



'''simple docstring'''





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


lowercase_		       =  50_000
lowercase_		       =  5_000

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




@get_duration
def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



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




@get_duration
def lowerCAmelCase  (__A  ,	__A  ,	__A):



     """simple docstring"""



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




@get_duration
def lowerCAmelCase  (__A  ,	__A  ,	__A):



     """simple docstring"""



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




@get_duration
def lowerCAmelCase  (__A  ,	__A  ,	__A  ,	__A):



     """simple docstring"""



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




def lowerCAmelCase  ():



     """simple docstring"""



     _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''': 10}),
         (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 100}),
         (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_000}),
         (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''': 1_000}),
     ]

     _a      =  [
         (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''': 1_000}),
         (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''': 1_000}),
     ]
     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''': (100,)}  ,	)
          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()








'''simple docstring'''





from __future__ import annotations

import math




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     _a      =  u
     for i in range(1  ,	__A):
          _a      =  temp * (u - i)
     return temp




def lowerCAmelCase  ():



     """simple docstring"""



     _a      =  int(input('''enter the numbers of values: '''))
     _a      =  []
     for _ in range(__A):
          y.append([])
     for i in range(__A):
          for j in range(__A):
               y[i].append(__A)
               _a      =  0

     print('''enter the values of parameters in a list: ''')
     _a      =  list(map(__A  ,	input().split()))

     print('''enter the values of corresponding parameters: ''')
     for i in range(__A):
          _a      =  float(input())

     _a      =  int(input('''enter the value to interpolate: '''))
     _a      =  (value - x[0]) / (x[1] - x[0])

     # for calculating forward difference table

     for i in range(1  ,	__A):
          for j in range(n - i):
               _a      =  y[j + 1][i - 1] - y[j][i - 1]

     _a      =  y[0][0]
     for i in range(1  ,	__A):
          summ += (ucal(__A  ,	__A) * y[0][i]) / math.factorial(__A)

     print(F'''the value at {value} is {summ}''')


if __name__ == "__main__":
  main()



