


'''simple docstring'''






import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A	:	List[str]     =     logging.get_logger(__name__)

__A	:	Optional[Any]     =     {
    'microsoft/git-base': 'https://huggingface.co/microsoft/git-base/resolve/main/config.json',
}
class 						__UpperCamelCase	(						__A							):
							lowercase			:		Tuple   		=  """git_vision_model"""





							def __init__(  self		:str  ,_UpperCamelCase		:List[str]=7_6_8  ,_UpperCamelCase		:Any=3_0_7_2  ,_UpperCamelCase		:Union[str, Any]=1_2  ,_UpperCamelCase		:str=1_2  ,_UpperCamelCase		:Tuple=3  ,_UpperCamelCase		:Dict=2_2_4  ,_UpperCamelCase		:Optional[Any]=1_6  ,_UpperCamelCase		:Any="quick_gelu"  ,_UpperCamelCase		:Optional[int]=1E-5  ,_UpperCamelCase		:Any=0.0  ,_UpperCamelCase		:Tuple=0.02  ,**_UpperCamelCase		:List[str]  ,):
									super().__init__(**UpperCamelCase__			)

									snake_case_		:							Union[str, Any]			       =						hidden_size
									snake_case_		:							Optional[Any]			       =						intermediate_size
									snake_case_		:							Union[str, Any]			       =						num_hidden_layers
									snake_case_		:							Optional[int]			       =						num_attention_heads
									snake_case_		:							List[str]			       =						num_channels
									snake_case_		:							Union[str, Any]			       =						patch_size
									snake_case_		:							Optional[int]			       =						image_size
									snake_case_		:							int			       =						initializer_range
									snake_case_		:							int			       =						attention_dropout
									snake_case_		:							int			       =						layer_norm_eps
									snake_case_		:							Optional[Any]			       =						hidden_act





							@classmethod
							def 		a__   (  cls		:Union[str, Any]  ,_UpperCamelCase		:str  ,**_UpperCamelCase		:int			):
									cls._set_token_in_kwargs(UpperCamelCase__			)

									snake_case_		:							Any			       =						cls.get_config_dict(UpperCamelCase__  ,**UpperCamelCase__			)

									# get the vision config dict if we are loading from GITConfig
									if config_dict.get("""model_type"""			) == "git":
											snake_case_		:							Dict			       =						config_dict['vision_config']

									if "model_type" in config_dict and hasattr(cls  ,"""model_type"""			) and config_dict["model_type"] != cls.model_type:
											logger.warning(
											    F'''You are using a model of type {config_dict["model_type"]} to instantiate a model of type '''
											    F'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''			)

									return cls.from_dict(UpperCamelCase__  ,**UpperCamelCase__			)





class 						__UpperCamelCase	(						__A							):
							lowercase			:		List[str]   		=  """git"""





							def __init__(  self		:Tuple  ,_UpperCamelCase		:Optional[Any]=None  ,_UpperCamelCase		:int=3_0_5_2_2  ,_UpperCamelCase		:List[Any]=7_6_8  ,_UpperCamelCase		:Union[str, Any]=6  ,_UpperCamelCase		:List[Any]=1_2  ,_UpperCamelCase		:Optional[Any]=3_0_7_2  ,_UpperCamelCase		:Optional[int]="gelu"  ,_UpperCamelCase		:Optional[int]=0.1  ,_UpperCamelCase		:Dict=0.1  ,_UpperCamelCase		:str=1_0_2_4  ,_UpperCamelCase		:List[Any]=0.02  ,_UpperCamelCase		:Optional[int]=1E-1_2  ,_UpperCamelCase		:Any=0  ,_UpperCamelCase		:List[Any]="absolute"  ,_UpperCamelCase		:Dict=True  ,_UpperCamelCase		:Tuple=False  ,_UpperCamelCase		:Tuple=1_0_1  ,_UpperCamelCase		:Tuple=1_0_2  ,_UpperCamelCase		:List[str]=None  ,**_UpperCamelCase		:Optional[Any]  ,):
									super().__init__(bos_token_id=UpperCamelCase__  ,eos_token_id=UpperCamelCase__  ,pad_token_id=UpperCamelCase__  ,**UpperCamelCase__			)

									if vision_config is None:
											snake_case_		:							Tuple			       =						{}
											logger.info("""vision_config is None. initializing the GitVisionConfig with default values."""			)

									snake_case_		:							List[Any]			       =						GitVisionConfig(**UpperCamelCase__			)
									snake_case_		:							str			       =						vocab_size
									snake_case_		:							Tuple			       =						hidden_size
									snake_case_		:							List[Any]			       =						num_hidden_layers
									snake_case_		:							Optional[int]			       =						num_attention_heads
									snake_case_		:							str			       =						hidden_act
									snake_case_		:							Union[str, Any]			       =						intermediate_size
									snake_case_		:							List[str]			       =						hidden_dropout_prob
									snake_case_		:							Optional[Any]			       =						attention_probs_dropout_prob
									snake_case_		:							Tuple			       =						max_position_embeddings
									snake_case_		:							Tuple			       =						initializer_range
									snake_case_		:							Any			       =						layer_norm_eps
									snake_case_		:							Optional[int]			       =						position_embedding_type
									snake_case_		:							str			       =						use_cache
									snake_case_		:							Tuple			       =						tie_word_embeddings
									snake_case_		:							str			       =						num_image_with_embedding

									snake_case_		:							Optional[Any]			       =						bos_token_id
									snake_case_		:							Tuple			       =						eos_token_id





							def 		a__   (  self		:Union[str, Any]			):
									snake_case_		:							Optional[int]			       =						copy.deepcopy(self.__dict__			)
									snake_case_		:							Dict			       =						self.vision_config.to_dict()
									snake_case_		:							Optional[Any]			       =						self.__class__.model_type
									return output



'''simple docstring'''






import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class 						__UpperCamelCase	(						lowercase__						,  unittest.TestCase							):
							lowercase			:		Dict   		=  TransfoXLTokenizer
							lowercase			:		Optional[Any]   		=  False
							lowercase			:		Dict   		=  False





							def 		a__   (  self		:Union[str, Any]			):
									super().setUp()

									snake_case_		:							Optional[int]			       =						[
									    """<unk>""",
									    """[CLS]""",
									    """[SEP]""",
									    """want""",
									    """unwanted""",
									    """wa""",
									    """un""",
									    """running""",
									    """,""",
									    """low""",
									    """l""",
									]
									snake_case_		:							Optional[int]			       =						os.path.join(self.tmpdirname  ,VOCAB_FILES_NAMES["""vocab_file"""]			)
									with open(self.vocab_file  ,"""w"""  ,encoding="""utf-8"""			) as vocab_writer:
											vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]			)			)





							def 		a__   (  self		:List[Any]  ,**_UpperCamelCase		:Optional[Any]			):
									snake_case_		:							Tuple			       =						True
									return TransfoXLTokenizer.from_pretrained(self.tmpdirname  ,**_UpperCamelCase			)





							def 		a__   (  self		:Tuple  ,_UpperCamelCase		:Union[str, Any]			):
									snake_case_		:							Any			       =						"""<unk> UNwanted , running"""
									snake_case_		:							Optional[int]			       =						"""<unk> unwanted, running"""
									return input_text, output_text





							def 		a__   (  self		:Dict			):
									snake_case_		:							Dict			       =						TransfoXLTokenizer(vocab_file=self.vocab_file  ,lower_case=_UpperCamelCase			)

									snake_case_		:							Dict			       =						tokenizer.tokenize("""<unk> UNwanted , running"""			)
									self.assertListEqual(_UpperCamelCase  ,["""<unk>""", """unwanted""", """,""", """running"""]			)

									self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase			)  ,[0, 4, 8, 7]			)





							def 		a__   (  self		:Optional[Any]			):
									snake_case_		:							Dict			       =						TransfoXLTokenizer(lower_case=_UpperCamelCase			)

									self.assertListEqual(
									    tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """			)  ,["""hello""", """!""", """how""", """are""", """you""", """?"""]			)





							def 		a__   (  self		:Any			):
									snake_case_		:							List[Any]			       =						TransfoXLTokenizer(lower_case=_UpperCamelCase			)

									self.assertListEqual(
									    tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """			)  ,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]			)





							def 		a__   (  self		:List[str]			):
									snake_case_		:							str			       =						TransfoXLTokenizer(lower_case=_UpperCamelCase			)
									snake_case_		:							List[str]			       =						"""Hello (bracket) and side-scrolled [and] Henry's $5,000 with 3.34 m. What's up!?"""
									snake_case_		:							Optional[int]			       =						[
									    """Hello""",
									    """(""",
									    """bracket""",
									    """)""",
									    """and""",
									    """side""",
									    """@-@""",
									    """scrolled""",
									    """[""",
									    """and""",
									    """]""",
									    """Henry""",
									    """'s""",
									    """$""",
									    """5""",
									    """@,@""",
									    """000""",
									    """with""",
									    """3""",
									    """@.@""",
									    """34""",
									    """m""",
									    """.""",
									    """What""",
									    """'s""",
									    """up""",
									    """!""",
									    """?""",
									]

									self.assertListEqual(tokenizer.tokenize(_UpperCamelCase			)  ,_UpperCamelCase			)

									self.assertEqual(tokenizer.convert_tokens_to_string(_UpperCamelCase			)  ,_UpperCamelCase			)





							def 		a__   (  self		:Dict			):
									snake_case_		:							Union[str, Any]			       =						self.get_tokenizer()
									snake_case_		:							Dict			       =						len(_UpperCamelCase			)

									tokenizer.add_tokens(["""new1""", """new2"""]			)
									tokenizer.move_added_token("""new1"""  ,1			)

									# Check that moved token is not copied (duplicate)
									self.assertEqual(len(_UpperCamelCase			)  ,original_len + 2			)
									# Check that token is moved to specified id
									self.assertEqual(tokenizer.encode("""new1"""			)  ,[1]			)
									self.assertEqual(tokenizer.decode([1]			)  ,"""new1"""			)