






'''simple docstring'''

import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union


if TYPE_CHECKING:
      from ...processing_utils import ProcessorMixin
      from ...utils import TensorType

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


UpperCamelCase      					=logging.get_logger(__name__)

UpperCamelCase      					={
    "google/owlvit-base-patch32": "https://huggingface.co/google/owlvit-base-patch32/resolve/main/config.json",
    "google/owlvit-base-patch16": "https://huggingface.co/google/owlvit-base-patch16/resolve/main/config.json",
    "google/owlvit-large-patch14": "https://huggingface.co/google/owlvit-large-patch14/resolve/main/config.json",
}




class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 __a      :    List[str]			  =    '''owlvit_text_model'''
 def __init__(				self      ,  __lowerCAmelCase=4_94_08      ,  __lowerCAmelCase=5_12      ,  __lowerCAmelCase=20_48      ,  __lowerCAmelCase=12      ,  __lowerCAmelCase=8      ,  __lowerCAmelCase=16      ,  __lowerCAmelCase="quick_gelu"      ,  __lowerCAmelCase=1E-5      ,  __lowerCAmelCase=0.0      ,  __lowerCAmelCase=0.02      ,  __lowerCAmelCase=1.0      ,  __lowerCAmelCase=0      ,  __lowerCAmelCase=4_94_06      ,  __lowerCAmelCase=4_94_07      ,  **__lowerCAmelCase      ,  ):
       super().__init__(pad_token_id=__lowerCAmelCase      ,  bos_token_id=__lowerCAmelCase      ,  eos_token_id=__lowerCAmelCase      ,  **__lowerCAmelCase			)

       UpperCamelCase_					: int            =				vocab_size
       UpperCamelCase_					: List[str]            =				hidden_size
       UpperCamelCase_					: Tuple            =				intermediate_size
       UpperCamelCase_					: Optional[int]            =				num_hidden_layers
       UpperCamelCase_					: List[Any]            =				num_attention_heads
       UpperCamelCase_					: int            =				max_position_embeddings
       UpperCamelCase_					: List[str]            =				hidden_act
       UpperCamelCase_					: Dict            =				layer_norm_eps
       UpperCamelCase_					: Optional[Any]            =				attention_dropout
       UpperCamelCase_					: str            =				initializer_range
       UpperCamelCase_					: Optional[Any]            =				initializer_factor





 @classmethod
 def 	_UpperCAmelCase							(				cls      ,  __lowerCAmelCase      ,  **__lowerCAmelCase			):
       cls._set_token_in_kwargs(__lowerCAmelCase			)

       UpperCamelCase_     ,      UpperCamelCase_					: Any            =				cls.get_config_dict(__lowerCAmelCase      ,  **__lowerCAmelCase			)

       # get the text config dict if we are loading from OwlViTConfig
       if config_dict.get("""model_type"""			) == "owlvit":
             UpperCamelCase_					: Optional[Any]            =				config_dict["""text_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(__lowerCAmelCase      ,  **__lowerCAmelCase			)






class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 __a      :    Dict			  =    '''owlvit_vision_model'''
 def __init__(				self      ,  __lowerCAmelCase=7_68      ,  __lowerCAmelCase=30_72      ,  __lowerCAmelCase=12      ,  __lowerCAmelCase=12      ,  __lowerCAmelCase=3      ,  __lowerCAmelCase=7_68      ,  __lowerCAmelCase=32      ,  __lowerCAmelCase="quick_gelu"      ,  __lowerCAmelCase=1E-5      ,  __lowerCAmelCase=0.0      ,  __lowerCAmelCase=0.02      ,  __lowerCAmelCase=1.0      ,  **__lowerCAmelCase      ,  ):
       super().__init__(**__lowerCAmelCase			)

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





 @classmethod
 def 	_UpperCAmelCase							(				cls      ,  __lowerCAmelCase      ,  **__lowerCAmelCase			):
       cls._set_token_in_kwargs(__lowerCAmelCase			)

       UpperCamelCase_     ,      UpperCamelCase_					: List[Any]            =				cls.get_config_dict(__lowerCAmelCase      ,  **__lowerCAmelCase			)

       # get the vision config dict if we are loading from OwlViTConfig
       if config_dict.get("""model_type"""			) == "owlvit":
             UpperCamelCase_					: List[str]            =				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(__lowerCAmelCase      ,  **__lowerCAmelCase			)






class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 __a      :    List[Any]			  =    '''owlvit'''
 __a      :    Union[str, Any]			  =    True
 def __init__(				self      ,  __lowerCAmelCase=None      ,  __lowerCAmelCase=None      ,  __lowerCAmelCase=5_12      ,  __lowerCAmelCase=2.65_92      ,  __lowerCAmelCase=True      ,  **__lowerCAmelCase      ,  ):
       super().__init__(**__lowerCAmelCase			)

       if text_config is None:
             UpperCamelCase_					: Optional[int]            =				{}
             logger.info("""text_config is None. Initializing the OwlViTTextConfig with default values."""			)

       if vision_config is None:
             UpperCamelCase_					: Optional[int]            =				{}
             logger.info("""vision_config is None. initializing the OwlViTVisionConfig with default values."""			)

       UpperCamelCase_					: List[Any]            =				OwlViTTextConfig(**__lowerCAmelCase			)
       UpperCamelCase_					: Tuple            =				OwlViTVisionConfig(**__lowerCAmelCase			)

       UpperCamelCase_					: Optional[int]            =				projection_dim
       UpperCamelCase_					: int            =				logit_scale_init_value
       UpperCamelCase_					: Optional[int]            =				return_dict
       UpperCamelCase_					: List[str]            =				1.0
 @classmethod
 def 	_UpperCAmelCase							(				cls      ,  __lowerCAmelCase      ,  **__lowerCAmelCase			):
       cls._set_token_in_kwargs(__lowerCAmelCase			)

       UpperCamelCase_     ,      UpperCamelCase_					: Any            =				cls.get_config_dict(__lowerCAmelCase      ,  **__lowerCAmelCase			)

       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(__lowerCAmelCase      ,  **__lowerCAmelCase			)
 @classmethod
 def 	_UpperCAmelCase							(				cls      ,  __lowerCAmelCase      ,  __lowerCAmelCase      ,  **__lowerCAmelCase			):
       UpperCamelCase_					: int            =				{}
       UpperCamelCase_					: Dict            =				text_config
       UpperCamelCase_					: Union[str, Any]            =				vision_config

       return cls.from_dict(__lowerCAmelCase      ,  **__lowerCAmelCase			)





 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: Optional[int]            =				copy.deepcopy(self.__dict__			)
       UpperCamelCase_					: List[str]            =				self.text_config.to_dict()
       UpperCamelCase_					: str            =				self.vision_config.to_dict()
       UpperCamelCase_					: Any            =				self.__class__.model_type
       return output






class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 @property
 def 	_UpperCAmelCase							(				self			):
       return OrderedDict(
           [
               ("""input_ids""", {0: """batch""", 1: """sequence"""}),
               ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
               ("""attention_mask""", {0: """batch""", 1: """sequence"""}),
           ]			)
 @property
 def 	_UpperCAmelCase							(				self			):
       return OrderedDict(
           [
               ("""logits_per_image""", {0: """batch"""}),
               ("""logits_per_text""", {0: """batch"""}),
               ("""text_embeds""", {0: """batch"""}),
               ("""image_embeds""", {0: """batch"""}),
           ]			)
 @property
 def 	_UpperCAmelCase							(				self			):
       return 1E-4
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase      ,  __lowerCAmelCase = -1      ,  __lowerCAmelCase = -1      ,  __lowerCAmelCase = None      ,  ):
       UpperCamelCase_					: Tuple            =				super().generate_dummy_inputs(
           processor.tokenizer      ,  batch_size=__lowerCAmelCase      ,  seq_length=__lowerCAmelCase      ,  framework=__lowerCAmelCase			)
       UpperCamelCase_					: int            =				super().generate_dummy_inputs(
           processor.image_processor      ,  batch_size=__lowerCAmelCase      ,  framework=__lowerCAmelCase			)
       return {**text_input_dict, **image_input_dict}





 @property
 def 	_UpperCAmelCase							(				self			):
       return 14














'''simple docstring'''

UpperCamelCase      					="Input must be a string of 8 numbers plus letter"
UpperCamelCase      					="TRWAGMYFPDXBNJZSQVHLCKE"



def 				snake_case       (  a_				:			str						)							->					bool:





      """simple docstring"""

      if not isinstance(a_     , a_						):
            UpperCamelCase_					: List[str]            =				f"Expected string as input, found {type(a_						).__name__}"
            raise TypeError(a_						)

      UpperCamelCase_					: int            =				spanish_id.replace("""-"""     , """"""						).upper()
      if len(a_						) != 9:
            raise ValueError(a_						)

      try:
            UpperCamelCase_					: List[str]            =				int(spanish_id_clean[0:8]						)
            UpperCamelCase_					: Any            =				spanish_id_clean[8]
      except ValueError as ex:
            raise ValueError(a_						) from ex

      if letter.isdigit():
            raise ValueError(a_						)

      return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
      import doctest

      doctest.testmod()






