
'''simple docstring'''


import os
import sys
import unittest


snake_case_ :  List[Any]     =					os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
snake_case_ :  List[Any]     =					os.path.join(git_repo_path, 'src', 'transformers')

snake_case_ :  Any     =					'\n{0} = None\n'

snake_case_ :  Any     =					'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n'


snake_case_ :  List[str]     =					'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'


class 						lowercase__	(  unittest.TestCase   ):






   '''simple docstring'''







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  find_backend('''    _import_structure["models.albert"].append("AlbertTokenizerFast")'''   )
      self.assertIsNone(lowerCamelCase__   )

      UpperCamelCase       =  find_backend('''    if not is_tokenizers_available():'''   )
      self.assertEqual(lowerCamelCase__ ,   '''tokenizers'''   )

      UpperCamelCase       =  find_backend('''    if not is_tensorflow_text_available():'''   )
      self.assertEqual(lowerCamelCase__ ,   '''tensorflow_text'''   )

      UpperCamelCase       =  find_backend('''    if not (is_sentencepiece_available() and is_tokenizers_available()):'''   )
      self.assertEqual(lowerCamelCase__ ,   '''sentencepiece_and_tokenizers'''   )

      UpperCamelCase       =  find_backend(
          '''    if not (is_sentencepiece_available() and is_tensorflow_text_available()):'''   )
      self.assertEqual(lowerCamelCase__ ,   '''sentencepiece_and_tensorflow_text'''   )

      UpperCamelCase       =  find_backend(
          '''    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):'''   )
      self.assertEqual(lowerCamelCase__ ,   '''sentencepiece_and_tokenizers_and_vision'''   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  read_init()
      # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
      self.assertIn('''torch''' ,   lowerCamelCase__   )
      self.assertIn('''tensorflow_text''' ,   lowerCamelCase__   )
      self.assertIn('''sentencepiece_and_tokenizers''' ,   lowerCamelCase__   )

      # Likewise, we can't assert on the exact content of a key
      self.assertIn('''BertModel''' ,   objects['''torch''']   )
      self.assertIn('''TFBertModel''' ,   objects['''tf''']   )
      self.assertIn('''FlaxBertModel''' ,   objects['''flax''']   )
      self.assertIn('''BertModel''' ,   objects['''torch''']   )
      self.assertIn('''TFBertTokenizer''' ,   objects['''tensorflow_text''']   )
      self.assertIn('''convert_slow_tokenizer''' ,   objects['''sentencepiece_and_tokenizers''']   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  create_dummy_object('''CONSTANT''' ,   '''\'torch\''''   )
      self.assertEqual(lowerCamelCase__ ,   '''\nCONSTANT = None\n'''   )

      UpperCamelCase       =  create_dummy_object('''function''' ,   '''\'torch\''''   )
      self.assertEqual(
          lowerCamelCase__ ,   '''\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'''   )

      UpperCamelCase       =  '''
class FakeClass(metaclass=DummyObject):
    _backends = \'torch\'

    def __init__(self, *args, **kwargs):
        requires_backends(self, \'torch\')
'''
      UpperCamelCase       =  create_dummy_object('''FakeClass''' ,   '''\'torch\''''   )
      self.assertEqual(lowerCamelCase__ ,   lowerCamelCase__   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  '''# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, ["torch"])


class FakeClass(metaclass=DummyObject):
    _backends = ["torch"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch"])
'''
      UpperCamelCase       =  create_dummy_files({'''torch''': ['''CONSTANT''', '''function''', '''FakeClass''']}   )
      self.assertEqual(dummy_files['''torch'''] ,   lowerCamelCase__   )







'''simple docstring'''


from random import randint
from tempfile import TemporaryFile

import numpy as np



def  __snake_case     (    _UpperCAmelCase					:       Optional[int],      _UpperCAmelCase					:       Tuple,      _UpperCAmelCase					:       Any):
   UpperCamelCase       =  0
   if start < end:
      UpperCamelCase       =  randint(_UpperCAmelCase,      _UpperCAmelCase)
      UpperCamelCase       =  a[end]
      UpperCamelCase       =  a[pivot]
      UpperCamelCase       =  temp

      UpperCamelCase     , UpperCamelCase       =  _in_place_partition(_UpperCAmelCase,      _UpperCAmelCase,      _UpperCAmelCase)
      count += _in_place_quick_sort(_UpperCAmelCase,      _UpperCAmelCase,      p - 1)
      count += _in_place_quick_sort(_UpperCAmelCase,      p + 1,      _UpperCAmelCase)
   return count



def  __snake_case     (    _UpperCAmelCase					:       Dict,      _UpperCAmelCase					:       Tuple,      _UpperCAmelCase					:       Any):
   UpperCamelCase       =  0
   UpperCamelCase       =  randint(_UpperCAmelCase,      _UpperCAmelCase)
   UpperCamelCase       =  a[end]
   UpperCamelCase       =  a[pivot]
   UpperCamelCase       =  temp
   UpperCamelCase       =  start - 1
   for index in range(_UpperCAmelCase,      _UpperCAmelCase):
      count += 1
      if a[index] < a[end]:  # check if current val is less than pivot value
         UpperCamelCase       =  new_pivot_index + 1
         UpperCamelCase       =  a[new_pivot_index]
         UpperCamelCase       =  a[index]
         UpperCamelCase       =  temp

   UpperCamelCase       =  a[new_pivot_index + 1]
   UpperCamelCase       =  a[end]
   UpperCamelCase       =  temp
   return new_pivot_index + 1, count


snake_case_ :  List[Any]     =					TemporaryFile()
snake_case_ :  Optional[Any]     =					100  # 1000 elements are to be sorted


snake_case_  , snake_case_ :  List[str]     =					0, 1  # mean and standard deviation
snake_case_ :  Any     =					np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('The array is')
print(X)


outfile.seek(0)  # using the same array
snake_case_ :  Optional[int]     =					np.load(outfile)
snake_case_ :  Optional[int]     =					len(M) - 1
snake_case_ :  List[str]     =					_in_place_quick_sort(M, 0, r)

print(
    'No of Comparisons for 100 elements selected from a standard normal distribution'
    'is :'
)

print(z)





