'''simple docstring'''


def  _lowerCamelCase   (				lowerCamelCase_ :							int       ):



     """simple docstring"""





     UpperCAmelCase_							:       str       =				len(lowerCamelCase_       )
     while cur > 1:
          # Find the maximum number in arr
          UpperCAmelCase_							:       Optional[Any]       =				arr.index(max(arr[0:cur]       )       )
          # Reverse from 0 to mi
          UpperCAmelCase_							:       Optional[Any]       =				arr[mi::-1] + arr[mi + 1 : len(lowerCamelCase_       )]
          # Reverse whole list
          UpperCAmelCase_							:       Any       =				arr[cur - 1 :: -1] + arr[cur : len(lowerCamelCase_       )]
          cur -= 1
     return arr


if __name__ == "__main__":
 snake_case__					:      List[Any]				      =  input('''Enter numbers separated by a comma:\n''').strip()
 snake_case__					:      List[Any]				      =  [int(item) for item in user_input.split(''',''')]
 print(pancake_sort(unsorted))







'''simple docstring'''


import os
import time

import numpy as np
import onnxruntime as ort


snake_case__					:      Optional[int]				      =  '''1'''
snake_case__					:      str				      =  '''0'''
snake_case__					:      List[str]				      =  '''1'''

snake_case__					:      List[str]				      =  ort.SessionOptions()
snake_case__					:      str				      =  ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print('''Create inference session...''')
snake_case__					:      Dict				      =  ['''TensorrtExecutionProvider''', '''CUDAExecutionProvider''']
snake_case__					:      Dict				      =  ort.InferenceSession('''model.onnx''', sess_options=sess_opt, providers=execution_provider)
snake_case__					:      str				      =  ort.RunOptions()

snake_case__					:      List[Any]				      =  128
snake_case__					:      Union[str, Any]				      =  1
snake_case__					:      Tuple				      =  np.ones((batch, sequence), dtype=np.intaa)
snake_case__					:      Tuple				      =  np.ones((batch, sequence), dtype=np.intaa)
snake_case__					:      Union[str, Any]				      =  np.ones((batch, sequence), dtype=np.intaa)

print('''Warm up phase...''')
sess.run(
    None,
    {
        sess.get_inputs()[0].name: input_ids,
        sess.get_inputs()[1].name: attention_mask,
        sess.get_inputs()[2].name: token_type_ids,
    },
    run_options=run_opt,
)

print('''Start inference...''')
snake_case__					:      Union[str, Any]				      =  time.time()
snake_case__					:      str				      =  2000
snake_case__					:      Tuple				      =  {}
for iter in range(max_iters):
 snake_case__					:      str				      =  sess.run(
     None,
     {
         sess.get_inputs()[0].name: input_ids,
         sess.get_inputs()[1].name: attention_mask,
         sess.get_inputs()[2].name: token_type_ids,
     },
     run_options=run_opt,
 )
print('''Average Inference Time = {:.3f} ms'''.format((time.time() - start_time) * 1000 / max_iters))






