase__		):







						if not root:  # None
												return
						else:
												inorder(root.left		)
												print(root.value						,						end=""","""		)
												inorder(root.right		)





def        _A						(							lowercase__						,						lowercase__		):







						for arg in args.split():
												if arg[0] == "+":
																		lowercase__							       =				insert(snake_case_						,						int(arg[1:]		)		)

												elif arg[0] == "-":
																		lowercase__							       =				erase(snake_case_						,						int(arg[1:]		)		)

												else:
																		print("""Unknown command"""		)

						return root





def        _A						(							):
						lowercase__							       =				None
						print(
						    """enter numbers to create a tree, + value to add value into treap, """
						    """- value to erase all nodes with value. \'q\' to quit. """		)

						lowercase__							       =				input()
						while args != "q":
												lowercase__							       =				interact_treap(snake_case_						,						snake_case_		)
												print(snake_case_		)
												lowercase__							       =				input()

						print("""good by!"""		)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()













"""simple docstring"""



import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


a_ =			50000
a_ =			5000

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







@get_duration
def 		__lowercase     (   snake_case_  :  datasets.Dataset				,snake_case_  :  Tuple						)   ->Tuple:



    '''simple docstring'''







    for i in range(snake_case_						):
        __A    :						int						 =     dataset[i]







@get_duration
def 		__lowercase     (   snake_case_  :  datasets.Dataset				,snake_case_  :  Optional[Any]				,snake_case_  :  int						)   ->Tuple:



    '''simple docstring'''







    for i in range(0				,len(snake_case_						)				,snake_case_						):
        __A    :						List[str]						 =     dataset[i : i + batch_size]







@get_duration
def 		__lowercase     (   snake_case_  :  datasets.Dataset				,snake_case_  :  List[Any]				,snake_case_  :  Any						)   ->int:



    '''simple docstring'''







    with dataset.formatted_as(type=snake_case_						):
        for i in range(snake_case_						):
            __A    :						Union[str, Any]						 =     dataset[i]







@get_duration
def 		__lowercase     (   snake_case_  :  datasets.Dataset				,snake_case_  :  Any				,snake_case_  :  Union[str, Any]				,snake_case_  :  Optional[int]						)   ->Union[str, Any]:



    '''simple docstring'''







    with dataset.formatted_as(type=snake_case_						):
        for i in range(0				,snake_case_				,snake_case_						):
            __A    :						Dict						 =     dataset[i : i + batch_size]







def 		__lowercase     (   )   ->Optional[int]:



    '''simple docstring'''







    __A    :						int						 =     {'''num examples''': SPEED_TEST_N_EXAMPLES}
    __A    :						Optional[int]						 =     [
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 100}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1000}),
        (read_formatted, {'''type''': '''numpy''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''pandas''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''torch''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''tensorflow''', '''length''': SMALL_TEST}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 10}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1000}),
    ]

    __A    :						int						 =     [
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 10}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 100}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1000}),
        (read_formatted, {'''type''': '''numpy''', '''length''': SMALL_TEST}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 10}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1000}),
    ]
    with tempfile.TemporaryDirectory() as tmp_dir:
        print('''generating dataset'''						)
        __A    :						Any						 =     datasets.Features(
            {'''list''': datasets.Sequence(datasets.Value('''float32'''						)						), '''numbers''': datasets.Value('''float32'''						)}						)
        __A    :						List[Any]						 =     generate_example_dataset(
            os.path.join(snake_case_				,'''dataset.arrow'''						)				,snake_case_				,num_examples=snake_case_				,seq_shapes={'''list''': (100,)}				,)
        print('''first set of iterations'''						)
        for func, kwargs in functions:
            print(func.__name__				,str(snake_case_						)						)
            __A    :						Dict						 =     func(snake_case_				,**snake_case_						)

        print('''shuffling dataset'''						)
        __A    :						int						 =     dataset.shuffle()
        print('''Second set of iterations (after shuffling'''						)
        for func, kwargs in functions_shuffled:
            print('''shuffled '''				,func.__name__				,str(snake_case_						)						)
            __A    :						Optional[Any]						 =     func(
                snake_case_				,**snake_case_						)

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


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




