





import math


def _A       (   __magic_name__  , __magic_name__ = 0  , __magic_name__ = 0	):
   lowercase__			       =  end or len(__magic_name__	)
   for i in range(__magic_name__  , __magic_name__	):
      lowercase__			       =  i
      lowercase__			       =  array[i]
      while temp_index != start and temp_index_value < array[temp_index - 1]:
         lowercase__			       =  array[temp_index - 1]
         temp_index -= 1
      lowercase__			       =  temp_index_value
   return array


def _A       (   __magic_name__  , __magic_name__  , __magic_name__	):  # Max Heap
   lowercase__			       =  index
   lowercase__			       =  2 * index + 1  # Left Node
   lowercase__			       =  2 * index + 2  # Right Node

   if left_index < heap_size and array[largest] < array[left_index]:
      lowercase__			       =  left_index

   if right_index < heap_size and array[largest] < array[right_index]:
      lowercase__			       =  right_index

   if largest != index:
      lowercase__       ,							lowercase__			       =  array[largest], array[index]
      heapify(__magic_name__  , __magic_name__  , __magic_name__	)


def _A       (   __magic_name__	):
   lowercase__			       =  len(__magic_name__	)

   for i in range(n // 2  , -1  , -1	):
      heapify(__magic_name__  , __magic_name__  , __magic_name__	)

   for i in range(n - 1  , 0  , -1	):
      lowercase__       ,							lowercase__			       =  array[0], array[i]
      heapify(__magic_name__  , 0  , __magic_name__	)

   return array


def _A       (   __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__	):
   if (array[first_index] > array[middle_index]) != (
       array[first_index] > array[last_index]
   ):
      return array[first_index]
   elif (array[middle_index] > array[first_index]) != (
       array[middle_index] > array[last_index]
   ):
      return array[middle_index]
   else:
      return array[last_index]


def _A       (   __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__	):
   lowercase__			       =  low
   lowercase__			       =  high
   while True:
      while array[i] < pivot:
         i += 1
      j -= 1
      while pivot < array[j]:
         j -= 1
      if i >= j:
         return i
      lowercase__       ,							lowercase__			       =  array[j], array[i]
      i += 1


def _A       (   __magic_name__	):
   if len(__magic_name__	) == 0:
      return array
   lowercase__			       =  2 * math.ceil(math.loga(len(__magic_name__	)	)	)
   lowercase__			       =  16
   return intro_sort(__magic_name__  , 0  , len(__magic_name__	)  , __magic_name__  , __magic_name__	)


def _A       (   __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__	):
   while end - start > size_threshold:
      if max_depth == 0:
         return heap_sort(__magic_name__	)
      max_depth -= 1
      lowercase__			       =  median_of_a(__magic_name__  , __magic_name__  , start + ((end - start) // 2) + 1  , end - 1	)
      lowercase__			       =  partition(__magic_name__  , __magic_name__  , __magic_name__  , __magic_name__	)
      intro_sort(__magic_name__  , __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__	)
      lowercase__			       =  p
   return insertion_sort(__magic_name__  , __magic_name__  , __magic_name__	)


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  _snake_case           =			input("""Enter numbers separated by a comma : """).strip()
  _snake_case           =			[float(item) for item in user_input.split(""",""")]
  print(sort(unsorted))













import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
  from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
  import torch_xla.core.xla_model as xm


def _A       (   __magic_name__	):
   if is_torch_version("<"  , "2.0.0"	) or not hasattr(__magic_name__  , "_dynamo"	):
      return False
   return isinstance(__magic_name__  , torch._dynamo.eval_frame.OptimizedModule	)


def _A       (   __magic_name__  , __magic_name__ = True	):
   lowercase__			       =  (torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

   lowercase__			       =  is_compiled_module(__magic_name__	)
   if is_compiled:
      lowercase__			       =  model
      lowercase__			       =  model._orig_mod

   if is_deepspeed_available():
      options += (DeepSpeedEngine,)

   while isinstance(__magic_name__  , __magic_name__	):
      lowercase__			       =  model.module

   if not keep_fpaa_wrapper:
      lowercase__			       =  getattr(__magic_name__  , "forward"	)
      lowercase__			       =  model.__dict__.pop("_original_forward"  , __magic_name__	)
      if original_forward is not None:
         while hasattr(__magic_name__  , "__wrapped__"	):
            lowercase__			       =  forward.__wrapped__
            if forward == original_forward:
               break
         lowercase__			       =  forward
      if getattr(__magic_name__  , "_converted_to_transformer_engine"  , __magic_name__	):
         convert_model(__magic_name__  , to_transformer_engine=__magic_name__	)

   if is_compiled:
      lowercase__			       =  model
      lowercase__			       =  compiled_model

   return model


def _A       (   ):
   PartialState().wait_for_everyone()


def _A       (   __magic_name__  , __magic_name__	):
   if PartialState().distributed_type == DistributedType.TPU:
      xm.save(__magic_name__  , __magic_name__	)
   elif PartialState().local_process_index == 0:
      torch.save(__magic_name__  , __magic_name__	)


@contextmanager
def _A       (   **__magic_name__	):
   for key, value in kwargs.items():
      lowercase__			       =  str(__magic_name__	)

   yield

   for key in kwargs:
      if key.upper() in os.environ:
         del os.environ[key.upper()]


def _A       (   __magic_name__	):
   if not hasattr(__magic_name__  , "__qualname__"	) and not hasattr(__magic_name__  , "__name__"	):
      lowercase__			       =  getattr(__magic_name__  , "__class__"  , __magic_name__	)
   if hasattr(__magic_name__  , "__qualname__"	):
      return obj.__qualname__
   if hasattr(__magic_name__  , "__name__"	):
      return obj.__name__
   return str(__magic_name__	)


def _A       (   __magic_name__  , __magic_name__	):
   for key, value in source.items():
      if isinstance(__magic_name__  , __magic_name__	):
         lowercase__			       =  destination.setdefault(__magic_name__  , {}	)
         merge_dicts(__magic_name__  , __magic_name__	)
      else:
         lowercase__			       =  value

   return destination







def _A       (   __magic_name__ = None	):
   if port is None:
      lowercase__			       =  2_9500
   with socket.socket(socket.AF_INET  , socket.SOCK_STREAM	) as s:
      return s.connect_ex(("localhost", port)	) == 0






