
'''simple docstring'''


import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
   from test_module.custom_tokenization_fast import CustomTokenizerFast


class 						lowercase__	(  unittest.TestCase   ):






   '''simple docstring'''







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  0







   @slow
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
         self.assertIsNotNone(lowerCamelCase__   )
         self.assertIsInstance(lowerCamelCase__ ,   (BertTokenizer, BertTokenizerFast)   )
         self.assertGreater(len(lowerCamelCase__   ) ,   0   )

      for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
         self.assertIsNotNone(lowerCamelCase__   )
         self.assertIsInstance(lowerCamelCase__ ,   (GPTaTokenizer, GPTaTokenizerFast)   )
         self.assertGreater(len(lowerCamelCase__   ) ,   0   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
      self.assertIsInstance(lowerCamelCase__ ,   (BertTokenizer, BertTokenizerFast)   )
      self.assertEqual(tokenizer.vocab_size ,   1_2   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
      self.assertIsInstance(lowerCamelCase__ ,   (RobertaTokenizer, RobertaTokenizerFast)   )
      self.assertEqual(tokenizer.vocab_size ,   2_0   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoConfig.from_pretrained(lowerCamelCase__   )
      self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )
      # Check that tokenizer_type ≠ model_type
      UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   config=lowerCamelCase__   )
      self.assertIsInstance(lowerCamelCase__ ,   (BertTokenizer, BertTokenizerFast)   )
      self.assertEqual(tokenizer.vocab_size ,   1_2   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      with tempfile.TemporaryDirectory() as tmp_dir:
         shutil.copy('''./tests/fixtures/vocab.txt''' ,   os.path.join(lowerCamelCase__ ,   '''vocab.txt'''   )   )

         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   tokenizer_type='''bert''' ,   use_fast=lowerCamelCase__   )
         self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )

      with tempfile.TemporaryDirectory() as tmp_dir:
         shutil.copy('''./tests/fixtures/vocab.json''' ,   os.path.join(lowerCamelCase__ ,   '''vocab.json'''   )   )
         shutil.copy('''./tests/fixtures/merges.txt''' ,   os.path.join(lowerCamelCase__ ,   '''merges.txt'''   )   )

         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   tokenizer_type='''gpt2''' ,   use_fast=lowerCamelCase__   )
         self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      with tempfile.TemporaryDirectory() as tmp_dir:
         shutil.copy('''./tests/fixtures/vocab.txt''' ,   os.path.join(lowerCamelCase__ ,   '''vocab.txt'''   )   )

         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   tokenizer_type='''bert'''   )
         self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )

      with tempfile.TemporaryDirectory() as tmp_dir:
         shutil.copy('''./tests/fixtures/vocab.json''' ,   os.path.join(lowerCamelCase__ ,   '''vocab.json'''   )   )
         shutil.copy('''./tests/fixtures/merges.txt''' ,   os.path.join(lowerCamelCase__ ,   '''merges.txt'''   )   )

         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   tokenizer_type='''gpt2'''   )
         self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      with pytest.raises(lowerCamelCase__   ):
         AutoTokenizer.from_pretrained('''./''' ,   tokenizer_type='''xxx'''   )







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
         UpperCamelCase       =  tokenizer_class.from_pretrained('''wietsedv/bert-base-dutch-cased'''   )
         self.assertIsInstance(lowerCamelCase__ ,   (BertTokenizer, BertTokenizerFast)   )

         if isinstance(lowerCamelCase__ ,   lowerCamelCase__   ):
            self.assertEqual(tokenizer.basic_tokenizer.do_lower_case ,   lowerCamelCase__   )
         else:
            self.assertEqual(tokenizer.do_lower_case ,   lowerCamelCase__   )

         self.assertEqual(tokenizer.model_max_length ,   5_1_2   )







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
         with self.assertRaisesRegex(
             lowerCamelCase__ ,   '''julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier''' ,   ):
            UpperCamelCase       =  tokenizer_class.from_pretrained('''julien-c/herlolip-not-exists'''   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  TOKENIZER_MAPPING.values()
      UpperCamelCase       =  []

      for slow_tok, fast_tok in tokenizers:
         if slow_tok is not None:
            tokenizer_names.append(slow_tok.__name__   )

         if fast_tok is not None:
            tokenizer_names.append(fast_tok.__name__   )

      for tokenizer_name in tokenizer_names:
         # must find the right class
         tokenizer_class_from_name(lowerCamelCase__   )







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased''' ,   use_fast=lowerCamelCase__   ) ,   lowerCamelCase__   )
      self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased'''   ) ,   lowerCamelCase__   )







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained('''distilbert-base-uncased''' ,   do_lower_case=lowerCamelCase__   )
      UpperCamelCase       =  '''Hello, world. How are you?'''
      UpperCamelCase       =  tokenizer.tokenize(lowerCamelCase__   )
      self.assertEqual('''[UNK]''' ,   tokens[0]   )

      UpperCamelCase       =  AutoTokenizer.from_pretrained('''microsoft/mpnet-base''' ,   do_lower_case=lowerCamelCase__   )
      UpperCamelCase       =  tokenizer.tokenize(lowerCamelCase__   )
      self.assertEqual('''[UNK]''' ,   tokens[0]   )







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained('''robot-test/dummy-tokenizer-fast-with-model-config'''   )
      self.assertEqual(type(lowerCamelCase__   ) ,   lowerCamelCase__   )
      self.assertEqual(tokenizer.model_max_length ,   5_1_2   )
      self.assertEqual(tokenizer.vocab_size ,   3_0_0_0_0   )
      self.assertEqual(tokenizer.unk_token ,   '''[UNK]'''   )
      self.assertEqual(tokenizer.padding_side ,   '''right'''   )
      self.assertEqual(tokenizer.truncation_side ,   '''right'''   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
      self.assertIsInstance(lowerCamelCase__ ,   (BertTokenizer, BertTokenizerFast)   )
      with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer.save_pretrained(lowerCamelCase__   )
         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )

      self.assertIsInstance(lowerCamelCase__ ,   tokenizer.__class__   )
      self.assertEqual(tokenizera.vocab_size ,   1_2   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained('''ctrl'''   )
      # There is no fast CTRL so this always gives us a slow tokenizer.
      self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  get_tokenizer_config('''bert-base-cased'''   )
      UpperCamelCase       =  config.pop('''_commit_hash''' ,   lowerCamelCase__   )
      # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
      self.assertEqual(lowerCamelCase__ ,   {'''do_lower_case''': False}   )

      # This model does not have a tokenizer_config so we get back an empty dict.
      UpperCamelCase       =  get_tokenizer_config(lowerCamelCase__   )
      self.assertDictEqual(lowerCamelCase__ ,   {}   )

      # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
      UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
      with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer.save_pretrained(lowerCamelCase__   )
         UpperCamelCase       =  get_tokenizer_config(lowerCamelCase__   )

      # Check the class of the tokenizer was properly saved (note that it always saves the slow class).
      self.assertEqual(config['''tokenizer_class'''] ,   '''BertTokenizer'''   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      try:
         AutoConfig.register('''custom''' ,   lowerCamelCase__   )

         AutoTokenizer.register(lowerCamelCase__ ,   slow_tokenizer_class=lowerCamelCase__   )
         # Trying to register something existing in the Transformers library will raise an error
         with self.assertRaises(lowerCamelCase__   ):
            AutoTokenizer.register(lowerCamelCase__ ,   slow_tokenizer_class=lowerCamelCase__   )

         UpperCamelCase       =  CustomTokenizer.from_pretrained(lowerCamelCase__   )
         with tempfile.TemporaryDirectory() as tmp_dir:
            tokenizer.save_pretrained(lowerCamelCase__   )

            UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
            self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )

      finally:
         if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
         if CustomConfig in TOKENIZER_MAPPING._extra_content:
            del TOKENIZER_MAPPING._extra_content[CustomConfig]







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      try:
         AutoConfig.register('''custom''' ,   lowerCamelCase__   )

         # Can register in two steps
         AutoTokenizer.register(lowerCamelCase__ ,   slow_tokenizer_class=lowerCamelCase__   )
         self.assertEqual(TOKENIZER_MAPPING[CustomConfig] ,   (CustomTokenizer, None)   )
         AutoTokenizer.register(lowerCamelCase__ ,   fast_tokenizer_class=lowerCamelCase__   )
         self.assertEqual(TOKENIZER_MAPPING[CustomConfig] ,   (CustomTokenizer, CustomTokenizerFast)   )

         del TOKENIZER_MAPPING._extra_content[CustomConfig]
         # Can register in one step
         AutoTokenizer.register(
             lowerCamelCase__ ,   slow_tokenizer_class=lowerCamelCase__ ,   fast_tokenizer_class=lowerCamelCase__   )
         self.assertEqual(TOKENIZER_MAPPING[CustomConfig] ,   (CustomTokenizer, CustomTokenizerFast)   )

         # Trying to register something existing in the Transformers library will raise an error
         with self.assertRaises(lowerCamelCase__   ):
            AutoTokenizer.register(lowerCamelCase__ ,   fast_tokenizer_class=lowerCamelCase__   )

         # We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
         # and that model does not have a tokenizer.json
         with tempfile.TemporaryDirectory() as tmp_dir:
            UpperCamelCase       =  BertTokenizerFast.from_pretrained(lowerCamelCase__   )
            bert_tokenizer.save_pretrained(lowerCamelCase__   )
            UpperCamelCase       =  CustomTokenizerFast.from_pretrained(lowerCamelCase__   )

         with tempfile.TemporaryDirectory() as tmp_dir:
            tokenizer.save_pretrained(lowerCamelCase__   )

            UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__   )
            self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )

            UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   use_fast=lowerCamelCase__   )
            self.assertIsInstance(lowerCamelCase__ ,   lowerCamelCase__   )

      finally:
         if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
         if CustomConfig in TOKENIZER_MAPPING._extra_content:
            del TOKENIZER_MAPPING._extra_content[CustomConfig]







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      with self.assertRaises(lowerCamelCase__   ):
         UpperCamelCase       =  AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''   )
      # If remote code is disabled, we can't load this config.
      with self.assertRaises(lowerCamelCase__   ):
         UpperCamelCase       =  AutoTokenizer.from_pretrained(
             '''hf-internal-testing/test_dynamic_tokenizer''' ,   trust_remote_code=lowerCamelCase__   )

      UpperCamelCase       =  AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer''' ,   trust_remote_code=lowerCamelCase__   )
      self.assertTrue(tokenizer.special_attribute_present   )
      # Test tokenizer can be reloaded.
      with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer.save_pretrained(lowerCamelCase__   )
         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   trust_remote_code=lowerCamelCase__   )
      self.assertTrue(reloaded_tokenizer.special_attribute_present   )

      if is_tokenizers_available():
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizerFast'''   )
         self.assertEqual(reloaded_tokenizer.__class__.__name__ ,   '''NewTokenizerFast'''   )

         # Test we can also load the slow version
         UpperCamelCase       =  AutoTokenizer.from_pretrained(
             '''hf-internal-testing/test_dynamic_tokenizer''' ,   trust_remote_code=lowerCamelCase__ ,   use_fast=lowerCamelCase__   )
         self.assertTrue(tokenizer.special_attribute_present   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )
         # Test tokenizer can be reloaded.
         with tempfile.TemporaryDirectory() as tmp_dir:
            tokenizer.save_pretrained(lowerCamelCase__   )
            UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   trust_remote_code=lowerCamelCase__ ,   use_fast=lowerCamelCase__   )
         self.assertEqual(reloaded_tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )
         self.assertTrue(reloaded_tokenizer.special_attribute_present   )
      else:
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )
         self.assertEqual(reloaded_tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )







   @require_tokenizers
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      class 						lowercase__	(  snake_case_   ):






         '''simple docstring'''







         _snake_case		   =							False




      class 						lowercase__	(  snake_case_   ):






         '''simple docstring'''







         _snake_case		   =							NewTokenizer
         _snake_case		   =							False

      try:
         AutoConfig.register('''custom''' ,   lowerCamelCase__   )
         AutoTokenizer.register(lowerCamelCase__ ,   slow_tokenizer_class=lowerCamelCase__   )
         AutoTokenizer.register(lowerCamelCase__ ,   fast_tokenizer_class=lowerCamelCase__   )
         # If remote code is not set, the default is to use local
         UpperCamelCase       =  AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizerFast'''   )
         self.assertFalse(tokenizer.special_attribute_present   )
         UpperCamelCase       =  AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer''' ,   use_fast=lowerCamelCase__   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )
         self.assertFalse(tokenizer.special_attribute_present   )

         # If remote code is disabled, we load the local one.
         UpperCamelCase       =  AutoTokenizer.from_pretrained(
             '''hf-internal-testing/test_dynamic_tokenizer''' ,   trust_remote_code=lowerCamelCase__   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizerFast'''   )
         self.assertFalse(tokenizer.special_attribute_present   )
         UpperCamelCase       =  AutoTokenizer.from_pretrained(
             '''hf-internal-testing/test_dynamic_tokenizer''' ,   trust_remote_code=lowerCamelCase__ ,   use_fast=lowerCamelCase__   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )
         self.assertFalse(tokenizer.special_attribute_present   )

         # If remote is enabled, we load from the Hub
         UpperCamelCase       =  AutoTokenizer.from_pretrained(
             '''hf-internal-testing/test_dynamic_tokenizer''' ,   trust_remote_code=lowerCamelCase__   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizerFast'''   )
         self.assertTrue(tokenizer.special_attribute_present   )
         UpperCamelCase       =  AutoTokenizer.from_pretrained(
             '''hf-internal-testing/test_dynamic_tokenizer''' ,   trust_remote_code=lowerCamelCase__ ,   use_fast=lowerCamelCase__   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )
         self.assertTrue(tokenizer.special_attribute_present   )

      finally:
         if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
         if CustomConfig in TOKENIZER_MAPPING._extra_content:
            del TOKENIZER_MAPPING._extra_content[CustomConfig]







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained(
          '''hf-internal-testing/test_dynamic_tokenizer_legacy''' ,   trust_remote_code=lowerCamelCase__   )
      self.assertTrue(tokenizer.special_attribute_present   )
      if is_tokenizers_available():
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizerFast'''   )

         # Test we can also load the slow version
         UpperCamelCase       =  AutoTokenizer.from_pretrained(
             '''hf-internal-testing/test_dynamic_tokenizer_legacy''' ,   trust_remote_code=lowerCamelCase__ ,   use_fast=lowerCamelCase__   )
         self.assertTrue(tokenizer.special_attribute_present   )
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )
      else:
         self.assertEqual(tokenizer.__class__.__name__ ,   '''NewTokenizer'''   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      with self.assertRaisesRegex(
          lowerCamelCase__ ,   '''bert-base is not a local folder and is not a valid model identifier'''   ):
         UpperCamelCase       =  AutoTokenizer.from_pretrained('''bert-base'''   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      with self.assertRaisesRegex(
          lowerCamelCase__ ,   R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''   ):
         UpperCamelCase       =  AutoTokenizer.from_pretrained(lowerCamelCase__ ,   revision='''aaaaaa'''   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''   )
      with RequestCounter() as counter:
         UpperCamelCase       =  AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''   )
         self.assertEqual(counter.get_request_count ,   0   )
         self.assertEqual(counter.head_request_count ,   1   )
         self.assertEqual(counter.other_request_count ,   0   )







'''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)





