





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


_lowerCamelCase :    Optional[Any]  							= logging.get_logger(__name__)

_lowerCamelCase :    Tuple  							= {
    '''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 						lowerCamelCase       (__lowerCamelCase      ):







							"""simple docstring"""




							UpperCAmelCase_      						=   "owlvit_text_model"






							def __init__( self     :					str,			_UpperCAmelCase     :					int=4_9_4_0_8,			_UpperCAmelCase     :					Dict=5_1_2,			_UpperCAmelCase     :					Any=2_0_4_8,			_UpperCAmelCase     :					Dict=1_2,			_UpperCAmelCase     :					List[str]=8,			_UpperCAmelCase     :					Tuple=1_6,			_UpperCAmelCase     :					Dict="quick_gelu",			_UpperCAmelCase     :					List[Any]=1E-5,			_UpperCAmelCase     :					Union[str, Any]=0.0,			_UpperCAmelCase     :					Tuple=0.02,			_UpperCAmelCase     :					Optional[int]=1.0,			_UpperCAmelCase     :					Optional[int]=0,			_UpperCAmelCase     :					Any=4_9_4_0_6,			_UpperCAmelCase     :					int=4_9_4_0_7,			**_UpperCAmelCase     :					str,			)				->			List[Any]:





														"""simple docstring"""
														super().__init__(pad_token_id=_UpperCAmelCase,			bos_token_id=_UpperCAmelCase,			eos_token_id=_UpperCAmelCase,			**_UpperCAmelCase						)

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






							@classmethod
							def  A_     ( cls     :					Union[str, Any],			_UpperCAmelCase     :					Union[str, os.PathLike],			**_UpperCAmelCase     :					int						)				->			"PretrainedConfig":





														"""simple docstring"""
														cls._set_token_in_kwargs(_UpperCAmelCase						)

														SCREAMING_SNAKE_CASE__       :      Any     =						cls.get_config_dict(_UpperCAmelCase,			**_UpperCAmelCase						)

														# get the text config dict if we are loading from OwlViTConfig
														if config_dict.get("model_type"						) == "owlvit":
																					SCREAMING_SNAKE_CASE__       :      Union[str, 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(_UpperCAmelCase,			**_UpperCAmelCase						)


class 						lowerCamelCase       (__lowerCamelCase      ):







							"""simple docstring"""




							UpperCAmelCase_      						=   "owlvit_vision_model"






							def __init__( self     :					Union[str, Any],			_UpperCAmelCase     :					str=7_6_8,			_UpperCAmelCase     :					List[str]=3_0_7_2,			_UpperCAmelCase     :					Optional[int]=1_2,			_UpperCAmelCase     :					List[Any]=1_2,			_UpperCAmelCase     :					Optional[int]=3,			_UpperCAmelCase     :					Optional[int]=7_6_8,			_UpperCAmelCase     :					List[str]=3_2,			_UpperCAmelCase     :					Tuple="quick_gelu",			_UpperCAmelCase     :					List[Any]=1E-5,			_UpperCAmelCase     :					Optional[Any]=0.0,			_UpperCAmelCase     :					Any=0.02,			_UpperCAmelCase     :					str=1.0,			**_UpperCAmelCase     :					Any,			)				->			Any:





														"""simple docstring"""
														super().__init__(**_UpperCAmelCase						)

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






							@classmethod
							def  A_     ( cls     :					Any,			_UpperCAmelCase     :					Union[str, os.PathLike],			**_UpperCAmelCase     :					str						)				->			"PretrainedConfig":





														"""simple docstring"""
														cls._set_token_in_kwargs(_UpperCAmelCase						)

														SCREAMING_SNAKE_CASE__       :      int     =						cls.get_config_dict(_UpperCAmelCase,			**_UpperCAmelCase						)

														# get the vision config dict if we are loading from OwlViTConfig
														if config_dict.get("model_type"						) == "owlvit":
																					SCREAMING_SNAKE_CASE__       :      List[Any]     =						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 						lowerCamelCase       (__lowerCamelCase      ):







							"""simple docstring"""




							UpperCAmelCase_      						=   "owlvit"
							UpperCAmelCase_      						=   True






							def __init__( self     :					List[Any],			_UpperCAmelCase     :					Dict=None,			_UpperCAmelCase     :					Optional[int]=None,			_UpperCAmelCase     :					List[Any]=5_1_2,			_UpperCAmelCase     :					List[str]=2.6592,			_UpperCAmelCase     :					Tuple=True,			**_UpperCAmelCase     :					Tuple,			)				->			Union[str, Any]:





														"""simple docstring"""
														super().__init__(**_UpperCAmelCase						)

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

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

														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						OwlViTTextConfig(**_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      Any     =						OwlViTVisionConfig(**_UpperCAmelCase						)

														SCREAMING_SNAKE_CASE__       :      Dict     =						projection_dim
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						logit_scale_init_value
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						return_dict
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						1.0






							@classmethod
							def  A_     ( cls     :					List[str],			_UpperCAmelCase     :					Union[str, os.PathLike],			**_UpperCAmelCase     :					Any						)				->			"PretrainedConfig":





														"""simple docstring"""
														cls._set_token_in_kwargs(_UpperCAmelCase						)

														SCREAMING_SNAKE_CASE__       :      Any     =						cls.get_config_dict(_UpperCAmelCase,			**_UpperCAmelCase						)

														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						)






							@classmethod
							def  A_     ( cls     :					str,			_UpperCAmelCase     :					Dict,			_UpperCAmelCase     :					Dict,			**_UpperCAmelCase     :					Tuple						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Dict     =						{}
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						text_config
														SCREAMING_SNAKE_CASE__       :      List[str]     =						vision_config

														return cls.from_dict(_UpperCAmelCase,			**_UpperCAmelCase						)






							def  A_     ( self     :					Union[str, Any]						)				->			Tuple:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      str     =						copy.deepcopy(self.__dict__						)
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.text_config.to_dict()
														SCREAMING_SNAKE_CASE__       :      Any     =						self.vision_config.to_dict()
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						self.__class__.model_type
														return output


class 						lowerCamelCase       (__lowerCamelCase      ):







							"""simple docstring"""




							@property
							def  A_     ( self     :					Union[str, Any]						)				->			Mapping[str, Mapping[int, str]]:





														"""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     :					Any						)				->			Mapping[str, Mapping[int, 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     :					List[Any]						)				->			float:





														"""simple docstring"""
														return 1E-4






							def  A_     ( self     :					Optional[int],			_UpperCAmelCase     :					"ProcessorMixin",			_UpperCAmelCase     :					int = -1,			_UpperCAmelCase     :					int = -1,			_UpperCAmelCase     :					Optional["TensorType"] = None,			)				->			Mapping[str, Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						super().generate_dummy_inputs(
														    processor.tokenizer,			batch_size=_UpperCAmelCase,			seq_length=_UpperCAmelCase,			framework=_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						super().generate_dummy_inputs(
														    processor.image_processor,			batch_size=_UpperCAmelCase,			framework=_UpperCAmelCase						)
														return {**text_input_dict, **image_input_dict}






							@property
							def  A_     ( self     :					Dict						)				->			int:





														"""simple docstring"""
														return 1_4













class 						lowerCamelCase       :







							"""simple docstring"""




							def __init__( self     :					int,			_UpperCAmelCase     :					Dict,			_UpperCAmelCase     :					str						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      str     =						name
														SCREAMING_SNAKE_CASE__       :      Tuple     =						val






							def __str__( self     :					str						)				->			List[Any]:





														"""simple docstring"""
														return F'''{self.__class__.__name__}({self.name}, {self.val})'''






							def __lt__( self     :					str,			_UpperCAmelCase     :					Dict						)				->			Union[str, Any]:





														"""simple docstring"""
														return self.val < other.val


class 						lowerCamelCase       :







							"""simple docstring"""




							def __init__( self     :					Optional[Any],			_UpperCAmelCase     :					str						)				->			Tuple:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						{}
														SCREAMING_SNAKE_CASE__       :      str     =						{}
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						self.build_heap(_UpperCAmelCase						)






							def __getitem__( self     :					Union[str, Any],			_UpperCAmelCase     :					Any						)				->			Dict:





														"""simple docstring"""
														return self.get_value(_UpperCAmelCase						)






							def  A_     ( self     :					int,			_UpperCAmelCase     :					Optional[int]						)				->			Any:





														"""simple docstring"""
														return (idx - 1) // 2






							def  A_     ( self     :					Optional[Any],			_UpperCAmelCase     :					Any						)				->			Dict:





														"""simple docstring"""
														return idx * 2 + 1






							def  A_     ( self     :					str,			_UpperCAmelCase     :					List[str]						)				->			Union[str, Any]:





														"""simple docstring"""
														return idx * 2 + 2






							def  A_     ( self     :					Tuple,			_UpperCAmelCase     :					int						)				->			Optional[int]:





														"""simple docstring"""
														return self.heap_dict[key]






							def  A_     ( self     :					Optional[int],			_UpperCAmelCase     :					Dict						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      List[str]     =						len(_UpperCAmelCase						) - 1
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.get_parent_idx(_UpperCAmelCase						)

														for idx, i in enumerate(_UpperCAmelCase						):
																					SCREAMING_SNAKE_CASE__       :      Optional[int]     =						idx
																					SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						i.val

														for i in range(_UpperCAmelCase,			-1,			-1						):
																					self.sift_down(_UpperCAmelCase,			_UpperCAmelCase						)
														return array






							def  A_     ( self     :					List[Any],			_UpperCAmelCase     :					Dict,			_UpperCAmelCase     :					Tuple						)				->			Tuple:





														"""simple docstring"""
														while True:
																					SCREAMING_SNAKE_CASE__       :      str     =						self.get_left_child_idx(_UpperCAmelCase						)  # noqa: E741
																					SCREAMING_SNAKE_CASE__       :      Tuple     =						self.get_right_child_idx(_UpperCAmelCase						)

																					SCREAMING_SNAKE_CASE__       :      Tuple     =						idx
																					if l < len(_UpperCAmelCase						) and array[l] < array[idx]:
																												SCREAMING_SNAKE_CASE__       :      List[Any]     =						l
																					if r < len(_UpperCAmelCase						) and array[r] < array[smallest]:
																												SCREAMING_SNAKE_CASE__       :      int     =						r

																					if smallest != idx:
																												SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Any     =						array[smallest], array[idx]
																												(
																												    (
																												    SCREAMING_SNAKE_CASE__
																												)   ,(
																												    SCREAMING_SNAKE_CASE__
																												)   ,
																												)       :      Optional[Any]     =						(
																												    self.idx_of_element[array[smallest]],
																												    self.idx_of_element[array[idx]],
																												)
																												SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						smallest
																					else:
																												break






							def  A_     ( self     :					Union[str, Any],			_UpperCAmelCase     :					str						)				->			Any:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Any     =						self.get_parent_idx(_UpperCAmelCase						)
														while p >= 0 and self.heap[p] > self.heap[idx]:
																					SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Any     =						self.heap[idx], self.heap[p]
																					SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      int     =						(
																					    self.idx_of_element[self.heap[idx]],
																					    self.idx_of_element[self.heap[p]],
																					)
																					SCREAMING_SNAKE_CASE__       :      Dict     =						p
																					SCREAMING_SNAKE_CASE__       :      List[str]     =						self.get_parent_idx(_UpperCAmelCase						)






							def  A_     ( self     :					str						)				->			List[str]:





														"""simple docstring"""
														return self.heap[0]






							def  A_     ( self     :					Tuple						)				->			List[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.heap[-1], self.heap[0]
														SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      List[Any]     =						(
														    self.idx_of_element[self.heap[-1]],
														    self.idx_of_element[self.heap[0]],
														)

														SCREAMING_SNAKE_CASE__       :      Any     =						self.heap.pop()
														del self.idx_of_element[x]
														self.sift_down(0,			self.heap						)
														return x






							def  A_     ( self     :					Union[str, Any],			_UpperCAmelCase     :					str						)				->			Optional[Any]:





														"""simple docstring"""
														self.heap.append(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      str     =						len(self.heap						) - 1
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						node.val
														self.sift_up(len(self.heap						) - 1						)






							def  A_     ( self     :					Optional[int]						)				->			int:





														"""simple docstring"""
														return len(self.heap						) == 0






							def  A_     ( self     :					Any,			_UpperCAmelCase     :					Tuple,			_UpperCAmelCase     :					str						)				->			Dict:





														"""simple docstring"""
														assert (
														    self.heap[self.idx_of_element[node]].val > new_value
														), "newValue must be less that current value"
														SCREAMING_SNAKE_CASE__       :      Tuple     =						new_value
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						new_value
														self.sift_up(self.idx_of_element[node]						)


_lowerCamelCase :    Tuple  							= Node('''R''', -1)
_lowerCamelCase :    int  							= Node('''B''', 6)
_lowerCamelCase :    str  							= Node('''A''', 3)
_lowerCamelCase :    Optional[Any]  							= Node('''X''', 1)
_lowerCamelCase :    str  							= Node('''E''', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
_lowerCamelCase :    int  							= MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('''Min Heap - before decrease key''')
for i in my_min_heap.heap:
		print(i)

print('''Min Heap - After decrease key of node [B -> -17]''')
my_min_heap.decrease_key(b, -1_7)

# After
for i in my_min_heap.heap:
		print(i)

if __name__ == "__main__":
		import doctest

		doctest.testmod()






