


"""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 	lowercase__				(					A_				):
   __UpperCAmelCase							       =					'''owlvit_text_model'''





   def __init__(							self      ,   SCREAMING_SNAKE_CASE=4_9408      ,   SCREAMING_SNAKE_CASE=512      ,   SCREAMING_SNAKE_CASE=2048      ,   SCREAMING_SNAKE_CASE=12      ,   SCREAMING_SNAKE_CASE=8      ,   SCREAMING_SNAKE_CASE=16      ,   SCREAMING_SNAKE_CASE="quick_gelu"      ,   SCREAMING_SNAKE_CASE=1e-5      ,   SCREAMING_SNAKE_CASE=0.0      ,   SCREAMING_SNAKE_CASE=0.02      ,   SCREAMING_SNAKE_CASE=1.0      ,   SCREAMING_SNAKE_CASE=0      ,   SCREAMING_SNAKE_CASE=4_9406      ,   SCREAMING_SNAKE_CASE=4_9407      ,   **SCREAMING_SNAKE_CASE      ,   )  ->  Dict:
      super().__init__(pad_token_id=SCREAMING_SNAKE_CASE      ,   bos_token_id=SCREAMING_SNAKE_CASE      ,   eos_token_id=SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)

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





   @classmethod
   def 		UpperCamelCase_  (							cls      ,   SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)  ->  "PretrainedConfig":
      cls._set_token_in_kwargs(SCREAMING_SNAKE_CASE)

      _lowerCamelCase   ,    _lowerCamelCase	:					int   =		cls.get_config_dict(SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)

      # get the text config dict if we are loading from OwlViTConfig
      if config_dict.get("""model_type""") == "owlvit":
         _lowerCamelCase	:					List[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(SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)







class 	lowercase__				(					A_				):
   __UpperCAmelCase							       =					'''owlvit_vision_model'''





   def __init__(							self      ,   SCREAMING_SNAKE_CASE=768      ,   SCREAMING_SNAKE_CASE=3072      ,   SCREAMING_SNAKE_CASE=12      ,   SCREAMING_SNAKE_CASE=12      ,   SCREAMING_SNAKE_CASE=3      ,   SCREAMING_SNAKE_CASE=768      ,   SCREAMING_SNAKE_CASE=32      ,   SCREAMING_SNAKE_CASE="quick_gelu"      ,   SCREAMING_SNAKE_CASE=1e-5      ,   SCREAMING_SNAKE_CASE=0.0      ,   SCREAMING_SNAKE_CASE=0.02      ,   SCREAMING_SNAKE_CASE=1.0      ,   **SCREAMING_SNAKE_CASE      ,   )  ->  Tuple:
      super().__init__(**SCREAMING_SNAKE_CASE)

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





   @classmethod
   def 		UpperCamelCase_  (							cls      ,   SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)  ->  "PretrainedConfig":
      cls._set_token_in_kwargs(SCREAMING_SNAKE_CASE)

      _lowerCamelCase   ,    _lowerCamelCase	:					Optional[int]   =		cls.get_config_dict(SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)

      # get the vision config dict if we are loading from OwlViTConfig
      if config_dict.get("""model_type""") == "owlvit":
         _lowerCamelCase	:					Optional[int]   =		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(SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)







class 	lowercase__				(					A_				):
   __UpperCAmelCase							       =					'''owlvit'''
   __UpperCAmelCase							       =					True





   def __init__(							self      ,   SCREAMING_SNAKE_CASE=None      ,   SCREAMING_SNAKE_CASE=None      ,   SCREAMING_SNAKE_CASE=512      ,   SCREAMING_SNAKE_CASE=2.65_92      ,   SCREAMING_SNAKE_CASE=True      ,   **SCREAMING_SNAKE_CASE      ,   )  ->  Union[str, Any]:
      super().__init__(**SCREAMING_SNAKE_CASE)

      if text_config is None:
         _lowerCamelCase	:					Dict   =		{}
         logger.info("""text_config is None. Initializing the OwlViTTextConfig with default values.""")

      if vision_config is None:
         _lowerCamelCase	:					Any   =		{}
         logger.info("""vision_config is None. initializing the OwlViTVisionConfig with default values.""")

      _lowerCamelCase	:					str   =		OwlViTTextConfig(**SCREAMING_SNAKE_CASE)
      _lowerCamelCase	:					Optional[int]   =		OwlViTVisionConfig(**SCREAMING_SNAKE_CASE)

      _lowerCamelCase	:					Union[str, Any]   =		projection_dim
      _lowerCamelCase	:					List[Any]   =		logit_scale_init_value
      _lowerCamelCase	:					List[str]   =		return_dict
      _lowerCamelCase	:					Optional[int]   =		1.0





   @classmethod
   def 		UpperCamelCase_  (							cls      ,   SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)  ->  "PretrainedConfig":
      cls._set_token_in_kwargs(SCREAMING_SNAKE_CASE)

      _lowerCamelCase   ,    _lowerCamelCase	:					Dict   =		cls.get_config_dict(SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)

      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(SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)





   @classmethod
   def 		UpperCamelCase_  (							cls      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)  ->  Tuple:
      _lowerCamelCase	:					Tuple   =		{}
      _lowerCamelCase	:					Dict   =		text_config
      _lowerCamelCase	:					int   =		vision_config

      return cls.from_dict(SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)





   def 		UpperCamelCase_  (							self)  ->  Tuple:
      _lowerCamelCase	:					Union[str, Any]   =		copy.deepcopy(self.__dict__)
      _lowerCamelCase	:					Dict   =		self.text_config.to_dict()
      _lowerCamelCase	:					Any   =		self.vision_config.to_dict()
      _lowerCamelCase	:					Optional[int]   =		self.__class__.model_type
      return output







class 	lowercase__				(					A_				):





   @property
   def 		UpperCamelCase_  (							self)  ->  Mapping[str, Mapping[int, str]]:
      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)  ->  Mapping[str, Mapping[int, str]]:
      return OrderedDict(
          [
              ("""logits_per_image""", {0: """batch"""}),
              ("""logits_per_text""", {0: """batch"""}),
              ("""text_embeds""", {0: """batch"""}),
              ("""image_embeds""", {0: """batch"""}),
          ])





   @property
   def 		UpperCamelCase_  (							self)  ->  float:
      return 1e-4





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = -1      ,   SCREAMING_SNAKE_CASE = -1      ,   SCREAMING_SNAKE_CASE = None      ,   )  ->  Mapping[str, Any]:
      _lowerCamelCase	:					List[str]   =		super().generate_dummy_inputs(
          processor.tokenizer      ,   batch_size=SCREAMING_SNAKE_CASE      ,   seq_length=SCREAMING_SNAKE_CASE      ,   framework=SCREAMING_SNAKE_CASE)
      _lowerCamelCase	:					Tuple   =		super().generate_dummy_inputs(
          processor.image_processor      ,   batch_size=SCREAMING_SNAKE_CASE      ,   framework=SCREAMING_SNAKE_CASE)
      return {**text_input_dict, **image_input_dict}





   @property
   def 		UpperCamelCase_  (							self)  ->  int:
      return 14




import string





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       ''
							for i in sequence:
														snake_case_     							=       ord(UpperCamelCase__ )
														if 65 <= extract <= 90:
																					output += chr(155 - extract )
														elif 97 <= extract <= 122:
																					output += chr(219 - extract )
														else:
																					output += i
							return output





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       string.ascii_letters
							snake_case_     							=       string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
							return "".join(
							    letters_reversed[letters.index(UpperCamelCase__ )] if c in letters else c for c in sequence )





def    __lowerCamelCase      (					):







							'''simple docstring'''






							from timeit import timeit

							print('Running performance benchmarks...' )
							snake_case_     							=       'from string import printable ; from __main__ import atbash, atbash_slow'
							print(F'''> atbash_slow(): {timeit("atbash_slow(printable)"  ,				setup=UpperCamelCase__ )} seconds''' )
							print(F'''>      atbash(): {timeit("atbash(printable)"  ,				setup=UpperCamelCase__ )} seconds''' )


if __name__ == "__main__":
					for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
										print(F'''{example} encrypted in atbash: {atbash(example)}''')
					benchmark()




