




'''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


A     =logging.get_logger(__name__)

A     ={
    '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  (	__a ):
       __a				:     Optional[int]   				=					"""owlvit_text_model"""
       def __init__(	self						:	Tuple   ,				lowercase						:	Union[str, Any]=49_408   ,				lowercase						:	str=512   ,				lowercase						:	int=2_048   ,				lowercase						:	Optional[Any]=12   ,				lowercase						:	Any=8   ,				lowercase						:	Optional[int]=16   ,				lowercase						:	Union[str, Any]="quick_gelu"   ,				lowercase						:	Dict=1E-5   ,				lowercase						:	Tuple=0.0   ,				lowercase						:	str=0.02   ,				lowercase						:	Dict=1.0   ,				lowercase						:	str=0   ,				lowercase						:	List[str]=49_406   ,				lowercase						:	int=49_407   ,				**lowercase						:	List[Any]   ,				):



           '''simple docstring'''

           super().__init__(pad_token_id=lowercase   ,				bos_token_id=lowercase   ,				eos_token_id=lowercase   ,				**lowercase				)

           UpperCAmelCase			       =		vocab_size
           UpperCAmelCase			       =		hidden_size
           UpperCAmelCase			       =		intermediate_size
           UpperCAmelCase			       =		num_hidden_layers
           UpperCAmelCase			       =		num_attention_heads
           UpperCAmelCase			       =		max_position_embeddings
           UpperCAmelCase			       =		hidden_act
           UpperCAmelCase			       =		layer_norm_eps
           UpperCAmelCase			       =		attention_dropout
           UpperCAmelCase			       =		initializer_range
           UpperCAmelCase			       =		initializer_factor







       @classmethod
       def     A      (	cls						:	int   ,				lowercase						:	Union[str, os.PathLike]   ,				**lowercase						:	List[Any]				):



           '''simple docstring'''

           cls._set_token_in_kwargs(lowercase				)

           UpperCAmelCase       ,     UpperCAmelCase			       =		cls.get_config_dict(lowercase   ,				**lowercase				)

           # get the text config dict if we are loading from OwlViTConfig
           if config_dict.get('''model_type'''				) == "owlvit":
               UpperCAmelCase			       =		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(lowercase   ,				**lowercase				)






class 			_a  (	__a ):
       __a				:     Dict   				=					"""owlvit_vision_model"""
       def __init__(	self						:	Tuple   ,				lowercase						:	str=768   ,				lowercase						:	Dict=3_072   ,				lowercase						:	int=12   ,				lowercase						:	Tuple=12   ,				lowercase						:	Optional[int]=3   ,				lowercase						:	Optional[int]=768   ,				lowercase						:	Optional[int]=32   ,				lowercase						:	Union[str, Any]="quick_gelu"   ,				lowercase						:	Dict=1E-5   ,				lowercase						:	List[Any]=0.0   ,				lowercase						:	List[Any]=0.02   ,				lowercase						:	str=1.0   ,				**lowercase						:	str   ,				):



           '''simple docstring'''

           super().__init__(**lowercase				)

           UpperCAmelCase			       =		hidden_size
           UpperCAmelCase			       =		intermediate_size
           UpperCAmelCase			       =		num_hidden_layers
           UpperCAmelCase			       =		num_attention_heads
           UpperCAmelCase			       =		num_channels
           UpperCAmelCase			       =		image_size
           UpperCAmelCase			       =		patch_size
           UpperCAmelCase			       =		hidden_act
           UpperCAmelCase			       =		layer_norm_eps
           UpperCAmelCase			       =		attention_dropout
           UpperCAmelCase			       =		initializer_range
           UpperCAmelCase			       =		initializer_factor







       @classmethod
       def     A      (	cls						:	Optional[Any]   ,				lowercase						:	Union[str, os.PathLike]   ,				**lowercase						:	int				):



           '''simple docstring'''

           cls._set_token_in_kwargs(lowercase				)

           UpperCAmelCase       ,     UpperCAmelCase			       =		cls.get_config_dict(lowercase   ,				**lowercase				)

           # get the vision config dict if we are loading from OwlViTConfig
           if config_dict.get('''model_type'''				) == "owlvit":
               UpperCAmelCase			       =		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(lowercase   ,				**lowercase				)






class 			_a  (	__a ):
       __a				:     Dict   				=					"""owlvit"""
       __a				:     Optional[Any]   				=					True
       def __init__(	self						:	Tuple   ,				lowercase						:	Tuple=None   ,				lowercase						:	Optional[Any]=None   ,				lowercase						:	List[str]=512   ,				lowercase						:	Any=2.6592   ,				lowercase						:	List[Any]=True   ,				**lowercase						:	str   ,				):



           '''simple docstring'''

           super().__init__(**lowercase				)

           if text_config is None:
               UpperCAmelCase			       =		{}
               logger.info('''text_config is None. Initializing the OwlViTTextConfig with default values.'''				)

           if vision_config is None:
               UpperCAmelCase			       =		{}
               logger.info('''vision_config is None. initializing the OwlViTVisionConfig with default values.'''				)

           UpperCAmelCase			       =		OwlViTTextConfig(**lowercase				)
           UpperCAmelCase			       =		OwlViTVisionConfig(**lowercase				)

           UpperCAmelCase			       =		projection_dim
           UpperCAmelCase			       =		logit_scale_init_value
           UpperCAmelCase			       =		return_dict
           UpperCAmelCase			       =		1.0
       @classmethod
       def     A      (	cls						:	Tuple   ,				lowercase						:	Union[str, os.PathLike]   ,				**lowercase						:	List[str]				):



           '''simple docstring'''

           cls._set_token_in_kwargs(lowercase				)

           UpperCAmelCase       ,     UpperCAmelCase			       =		cls.get_config_dict(lowercase   ,				**lowercase				)

           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(lowercase   ,				**lowercase				)
       @classmethod
       def     A      (	cls						:	List[str]   ,				lowercase						:	Dict   ,				lowercase						:	Dict   ,				**lowercase						:	Dict				):



           '''simple docstring'''

           UpperCAmelCase			       =		{}
           UpperCAmelCase			       =		text_config
           UpperCAmelCase			       =		vision_config

           return cls.from_dict(lowercase   ,				**lowercase				)







       def     A      (	self						:	Dict				):



           '''simple docstring'''

           UpperCAmelCase			       =		copy.deepcopy(self.__dict__				)
           UpperCAmelCase			       =		self.text_config.to_dict()
           UpperCAmelCase			       =		self.vision_config.to_dict()
           UpperCAmelCase			       =		self.__class__.model_type
           return output






class 			_a  (	__a ):
       @property
       def     A      (	self						:	Optional[Any]				):



           '''simple docstring'''

           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     A      (	self						:	str				):



           '''simple docstring'''

           return OrderedDict(
               [
                   ('''logits_per_image''', {0: '''batch'''}),
                   ('''logits_per_text''', {0: '''batch'''}),
                   ('''text_embeds''', {0: '''batch'''}),
                   ('''image_embeds''', {0: '''batch'''}),
               ]				)
       @property
       def     A      (	self						:	Any				):



           '''simple docstring'''

           return 1E-4
       def     A      (	self						:	Tuple   ,				lowercase						:	"ProcessorMixin"   ,				lowercase						:	int = -1   ,				lowercase						:	int = -1   ,				lowercase						:	Optional["TensorType"] = None   ,				):



           '''simple docstring'''

           UpperCAmelCase			       =		super().generate_dummy_inputs(
               processor.tokenizer   ,				batch_size=lowercase   ,				seq_length=lowercase   ,				framework=lowercase				)
           UpperCAmelCase			       =		super().generate_dummy_inputs(
               processor.image_processor   ,				batch_size=lowercase   ,				framework=lowercase				)
           return {**text_input_dict, **image_input_dict}







       @property
       def     A      (	self						:	List[Any]				):



           '''simple docstring'''

           return 14











from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

snake_case__					:							Union[str, Any]													=     (3, 9, -11, 0, 7, 5, 1, -1)
snake_case__					:							int													=     (4, 6, 2, 0, 8, 10, 3, -2)





@dataclass
class A_					:
   lowerCAmelCase__        = 42
   lowerCAmelCase__        = 42





class A_					:




   def __init__(self	:Dict    ,   _UpperCamelCase	:Iterable[int] )->					None:
         __A          =				None
         for i in sorted(_UpperCamelCase    ,   reverse=_UpperCamelCase ):
               __A          =				Node(_UpperCamelCase    ,   self.head )




   def __iter__(self	:List[str] )->					Iterator[int]:
         __A          =				self.head
         while node:
               yield node.data
               __A          =				node.next_node




   def __len__(self	:Union[str, Any] )->					int:
         return sum(1 for _ in self )






   def __str__(self	:List[Any] )->					str:
         return " -> ".join([str(_UpperCamelCase ) for node in self] )





def _a				(	lowerCamelCase:   SortedLinkedList					,				lowerCamelCase:   SortedLinkedList )	->						SortedLinkedList:







      '''simple docstring'''






      return SortedLinkedList(list(lowerCamelCase ) + list(lowerCamelCase ) )


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       snake_case__					:							Any													=     SortedLinkedList
       print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))





