


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       lowerCamelCase__   (       lowerCAmelCase   ,							unittest.TestCase):
     SCREAMING_SNAKE_CASE__      			=			GPTaTokenizer
     SCREAMING_SNAKE_CASE__      			=			GPTaTokenizerFast
     SCREAMING_SNAKE_CASE__      			=			True
     SCREAMING_SNAKE_CASE__      			=			{'''add_prefix_space''': True}
     SCREAMING_SNAKE_CASE__      			=			False





     def      __A					(self       )     ->   Dict:
      super().setUp()

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

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





     def      __A					(self		,     **UpperCAmelCase       )     ->   str:
      kwargs.update(self.special_tokens_map       )
      return GPTaTokenizer.from_pretrained(self.tmpdirname		,     **UpperCAmelCase       )





     def      __A					(self		,     **UpperCAmelCase       )     ->   Dict:
      kwargs.update(self.special_tokens_map       )
      return GPTaTokenizerFast.from_pretrained(self.tmpdirname		,     **UpperCAmelCase       )





     def      __A					(self		,     UpperCAmelCase       )     ->   Tuple:
      _lowercase							      ='''lower newer'''
      _lowercase							      ='''lower newer'''
      return input_text, output_text





     def      __A					(self       )     ->   List[Any]:
      _lowercase							      =GPTaTokenizer(self.vocab_file		,     self.merges_file		,     **self.special_tokens_map       )
      _lowercase							      ='''lower newer'''
      _lowercase							      =['''\u0120low''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
      _lowercase							      =tokenizer.tokenize(UpperCAmelCase		,     add_prefix_space=UpperCAmelCase       )
      self.assertListEqual(UpperCAmelCase		,     UpperCAmelCase       )

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





     def      __A					(self       )     ->   List[str]:
      if not self.test_rust_tokenizer:
       return

      _lowercase							      =self.get_tokenizer()
      _lowercase							      =self.get_rust_tokenizer(add_prefix_space=UpperCAmelCase       )

      _lowercase							      ='''lower newer'''

      # Testing tokenization
      _lowercase							      =tokenizer.tokenize(UpperCAmelCase		,     add_prefix_space=UpperCAmelCase       )
      _lowercase							      =rust_tokenizer.tokenize(UpperCAmelCase       )
      self.assertListEqual(UpperCAmelCase		,     UpperCAmelCase       )

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

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

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





     def      __A					(self		,     *UpperCAmelCase		,     **UpperCAmelCase       )     ->   Dict:
      # It's very difficult to mix/test pretokenization with byte-level
      # And get both GPT2 and Roberta to work at the same time (mostly an issue of adding a space before the string)
      pass





     def      __A					(self		,     UpperCAmelCase=1_5       )     ->   Dict:
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"       ):
        _lowercase							      =self.rust_tokenizer_class.from_pretrained(UpperCAmelCase		,     **UpperCAmelCase       )

        # Simple input
        _lowercase							      ='''This is a simple input'''
        _lowercase							      =['''This is a simple input 1''', '''This is a simple input 2''']
        _lowercase							      =('''This is a simple input''', '''This is a pair''')
        _lowercase							      =[
            ('''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(UpperCAmelCase		,     tokenizer_r.encode		,     UpperCAmelCase		,     max_length=UpperCAmelCase		,     padding='''max_length'''       )

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

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

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

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

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





     def      __A					(self       )     ->   Dict:
      _lowercase							      =GPTaTokenizer.from_pretrained(self.tmpdirname		,     pad_token='''<pad>'''       )

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

      _lowercase							      =tokenizer.pad_token_id

      _lowercase							      =tokenizer(UpperCAmelCase		,     padding='''max_length'''		,     max_length=3_0		,     return_tensors='''np'''       )
      _lowercase							      =tokenizer(UpperCAmelCase		,     padding=UpperCAmelCase		,     truncate=UpperCAmelCase		,     return_tensors='''np'''       )
      _lowercase							      =tokenizer(*UpperCAmelCase		,     padding='''max_length'''		,     max_length=6_0		,     return_tensors='''np'''       )
      _lowercase							      =tokenizer(UpperCAmelCase		,     padding=UpperCAmelCase		,     truncate=UpperCAmelCase		,     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      __A					(self       )     ->   int:
      _lowercase							      ='''$$$'''
      _lowercase							      =GPTaTokenizer.from_pretrained(self.tmpdirname		,     bos_token=UpperCAmelCase		,     add_bos_token=UpperCAmelCase       )

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

      _lowercase							      =tokenizer.bos_token_id

      _lowercase							      =tokenizer(UpperCAmelCase       )
      _lowercase							      =tokenizer(UpperCAmelCase       )

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

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

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





     def      __A					(self       )     ->   Union[str, Any]:
      pass





     def      __A					(self       )     ->   Optional[Any]:
      # TODO: change to self.get_tokenizers() when the fast version is implemented
      _lowercase							      =[self.get_tokenizer(do_lower_case=UpperCAmelCase		,     add_bos_token=UpperCAmelCase       )]
      for tokenizer in tokenizers:
       with self.subTest(f"{tokenizer.__class__.__name__}"       ):
        _lowercase							      ='''Encode this.'''
        _lowercase							      ='''This one too please.'''
        _lowercase							      =tokenizer.encode(UpperCAmelCase		,     add_special_tokens=UpperCAmelCase       )
        encoded_sequence += tokenizer.encode(UpperCAmelCase		,     add_special_tokens=UpperCAmelCase       )
        _lowercase							      =tokenizer.encode_plus(
            UpperCAmelCase		,     UpperCAmelCase		,     add_special_tokens=UpperCAmelCase		,     return_special_tokens_mask=UpperCAmelCase		,     )
        _lowercase							      =encoded_sequence_dict['''input_ids''']
        _lowercase							      =encoded_sequence_dict['''special_tokens_mask''']
        self.assertEqual(len(UpperCAmelCase       )		,     len(UpperCAmelCase       )       )

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







@require_tokenizers
class       lowerCamelCase__   (       unittest.TestCase):





     def      __A					(self       )     ->   List[Any]:
      # More context:
      # https://huggingface.co/wjmcat/opt-350m-paddle/discussions/1
      # https://huggingface.slack.com/archives/C01N44FJDHT/p1653511495183519
      # https://github.com/huggingface/transformers/pull/17088#discussion_r871246439

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

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

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





     def      __A					(self       )     ->   List[str]:
      _lowercase							      =AutoTokenizer.from_pretrained('''facebook/opt-350m'''		,     use_slow=UpperCAmelCase       )
      _lowercase							      ='''A photo of a cat'''

      _lowercase							      =tokenizer.encode(
          UpperCAmelCase		,     )
      # Same as above
      self.assertEqual(UpperCAmelCase		,     [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      __A					(self       )     ->   Any:
      _lowercase							      =AutoTokenizer.from_pretrained('''facebook/opt-350m'''		,     from_slow=UpperCAmelCase       )

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

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





from typing import Any
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						)     ->			list:







 """simple docstring"""


 _validation(
     __snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						)
 # Creates data structures and fill initial step
 _lowercase							      ={}
 _lowercase							      ={}
 for state in states_space:
  _lowercase							      =observations_space[0]
  _lowercase							      =(
      initial_probabilities[state] * emission_probabilities[state][observation]
  )
  _lowercase							      =None

 # Fills the data structure with the probabilities of
 # different transitions and pointers to previous states
 for o in range(1     ,						len(__snake_case						)						):
  _lowercase							      =observations_space[o]
  _lowercase							      =observations_space[o - 1]
  for state in states_space:
   # Calculates the argmax for probability function
   _lowercase							      =''''''
   _lowercase							      =-1
   for k_state in states_space:
    _lowercase							      =(
        probabilities[(k_state, prior_observation)]
        * transition_probabilities[k_state][state]
        * emission_probabilities[state][observation]
    )
    if probability > max_probability:
     _lowercase							      =probability
     _lowercase							      =k_state

            # Update probabilities and pointers dicts
   _lowercase							      =(
       probabilities[(arg_max, prior_observation)]
       * transition_probabilities[arg_max][state]
       * emission_probabilities[state][observation]
   )

   _lowercase							      =arg_max

    # The final observation
 _lowercase							      =observations_space[len(__snake_case						) - 1]

 # argmax for given final observation
 _lowercase							      =''''''
 _lowercase							      =-1
 for k_state in states_space:
  _lowercase							      =probabilities[(k_state, final_observation)]
  if probability > max_probability:
   _lowercase							      =probability
   _lowercase							      =k_state
 _lowercase							      =arg_max

 # Process pointers backwards
 _lowercase							      =last_state
 _lowercase							      =[]
 for o in range(len(__snake_case						) - 1     ,						-1     ,						-1						):
  result.append(__snake_case						)
  _lowercase							      =pointers[previous, observations_space[o]]
 result.reverse()

 return result
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						)     ->			None:







 """simple docstring"""


 _validate_not_empty(
     __snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						)
 _validate_lists(__snake_case     ,						__snake_case						)
 _validate_dicts(
     __snake_case     ,						__snake_case     ,						__snake_case						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case     ,						)     ->			None:







 """simple docstring"""


 if not all(
     [
         observations_space,
         states_space,
         initial_probabilities,
         transition_probabilities,
         emission_probabilities,
     ]						):
  raise ValueError('''There\'s an empty parameter'''						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case						)     ->			None:







 """simple docstring"""


 _validate_list(__snake_case     ,						'''observations_space'''						)
 _validate_list(__snake_case     ,						'''states_space'''						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case						)     ->			None:







 """simple docstring"""


 if not isinstance(_object     ,						__snake_case						):
  _lowercase							      =F"{var_name} must be a list"
  raise ValueError(__snake_case						)
 else:
  for x in _object:
   if not isinstance(__snake_case     ,						__snake_case						):
    _lowercase							      =F"{var_name} must be a list of strings"
    raise ValueError(__snake_case						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case     ,						)     ->			None:







 """simple docstring"""


 _validate_dict(__snake_case     ,						'''initial_probabilities'''     ,						__snake_case						)
 _validate_nested_dict(__snake_case     ,						'''transition_probabilities'''						)
 _validate_nested_dict(__snake_case     ,						'''emission_probabilities'''						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case						)     ->			None:







 """simple docstring"""


 _validate_dict(_object     ,						__snake_case     ,						__snake_case						)
 for x in _object.values():
  _validate_dict(__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case						)
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case     ,						__snake_case = False						)     ->			None:







 """simple docstring"""


 if not isinstance(_object     ,						__snake_case						):
  _lowercase							      =F"{var_name} must be a dict"
  raise ValueError(__snake_case						)
 if not all(isinstance(__snake_case     ,						__snake_case						) for x in _object						):
  _lowercase							      =F"{var_name} all keys must be strings"
  raise ValueError(__snake_case						)
 if not all(isinstance(__snake_case     ,						__snake_case						) for x in _object.values()						):
  _lowercase							      ='''nested dictionary ''' if nested else ''''''
  _lowercase							      =F"{var_name} {nested_text}all values must be {value_type.__name__}"
  raise ValueError(__snake_case						)


if __name__ == "__main__":
  from doctest import testmod

  testmod()

