


from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


snake_case    :   Optional[Any]	    =					logging.get_logger(__name__)

snake_case    :   Dict	    =					{
    '''facebook/data2vec-vision-base-ft''': (
        '''https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json'''
    ),
}







class 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	'data2vec-vision'




 def __init__(		self ,  _lowerCamelCase=768 ,  _lowerCamelCase=12 ,  _lowerCamelCase=12 ,  _lowerCamelCase=3072 ,  _lowerCamelCase="gelu" ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.02 ,  _lowerCamelCase=1e-12 ,  _lowerCamelCase=224 ,  _lowerCamelCase=16 ,  _lowerCamelCase=3 ,  _lowerCamelCase=False ,  _lowerCamelCase=False ,  _lowerCamelCase=False ,  _lowerCamelCase=False ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=True ,  _lowerCamelCase=[3, 5, 7, 11] ,  _lowerCamelCase=[1, 2, 3, 6] ,  _lowerCamelCase=True ,  _lowerCamelCase=0.4 ,  _lowerCamelCase=256 ,  _lowerCamelCase=1 ,  _lowerCamelCase=False ,  _lowerCamelCase=255 ,  **_lowerCamelCase ,  ):
       super().__init__(**_lowerCamelCase   )

       a						:Tuple										=	hidden_size
       a						:Any										=	num_hidden_layers
       a						:Optional[int]										=	num_attention_heads
       a						:Dict										=	intermediate_size
       a						:List[Any]										=	hidden_act
       a						:List[str]										=	hidden_dropout_prob
       a						:Union[str, Any]										=	attention_probs_dropout_prob
       a						:Any										=	initializer_range
       a						:Any										=	layer_norm_eps

       a						:Union[str, Any]										=	image_size
       a						:int										=	patch_size
       a						:Optional[int]										=	num_channels
       a						:Union[str, Any]										=	use_mask_token
       a						:Optional[Any]										=	use_absolute_position_embeddings
       a						:Tuple										=	use_relative_position_bias
       a						:List[Any]										=	use_shared_relative_position_bias
       a						:Dict										=	layer_scale_init_value
       a						:Optional[int]										=	drop_path_rate
       a						:List[str]										=	use_mean_pooling
       # decode head attributes (semantic segmentation)
       a						:str										=	out_indices
       a						:Tuple										=	pool_scales
       # auxiliary head attributes (semantic segmentation)
       a						:List[Any]										=	use_auxiliary_head
       a						:List[Any]										=	auxiliary_loss_weight
       a						:Optional[int]										=	auxiliary_channels
       a						:List[str]										=	auxiliary_num_convs
       a						:str										=	auxiliary_concat_input
       a						:Union[str, Any]										=	semantic_loss_ignore_index







class 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	version.parse('1.11'							)




 @property
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       return OrderedDict(
           [
               ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
           ]   )




 @property
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       return 1e-4









import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 		_snake_case  (				_snake_case						,   unittest.TestCase							):
 SCREAMING_SNAKE_CASE__				=	MgpstrTokenizer
 SCREAMING_SNAKE_CASE__				=	False
 SCREAMING_SNAKE_CASE__				=	{}
 SCREAMING_SNAKE_CASE__				=	False




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       super().setUp()

       # fmt: off
       a						:int										=	['''[GO]''', '''[s]''', '''0''', '''1''', '''2''', '''3''', '''4''', '''5''', '''6''', '''7''', '''8''', '''9''', '''a''', '''b''', '''c''', '''d''', '''e''', '''f''', '''g''', '''h''', '''i''', '''j''', '''k''', '''l''', '''m''', '''n''', '''o''', '''p''', '''q''', '''r''', '''s''', '''t''', '''u''', '''v''', '''w''', '''x''', '''y''', '''z''']
       # fmt: on
       a						:List[str]										=	dict(zip(_lowerCamelCase ,  range(len(_lowerCamelCase   )   )   )   )

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




 def 	SCREAMING_SNAKE_CASE__    (		self ,  **_lowerCamelCase   ):
       return MgpstrTokenizer.from_pretrained(self.tmpdirname ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       a						:str										=	'''tester'''
       a						:Union[str, Any]										=	'''tester'''
       return input_text, output_text




 @unittest.skip('''MGP-STR always lower cases letters.'''   )
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       pass




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:List[Any]										=	self.get_tokenizers(do_lower_case=_lowerCamelCase   )
       for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''   ):
                   a						:Any										=	'''[SPECIAL_TOKEN]'''

                   tokenizer.add_special_tokens({'''cls_token''': special_token}   )
                   a						:str										=	tokenizer.encode([special_token] ,  add_special_tokens=_lowerCamelCase   )
                   self.assertEqual(len(_lowerCamelCase   ) ,  1   )

                   a						:Tuple										=	tokenizer.decode(_lowerCamelCase ,  skip_special_tokens=_lowerCamelCase   )
                   self.assertTrue(special_token not in decoded   )




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:Optional[Any]										=	self.get_tokenizers()
       for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''   ):
                   a							,    a						:Tuple										=	self.get_input_output_texts(_lowerCamelCase   )

                   a						:Tuple										=	tokenizer.tokenize(_lowerCamelCase   )
                   a						:int										=	tokenizer.convert_tokens_to_ids(_lowerCamelCase   )
                   a						:Optional[int]										=	tokenizer.encode(_lowerCamelCase ,  add_special_tokens=_lowerCamelCase   )
                   self.assertListEqual(_lowerCamelCase ,  _lowerCamelCase   )

                   a						:Any										=	tokenizer.convert_ids_to_tokens(_lowerCamelCase   )
                   self.assertNotEqual(len(_lowerCamelCase   ) ,  0   )
                   a						:str										=	tokenizer.decode(_lowerCamelCase   )
                   self.assertIsInstance(_lowerCamelCase ,  _lowerCamelCase   )

                   self.assertEqual(text_a.replace(''' ''' ,  ''''''   ) ,  _lowerCamelCase   )




 @unittest.skip('''MGP-STR tokenizer only handles one sequence.'''   )
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       pass




 @unittest.skip('''inputs cannot be pretokenized in MgpstrTokenizer'''   )
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       pass





