


import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


snake_case							: List[str]      =   5_00_00
snake_case							: Optional[int]      =   50_00

snake_case    ,  snake_case							: Union[str, Any]      =   os.path.split(__file__)
snake_case							: int      =   os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))






@get_duration
def 							__lowercase     (				__lowerCAmelCase							:       str      ,					__lowerCAmelCase							:       Dict     ):

							for i in range(a__     ):
														a__    =  dataset[i]






@get_duration
def 							__lowercase     (				__lowerCAmelCase							:       Dict      ,					__lowerCAmelCase							:       Union[str, Any]      ,					__lowerCAmelCase							:       str     ):

							for i in range(0      ,					len(a__     )      ,					a__     ):
														a__    =  dataset[i : i + batch_size]






@get_duration
def 							__lowercase     (				__lowerCAmelCase							:       str      ,					__lowerCAmelCase							:       str      ,					__lowerCAmelCase							:       List[Any]     ):

							with dataset.formatted_as(type=a__     ):
														for i in range(a__     ):
																					a__    =  dataset[i]






@get_duration
def 							__lowercase     (				__lowerCAmelCase							:       List[str]      ,					__lowerCAmelCase							:       Optional[int]      ,					__lowerCAmelCase							:       Tuple      ,					__lowerCAmelCase							:       str     ):

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






def 							__lowercase     (				):
							a__    =  {'num examples': SPEED_TEST_N_EXAMPLES}
							a__    =  [
							    (read, {'length': SMALL_TEST}),
							    (read, {'length': SPEED_TEST_N_EXAMPLES}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0_0}),
							    (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': 1_0}),
							    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_0_0_0}),
							]

							a__    =  [
							    (read, {'length': SMALL_TEST}),
							    (read, {'length': SPEED_TEST_N_EXAMPLES}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0}),
							    (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_0_0_0}),
							    (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
							    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_0}),
							    (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_0_0_0}),
							]
							with tempfile.TemporaryDirectory() as tmp_dir:
														print('generating dataset'     )
														a__    =  datasets.Features(
														    {'list': datasets.Sequence(datasets.Value('float32'     )     ), 'numbers': datasets.Value('float32'     )}     )
														a__    =  generate_example_dataset(
														    os.path.join(a__      ,					'dataset.arrow'     )      ,					a__      ,					num_examples=a__      ,					seq_shapes={'list': (1_0_0,)}      ,					)
														print('first set of iterations'     )
														for func, kwargs in functions:
																					print(func.__name__      ,					str(a__     )     )
																					a__    =  func(a__      ,					**a__     )

														print('shuffling dataset'     )
														a__    =  dataset.shuffle()
														print('Second set of iterations (after shuffling'     )
														for func, kwargs in functions_shuffled:
																					print('shuffled '      ,					func.__name__      ,					str(a__     )     )
																					a__    =  func(
																					    a__      ,					**a__     )

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


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








import unittest

from knapsack import greedy_knapsack as kp







class  snake_case_     (unittest.TestCase   ):
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					Union[str, Any]:
												a__    =  [10, 20, 30, 40, 50, 60]
												a__    =  [2, 4, 6, 8, 10, 12]
												a__    =  1_00
												self.assertEqual(kp.calc_profit(__snake_case    ,__snake_case    ,__snake_case   )    ,2_10   )
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[int]:
												self.assertRaisesRegex(__snake_case    ,'max_weight must greater than zero.'   )
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					int:
												self.assertRaisesRegex(__snake_case    ,'Weight can not be negative.'   )
					def 				lowerCamelCase__(   self     :str   )      ->					List[str]:
												self.assertRaisesRegex(__snake_case    ,'Profit can not be negative.'   )
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[Any]:
												self.assertRaisesRegex(__snake_case    ,'max_weight must greater than zero.'   )



					def 				lowerCamelCase__(   self     :int   )      ->					List[Any]:
												self.assertRaisesRegex(
												    __snake_case    ,'The length of profit and weight must be same.'   )


if __name__ == "__main__":
						unittest.main()




