
'''simple docstring'''


import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 						lowercase__	(  snake_case_,					unittest.TestCase   ):






   '''simple docstring'''







   _snake_case		   =							GPTaTokenizer
   _snake_case		   =							GPTaTokenizerFast
   _snake_case		   =							True
   _snake_case		   =							{'''add_prefix_space''': True}
   _snake_case		   =							False







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      UpperCamelCase       =  [
          '''l''',
          '''o''',
          '''w''',
          '''e''',
          '''r''',
          '''s''',
          '''t''',
          '''i''',
          '''d''',
          '''n''',
          '''\u0120''',
          '''\u0120l''',
          '''\u0120n''',
          '''\u0120lo''',
          '''\u0120low''',
          '''er''',
          '''\u0120lowest''',
          '''\u0120newer''',
          '''\u0120wider''',
          '''<unk>''',
          '''<|endoftext|>''',
      ]
      UpperCamelCase       =  dict(zip(lowerCamelCase__ ,   range(len(lowerCamelCase__   )   )   )   )
      UpperCamelCase       =  ['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
      UpperCamelCase       =  {'''unk_token''': '''<unk>'''}

      UpperCamelCase       =  os.path.join(self.tmpdirname ,   VOCAB_FILES_NAMES['''vocab_file''']   )
      UpperCamelCase       =  os.path.join(self.tmpdirname ,   VOCAB_FILES_NAMES['''merges_file''']   )
      with open(self.vocab_file ,   '''w''' ,   encoding='''utf-8'''   ) as fp:
         fp.write(json.dumps(lowerCamelCase__   ) + '''\n'''   )
      with open(self.merges_file ,   '''w''' ,   encoding='''utf-8'''   ) as fp:
         fp.write('''\n'''.join(lowerCamelCase__   )   )







   def       UpperCAmelCase				(			self ,   **lowerCamelCase__   ):

      '''simple docstring'''







      kwargs.update(self.special_tokens_map   )
      return GPTaTokenizer.from_pretrained(self.tmpdirname ,   **lowerCamelCase__   )







   def       UpperCAmelCase				(			self ,   **lowerCamelCase__   ):

      '''simple docstring'''







      kwargs.update(self.special_tokens_map   )
      return GPTaTokenizerFast.from_pretrained(self.tmpdirname ,   **lowerCamelCase__   )







   def       UpperCAmelCase				(			self ,   lowerCamelCase__   ):

      '''simple docstring'''







      UpperCamelCase       =  '''lower newer'''
      UpperCamelCase       =  '''lower newer'''
      return input_text, output_text







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  GPTaTokenizer(self.vocab_file ,   self.merges_file ,   **self.special_tokens_map   )
      UpperCamelCase       =  '''lower newer'''
      UpperCamelCase       =  ['''\u0120low''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
      UpperCamelCase       =  tokenizer.tokenize(lowerCamelCase__ ,   add_prefix_space=lowerCamelCase__   )
      self.assertListEqual(lowerCamelCase__ ,   lowerCamelCase__   )

      UpperCamelCase       =  tokens + [tokenizer.unk_token]
      UpperCamelCase       =  [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase__   ) ,   lowerCamelCase__   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      if not self.test_rust_tokenizer:
         return

      UpperCamelCase       =  self.get_tokenizer()
      UpperCamelCase       =  self.get_rust_tokenizer(add_prefix_space=lowerCamelCase__   )

      UpperCamelCase       =  '''lower newer'''

      # Testing tokenization
      UpperCamelCase       =  tokenizer.tokenize(lowerCamelCase__ ,   add_prefix_space=lowerCamelCase__   )
      UpperCamelCase       =  rust_tokenizer.tokenize(lowerCamelCase__   )
      self.assertListEqual(lowerCamelCase__ ,   lowerCamelCase__   )

      # Testing conversion to ids without special tokens
      UpperCamelCase       =  tokenizer.encode(lowerCamelCase__ ,   add_special_tokens=lowerCamelCase__ ,   add_prefix_space=lowerCamelCase__   )
      UpperCamelCase       =  rust_tokenizer.encode(lowerCamelCase__ ,   add_special_tokens=lowerCamelCase__   )
      self.assertListEqual(lowerCamelCase__ ,   lowerCamelCase__   )

      # Testing conversion to ids with special tokens
      UpperCamelCase       =  self.get_rust_tokenizer(add_prefix_space=lowerCamelCase__   )
      UpperCamelCase       =  tokenizer.encode(lowerCamelCase__ ,   add_prefix_space=lowerCamelCase__   )
      UpperCamelCase       =  rust_tokenizer.encode(lowerCamelCase__   )
      self.assertListEqual(lowerCamelCase__ ,   lowerCamelCase__   )

      # Testing the unknown token
      UpperCamelCase       =  tokens + [rust_tokenizer.unk_token]
      UpperCamelCase       =  [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
      self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowerCamelCase__   ) ,   lowerCamelCase__   )







   def       UpperCAmelCase				(			self ,   *lowerCamelCase__ ,   **lowerCamelCase__   ):

      '''simple docstring'''







      pass







   def       UpperCAmelCase				(			self ,   lowerCamelCase__=1_5   ):

      '''simple docstring'''







      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'   ):
            UpperCamelCase       =  self.rust_tokenizer_class.from_pretrained(lowerCamelCase__ ,   **lowerCamelCase__   )

            # Simple input
            UpperCamelCase       =  '''This is a simple input'''
            UpperCamelCase       =  ['''This is a simple input 1''', '''This is a simple input 2''']
            UpperCamelCase       =  ('''This is a simple input''', '''This is a pair''')
            UpperCamelCase       =  [
                ('''This is a simple input 1''', '''This is a simple input 2'''),
                ('''This is a simple pair 1''', '''This is a simple pair 2'''),
            ]

            # Simple input tests
            self.assertRaises(lowerCamelCase__ ,   tokenizer_r.encode ,   lowerCamelCase__ ,   max_length=lowerCamelCase__ ,   padding='''max_length'''   )

            # Simple input
            self.assertRaises(lowerCamelCase__ ,   tokenizer_r.encode_plus ,   lowerCamelCase__ ,   max_length=lowerCamelCase__ ,   padding='''max_length'''   )

            # Simple input
            self.assertRaises(
                lowerCamelCase__ ,   tokenizer_r.batch_encode_plus ,   lowerCamelCase__ ,   max_length=lowerCamelCase__ ,   padding='''max_length''' ,   )

            # Pair input
            self.assertRaises(lowerCamelCase__ ,   tokenizer_r.encode ,   lowerCamelCase__ ,   max_length=lowerCamelCase__ ,   padding='''max_length'''   )

            # Pair input
            self.assertRaises(lowerCamelCase__ ,   tokenizer_r.encode_plus ,   lowerCamelCase__ ,   max_length=lowerCamelCase__ ,   padding='''max_length'''   )

            # Pair input
            self.assertRaises(
                lowerCamelCase__ ,   tokenizer_r.batch_encode_plus ,   lowerCamelCase__ ,   max_length=lowerCamelCase__ ,   padding='''max_length''' ,   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  GPTaTokenizer.from_pretrained(self.tmpdirname ,   pad_token='''<pad>'''   )

      # Simple input
      UpperCamelCase       =  '''This is a simple input'''
      UpperCamelCase       =  ['''This is a simple input looooooooong''', '''This is a simple input''']
      UpperCamelCase       =  ('''This is a simple input''', '''This is a pair''')
      UpperCamelCase       =  [
          ('''This is a simple input loooooong''', '''This is a simple input'''),
          ('''This is a simple pair loooooong''', '''This is a simple pair'''),
      ]

      UpperCamelCase       =  tokenizer.pad_token_id

      UpperCamelCase       =  tokenizer(lowerCamelCase__ ,   padding='''max_length''' ,   max_length=3_0 ,   return_tensors='''np'''   )
      UpperCamelCase       =  tokenizer(lowerCamelCase__ ,   padding=lowerCamelCase__ ,   truncate=lowerCamelCase__ ,   return_tensors='''np'''   )
      UpperCamelCase       =  tokenizer(*lowerCamelCase__ ,   padding='''max_length''' ,   max_length=6_0 ,   return_tensors='''np'''   )
      UpperCamelCase       =  tokenizer(lowerCamelCase__ ,   padding=lowerCamelCase__ ,   truncate=lowerCamelCase__ ,   return_tensors='''np'''   )

      # s
      # test single string max_length padding
      self.assertEqual(out_s['''input_ids'''].shape[-1] ,   3_0   )
      self.assertTrue(pad_token_id in out_s['''input_ids''']   )
      self.assertTrue(0 in out_s['''attention_mask''']   )

      # s2
      # test automatic padding
      self.assertEqual(out_sa['''input_ids'''].shape[-1] ,   3_3   )
      # long slice doesn't have padding
      self.assertFalse(pad_token_id in out_sa['''input_ids'''][0]   )
      self.assertFalse(0 in out_sa['''attention_mask'''][0]   )
      # short slice does have padding
      self.assertTrue(pad_token_id in out_sa['''input_ids'''][1]   )
      self.assertTrue(0 in out_sa['''attention_mask'''][1]   )

      # p
      # test single pair max_length padding
      self.assertEqual(out_p['''input_ids'''].shape[-1] ,   6_0   )
      self.assertTrue(pad_token_id in out_p['''input_ids''']   )
      self.assertTrue(0 in out_p['''attention_mask''']   )

      # p2
      # test automatic padding pair
      self.assertEqual(out_pa['''input_ids'''].shape[-1] ,   5_2   )
      # long slice pair doesn't have padding
      self.assertFalse(pad_token_id in out_pa['''input_ids'''][0]   )
      self.assertFalse(0 in out_pa['''attention_mask'''][0]   )
      # short slice pair does have padding
      self.assertTrue(pad_token_id in out_pa['''input_ids'''][1]   )
      self.assertTrue(0 in out_pa['''attention_mask'''][1]   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  '''$$$'''
      UpperCamelCase       =  GPTaTokenizer.from_pretrained(self.tmpdirname ,   bos_token=lowerCamelCase__ ,   add_bos_token=lowerCamelCase__   )

      UpperCamelCase       =  '''This is a simple input'''
      UpperCamelCase       =  ['''This is a simple input 1''', '''This is a simple input 2''']

      UpperCamelCase       =  tokenizer.bos_token_id

      UpperCamelCase       =  tokenizer(lowerCamelCase__   )
      UpperCamelCase       =  tokenizer(lowerCamelCase__   )

      self.assertEqual(out_s.input_ids[0] ,   lowerCamelCase__   )
      self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids   )   )

      UpperCamelCase       =  tokenizer.decode(out_s.input_ids   )
      UpperCamelCase       =  tokenizer.batch_decode(out_sa.input_ids   )

      self.assertEqual(decode_s.split()[0] ,   lowerCamelCase__   )
      self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa   )   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      pass







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  [self.get_tokenizer(do_lower_case=lowerCamelCase__ ,   add_bos_token=lowerCamelCase__   )]
      for tokenizer in tokenizers:
         with self.subTest(f'{tokenizer.__class__.__name__}'   ):
            UpperCamelCase       =  '''Encode this.'''
            UpperCamelCase       =  '''This one too please.'''
            UpperCamelCase       =  tokenizer.encode(lowerCamelCase__ ,   add_special_tokens=lowerCamelCase__   )
            encoded_sequence += tokenizer.encode(lowerCamelCase__ ,   add_special_tokens=lowerCamelCase__   )
            UpperCamelCase       =  tokenizer.encode_plus(
                lowerCamelCase__ ,   lowerCamelCase__ ,   add_special_tokens=lowerCamelCase__ ,   return_special_tokens_mask=lowerCamelCase__ ,   )
            UpperCamelCase       =  encoded_sequence_dict['''input_ids''']
            UpperCamelCase       =  encoded_sequence_dict['''special_tokens_mask''']
            self.assertEqual(len(lowerCamelCase__   ) ,   len(lowerCamelCase__   )   )

            UpperCamelCase       =  [
                (x if not special_tokens_mask[i] else None) for i, x in enumerate(lowerCamelCase__   )
            ]
            UpperCamelCase       =  [x for x in filtered_sequence if x is not None]
            self.assertEqual(lowerCamelCase__ ,   lowerCamelCase__   )




@require_tokenizers
class 						lowercase__	(  unittest.TestCase   ):






   '''simple docstring'''







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained('''facebook/opt-350m''' ,   from_slow=lowerCamelCase__   )
      UpperCamelCase       =  '''A photo of a cat'''

      UpperCamelCase       =  tokenizer.encode(
          lowerCamelCase__ ,   )
      self.assertEqual(lowerCamelCase__ ,   [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]   )
      tokenizer.save_pretrained('''test_opt'''   )

      UpperCamelCase       =  AutoTokenizer.from_pretrained('''./test_opt'''   )
      UpperCamelCase       =  tokenizer.encode(
          lowerCamelCase__ ,   )
      self.assertEqual(lowerCamelCase__ ,   [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]   )







   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained('''facebook/opt-350m''' ,   use_slow=lowerCamelCase__   )
      UpperCamelCase       =  '''A photo of a cat'''

      UpperCamelCase       =  tokenizer.encode(
          lowerCamelCase__ ,   )
      # Same as above
      self.assertEqual(lowerCamelCase__ ,   [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]   )







   @unittest.skip('''This test is failing because of a bug in the fast tokenizer'''   )
   def       UpperCAmelCase				(			self   ):

      '''simple docstring'''







      UpperCamelCase       =  AutoTokenizer.from_pretrained('''facebook/opt-350m''' ,   from_slow=lowerCamelCase__   )

      UpperCamelCase       =  '''bos'''
      UpperCamelCase       =  tokenizer.get_vocab()['''bos''']

      UpperCamelCase       =  '''A photo of a cat'''
      UpperCamelCase       =  tokenizer.encode(
          lowerCamelCase__ ,   )
      # We changed the bos token
      self.assertEqual(lowerCamelCase__ ,   [3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]   )
      tokenizer.save_pretrained('''./tok'''   )
      UpperCamelCase       =  AutoTokenizer.from_pretrained('''./tok'''   )
      self.assertTrue(tokenizer.is_fast   )
      UpperCamelCase       =  tokenizer.encode(
          lowerCamelCase__ ,   )
      self.assertEqual(lowerCamelCase__ ,   [3_1_9_5_7, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]   )







'''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)





