




import math







def 				lowerCAmelCase_	(     snake_case_,snake_case_ = 0,snake_case_ = 0     ):
      _A							:     Tuple			=						end or len(snake_case_     )
      for i in range(snake_case_,snake_case_     ):
            _A							:     List[str]			=						i
            _A							:     Optional[Any]			=						array[i]
            while temp_index != start and temp_index_value < array[temp_index - 1]:
                  _A							:     int			=						array[temp_index - 1]
                  temp_index -= 1
            _A							:     Dict			=						temp_index_value
      return array







def 				lowerCAmelCase_	(     snake_case_,snake_case_,snake_case_     ):  # Max Heap
      _A							:     Dict			=						index
      _A							:     Union[str, Any]			=						2 * index + 1  # Left Node
      _A							:     List[Any]			=						2 * index + 2  # Right Node

      if left_index < heap_size and array[largest] < array[left_index]:
            _A							:     str			=						left_index

      if right_index < heap_size and array[largest] < array[right_index]:
            _A							:     str			=						right_index

      if largest != index:
            _A			,   _A							:     List[Any]			=						array[largest], array[index]
            heapify(snake_case_,snake_case_,snake_case_     )







def 				lowerCAmelCase_	(     snake_case_     ):
      _A							:     Any			=						len(snake_case_     )

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

      for i in range(n - 1,0,-1     ):
            _A			,   _A							:     Union[str, Any]			=						array[0], array[i]
            heapify(snake_case_,0,snake_case_     )

      return array







def 				lowerCAmelCase_	(     snake_case_,snake_case_,snake_case_,snake_case_     ):
      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 				lowerCAmelCase_	(     snake_case_,snake_case_,snake_case_,snake_case_     ):
      _A							:     int			=						low
      _A							:     List[Any]			=						high
      while True:
            while array[i] < pivot:
                  i += 1
            j -= 1
            while pivot < array[j]:
                  j -= 1
            if i >= j:
                  return i
            _A			,   _A							:     str			=						array[j], array[i]
            i += 1







def 				lowerCAmelCase_	(     snake_case_     ):
      if len(snake_case_     ) == 0:
            return array
      _A							:     Tuple			=						2 * math.ceil(math.loga(len(snake_case_     )     )     )
      _A							:     List[str]			=						16
      return intro_sort(snake_case_,0,len(snake_case_     ),snake_case_,snake_case_     )







def 				lowerCAmelCase_	(     snake_case_,snake_case_,snake_case_,snake_case_,snake_case_     ):
      while end - start > size_threshold:
            if max_depth == 0:
                  return heap_sort(snake_case_     )
            max_depth -= 1
            _A							:     Optional[Any]			=						median_of_a(snake_case_,snake_case_,start + ((end - start) // 2) + 1,end - 1     )
            _A							:     List[Any]			=						partition(snake_case_,snake_case_,snake_case_,snake_case_     )
            intro_sort(snake_case_,snake_case_,snake_case_,snake_case_,snake_case_     )
            _A							:     Optional[Any]			=						p
      return insertion_sort(snake_case_,snake_case_,snake_case_     )


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))







from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
  import numpy as np
  import tensorflow as tf

  from transformers import TFCamembertModel







@require_tf
@require_sentencepiece
@require_tokenizers
class 						lowercase							(   unittest.TestCase		):

     @slow
     def 					a__	(  self				)						->							Any:
           _A							:     Tuple			=						TFCamembertModel.from_pretrained("""jplu/tf-camembert-base"""				)

           _A							:     List[Any]			=						tf.convert_to_tensor(
               [[5, 121, 11, 660, 16, 730, 2_5543, 110, 83, 6]]		,     dtype=tf.intaa		,     )  # J'aime le camembert !"

           _A							:     List[str]			=						model(_a				)["""last_hidden_state"""]
           _A							:     Union[str, Any]			=						tf.TensorShape((1, 10, 768)				)
           self.assertEqual(output.shape		,     _a				)
           # compare the actual values for a slice.
           _A							:     List[Any]			=						tf.convert_to_tensor(
               [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]		,     dtype=tf.floataa		,     )
           # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
           # camembert.eval()
           # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

           self.assertTrue(np.allclose(output[:, :3, :3].numpy()		,     expected_slice.numpy()		,     atol=1e-4				)				)

