



import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


UpperCAmelCase :				Any							=logging.get_logger(__name__)

UpperCAmelCase :				List[str]							={
    """google/vit-hybrid-base-bit-384""": """https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json""",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}


class    _lowercase (a_   ):
				'''simple docstring'''







				lowercase__     =    """vit-hybrid"""

				def __init__(			self  ,			snake_case__=None  ,			snake_case__=768  ,			snake_case__=12  ,			snake_case__=12  ,			snake_case__=3072  ,			snake_case__="gelu"  ,			snake_case__=0.0  ,			snake_case__=0.0  ,			snake_case__=0.02  ,			snake_case__=1e-12  ,			snake_case__=224  ,			snake_case__=1  ,			snake_case__=3  ,			snake_case__=[1, 1024, 24, 24]  ,			snake_case__=True  ,			**snake_case__  ,			):

									'''simple docstring'''


									super().__init__(**snake_case__     )

									if backbone_config is None:
														logger.info("`backbone_config` is `None`. Initializing the config with a `BiT` backbone."     )
														UpperCamelCase_			= {
														    "global_padding": "same",
														    "layer_type": "bottleneck",
														    "depths": [3, 4, 9],
														    "out_features": ["stage3"],
														    "embedding_dynamic_padding": True,
														}

									if isinstance(snake_case__  ,			snake_case__     ):
														if "model_type" in backbone_config:
																			UpperCamelCase_			= CONFIG_MAPPING[backbone_config["model_type"]]
														else:
																			logger.info(
																			    "`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."     )
																			UpperCamelCase_			= BitConfig
														UpperCamelCase_			= backbone_config_class(**snake_case__     )

									UpperCamelCase_			= backbone_featmap_shape
									UpperCamelCase_			= backbone_config
									UpperCamelCase_			= hidden_size
									UpperCamelCase_			= num_hidden_layers
									UpperCamelCase_			= num_attention_heads
									UpperCamelCase_			= intermediate_size
									UpperCamelCase_			= hidden_act
									UpperCamelCase_			= hidden_dropout_prob
									UpperCamelCase_			= attention_probs_dropout_prob
									UpperCamelCase_			= initializer_range
									UpperCamelCase_			= layer_norm_eps
									UpperCamelCase_			= image_size
									UpperCamelCase_			= patch_size
									UpperCamelCase_			= num_channels
									UpperCamelCase_			= qkv_bias

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= copy.deepcopy(self.__dict__     )
									UpperCamelCase_			= self.backbone_config.to_dict()
									UpperCamelCase_			= self.__class__.model_type
									return output





"""simple docstring"""
from transformers.models.cpm.tokenization_cpm import CpmTokenizer
from transformers.testing_utils import custom_tokenizers

from ..xlnet.test_modeling_xlnet import XLNetModelTest
@custom_tokenizers
class 							lowerCamelCase    (     _lowerCAmelCase							):






					'''simple docstring'''





					def   lowerCAmelCase_							(			self:				Optional[int]		,	snake_case:				Optional[Any]		,	snake_case:				Optional[Any]		,	snake_case:				Tuple		,	snake_case:				int		,	snake_case:				Optional[Any]		)  ->      int:
											return True






					def   lowerCAmelCase_							(			self:				Tuple		)  ->      Optional[int]:
											snake_case_					:Dict		=     CpmTokenizer.from_pretrained("""TsinghuaAI/CPM-Generate"""		)
											snake_case_					:Any		=     """Hugging Face大法好，谁用谁知道。"""
											snake_case_					:Union[str, Any]		=     """Hugging Face大法好,谁用谁知道。<unk>"""
											snake_case_					:Dict		=     """▁Hu gg ing ▁ ▂ ▁F ace ▁大法 ▁好 ▁ , ▁谁 ▁用 ▁谁 ▁知 道 ▁ 。""".split()

											snake_case_					:str		=     tokenizer.tokenize(snake_case		)
											self.assertListEqual(snake_case		,	snake_case		)

											snake_case_					:List[Any]		=     tokens + [tokenizer.unk_token]

											snake_case_					:Optional[Any]		=     [13_789, 13_283, 1_421, 8, 10, 1_164, 13_608, 16_528, 63, 8, 9, 440, 108, 440, 121, 90, 8, 12, 0]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case		)		,	snake_case		)

											snake_case_					:int		=     tokenizer.decode(snake_case		)
											self.assertEqual(snake_case		,	snake_case		)
