


"""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 					__magic_name__		(			__UpperCAmelCase			,						unittest.TestCase     ):
       __A			:      Optional[Any]        =   GPTaTokenizer
       __A			:      int        =   GPTaTokenizerFast
       __A			:      Tuple        =   True
       __A			:      str        =   {"add_prefix_space": True}
       __A			:      List[Any]        =   False






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              super().setUp()

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

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






       def  __snake_case						(   self  :    Tuple  ,     **snake_case__  :    Optional[Any]				):

              '''simple docstring'''






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






       def  __snake_case						(   self  :    Tuple  ,     **snake_case__  :    List[Any]				):

              '''simple docstring'''






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






       def  __snake_case						(   self  :    List[str]  ,     snake_case__  :    Optional[Any]				):

              '''simple docstring'''






              lowercase		:Optional[int]       							=				'''lower newer'''
              lowercase		:int       							=				'''lower newer'''
              return input_text, output_text






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              lowercase		:Any       							=				GPTaTokenizer(self.vocab_file  ,     self.merges_file  ,     **self.special_tokens_map				)
              lowercase		:Union[str, Any]       							=				'''lower newer'''
              lowercase		:str       							=				['''\u0120low''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
              lowercase		:Optional[Any]       							=				tokenizer.tokenize(snake_case__  ,     add_prefix_space=snake_case__				)
              self.assertListEqual(snake_case__  ,     snake_case__				)

              lowercase		:List[str]       							=				tokens + [tokenizer.unk_token]
              lowercase		:List[str]       							=				[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__				)  ,     snake_case__				)






       def  __snake_case						(   self  :    Union[str, Any]				):

              '''simple docstring'''






              if not self.test_rust_tokenizer:
                     return

              lowercase		:Dict       							=				self.get_tokenizer()
              lowercase		:Any       							=				self.get_rust_tokenizer(add_prefix_space=snake_case__				)

              lowercase		:List[Any]       							=				'''lower newer'''

              # Testing tokenization
              lowercase		:str       							=				tokenizer.tokenize(snake_case__  ,     add_prefix_space=snake_case__				)
              lowercase		:Dict       							=				rust_tokenizer.tokenize(snake_case__				)
              self.assertListEqual(snake_case__  ,     snake_case__				)

              # Testing conversion to ids without special tokens
              lowercase		:str       							=				tokenizer.encode(snake_case__  ,     add_special_tokens=snake_case__  ,     add_prefix_space=snake_case__				)
              lowercase		:str       							=				rust_tokenizer.encode(snake_case__  ,     add_special_tokens=snake_case__				)
              self.assertListEqual(snake_case__  ,     snake_case__				)

              # Testing conversion to ids with special tokens
              lowercase		:List[Any]       							=				self.get_rust_tokenizer(add_prefix_space=snake_case__				)
              lowercase		:Union[str, Any]       							=				tokenizer.encode(snake_case__  ,     add_prefix_space=snake_case__				)
              lowercase		:List[Any]       							=				rust_tokenizer.encode(snake_case__				)
              self.assertListEqual(snake_case__  ,     snake_case__				)

              # Testing the unknown token
              lowercase		:Optional[Any]       							=				tokens + [rust_tokenizer.unk_token]
              lowercase		:Optional[int]       							=				[1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
              self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(snake_case__				)  ,     snake_case__				)






       def  __snake_case						(   self  :    Union[str, Any]  ,     *snake_case__  :    Dict  ,     **snake_case__  :    Any				):

              '''simple docstring'''






              pass






       def  __snake_case						(   self  :    int  ,     snake_case__  :    Optional[Any]=1_5				):

              '''simple docstring'''






              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
                            lowercase		:Tuple       							=				self.rust_tokenizer_class.from_pretrained(snake_case__  ,     **snake_case__				)

                            # Simple input
                            lowercase		:List[Any]       							=				'''This is a simple input'''
                            lowercase		:List[Any]       							=				['''This is a simple input 1''', '''This is a simple input 2''']
                            lowercase		:Tuple       							=				('''This is a simple input''', '''This is a pair''')
                            lowercase		:List[str]       							=				[
                                ('''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(snake_case__  ,     tokenizer_r.encode  ,     snake_case__  ,     max_length=snake_case__  ,     padding='''max_length'''				)

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

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

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

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

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






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              lowercase		:List[str]       							=				GPTaTokenizer.from_pretrained(self.tmpdirname  ,     pad_token='''<pad>'''				)

              # Simple input
              lowercase		:Optional[Any]       							=				'''This is a simple input'''
              lowercase		:Optional[int]       							=				['''This is a simple input looooooooong''', '''This is a simple input''']
              lowercase		:List[Any]       							=				('''This is a simple input''', '''This is a pair''')
              lowercase		:List[str]       							=				[
                  ('''This is a simple input loooooong''', '''This is a simple input'''),
                  ('''This is a simple pair loooooong''', '''This is a simple pair'''),
              ]

              lowercase		:Dict       							=				tokenizer.pad_token_id

              lowercase		:Tuple       							=				tokenizer(snake_case__  ,     padding='''max_length'''  ,     max_length=3_0  ,     return_tensors='''np'''				)
              lowercase		:int       							=				tokenizer(snake_case__  ,     padding=snake_case__  ,     truncate=snake_case__  ,     return_tensors='''np'''				)
              lowercase		:Optional[int]       							=				tokenizer(*snake_case__  ,     padding='''max_length'''  ,     max_length=6_0  ,     return_tensors='''np'''				)
              lowercase		:Any       							=				tokenizer(snake_case__  ,     padding=snake_case__  ,     truncate=snake_case__  ,     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  __snake_case						(   self  :    List[str]				):

              '''simple docstring'''






              lowercase		:Dict       							=				'''$$$'''
              lowercase		:List[Any]       							=				GPTaTokenizer.from_pretrained(self.tmpdirname  ,     bos_token=snake_case__  ,     add_bos_token=snake_case__				)

              lowercase		:Any       							=				'''This is a simple input'''
              lowercase		:Any       							=				['''This is a simple input 1''', '''This is a simple input 2''']

              lowercase		:str       							=				tokenizer.bos_token_id

              lowercase		:Dict       							=				tokenizer(snake_case__				)
              lowercase		:Dict       							=				tokenizer(snake_case__				)

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

              lowercase		:Any       							=				tokenizer.decode(out_s.input_ids				)
              lowercase		:str       							=				tokenizer.batch_decode(out_sa.input_ids				)

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






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              pass







       def  __snake_case						(   self  :    List[str]				):

              '''simple docstring'''






              lowercase		:str       							=				[self.get_tokenizer(do_lower_case=snake_case__  ,     add_bos_token=snake_case__				)]
              for tokenizer in tokenizers:
                     with self.subTest(f"""{tokenizer.__class__.__name__}"""				):
                            lowercase		:List[Any]       							=				'''Encode this.'''
                            lowercase		:List[str]       							=				'''This one too please.'''
                            lowercase		:Dict       							=				tokenizer.encode(snake_case__  ,     add_special_tokens=snake_case__				)
                            encoded_sequence += tokenizer.encode(snake_case__  ,     add_special_tokens=snake_case__				)
                            lowercase		:Union[str, Any]       							=				tokenizer.encode_plus(
                                snake_case__  ,     snake_case__  ,     add_special_tokens=snake_case__  ,     return_special_tokens_mask=snake_case__  ,     )
                            lowercase		:Dict       							=				encoded_sequence_dict['''input_ids''']
                            lowercase		:Optional[Any]       							=				encoded_sequence_dict['''special_tokens_mask''']
                            self.assertEqual(len(snake_case__				)  ,     len(snake_case__				)				)

                            lowercase		:Optional[int]       							=				[
                                (x if not special_tokens_mask[i] else None) for i, x in enumerate(snake_case__				)
                            ]
                            lowercase		:Any       							=				[x for x in filtered_sequence if x is not None]
                            self.assertEqual(snake_case__  ,     snake_case__				)







@require_tokenizers
class 					__magic_name__		(			unittest.TestCase     ):






       def  __snake_case						(   self  :    List[Any]				):

              '''simple docstring'''






              lowercase		:str       							=				AutoTokenizer.from_pretrained('''facebook/opt-350m'''  ,     from_slow=snake_case__				)
              lowercase		:List[str]       							=				'''A photo of a cat'''

              lowercase		:Optional[int]       							=				tokenizer.encode(
                  snake_case__  ,     )
              self.assertEqual(snake_case__  ,     [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]				)
              tokenizer.save_pretrained('''test_opt'''				)

              lowercase		:int       							=				AutoTokenizer.from_pretrained('''./test_opt'''				)
              lowercase		:str       							=				tokenizer.encode(
                  snake_case__  ,     )
              self.assertEqual(snake_case__  ,     [2, 2_5_0, 1_3_4_5, 9, 1_0, 4_7_5_8]				)






       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              lowercase		:Tuple       							=				AutoTokenizer.from_pretrained('''facebook/opt-350m'''  ,     use_slow=snake_case__				)
              lowercase		:List[Any]       							=				'''A photo of a cat'''

              lowercase		:Optional[int]       							=				tokenizer.encode(
                  snake_case__  ,     )
              # Same as above
              self.assertEqual(snake_case__  ,     [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  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              lowercase		:int       							=				AutoTokenizer.from_pretrained('''facebook/opt-350m'''  ,     from_slow=snake_case__				)

              lowercase		:Any       							=				'''bos'''
              lowercase		:Tuple       							=				tokenizer.get_vocab()['''bos''']

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





"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase      		=			{
    '''configuration_layoutlmv3''': [
        '''LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''LayoutLMv3Config''',
        '''LayoutLMv3OnnxConfig''',
    ],
    '''processing_layoutlmv3''': ['''LayoutLMv3Processor'''],
    '''tokenization_layoutlmv3''': ['''LayoutLMv3Tokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase      		=			['''LayoutLMv3TokenizerFast''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase      		=			[
     '''LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''LayoutLMv3ForQuestionAnswering''',
     '''LayoutLMv3ForSequenceClassification''',
     '''LayoutLMv3ForTokenClassification''',
     '''LayoutLMv3Model''',
     '''LayoutLMv3PreTrainedModel''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase      		=			[
     '''TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFLayoutLMv3ForQuestionAnswering''',
     '''TFLayoutLMv3ForSequenceClassification''',
     '''TFLayoutLMv3ForTokenClassification''',
     '''TFLayoutLMv3Model''',
     '''TFLayoutLMv3PreTrainedModel''',
 ]

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase      		=			['''LayoutLMv3FeatureExtractor''']
 UpperCAmelCase      		=			['''LayoutLMv3ImageProcessor''']


if TYPE_CHECKING:
 from .configuration_layoutlmva import (
     LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
     LayoutLMvaConfig,
     LayoutLMvaOnnxConfig,
 )
 from .processing_layoutlmva import LayoutLMvaProcessor
 from .tokenization_layoutlmva import LayoutLMvaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_layoutlmva import (
      LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
      LayoutLMvaForQuestionAnswering,
      LayoutLMvaForSequenceClassification,
      LayoutLMvaForTokenClassification,
      LayoutLMvaModel,
      LayoutLMvaPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_layoutlmva import (
      TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFLayoutLMvaForQuestionAnswering,
      TFLayoutLMvaForSequenceClassification,
      TFLayoutLMvaForTokenClassification,
      TFLayoutLMvaModel,
      TFLayoutLMvaPreTrainedModel,
  )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
  from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
 import sys

 UpperCAmelCase      		=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

