






'''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


lowerCAmelCase__          =						logging.get_logger(__name__)

lowerCAmelCase__          =						{
    '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					(__lowerCamelCase    ):
	_lowerCamelCase              =  '''owlvit_text_model'''

	def __init__(      self   :						Tuple  ,					UpperCAmelCase_   :						Any=49_408  ,					UpperCAmelCase_   :						Union[str, Any]=512  ,					UpperCAmelCase_   :						int=2_048  ,					UpperCAmelCase_   :						List[Any]=12  ,					UpperCAmelCase_   :						Any=8  ,					UpperCAmelCase_   :						List[str]=16  ,					UpperCAmelCase_   :						Dict="quick_gelu"  ,					UpperCAmelCase_   :						Optional[int]=1e-5  ,					UpperCAmelCase_   :						Optional[Any]=0.0  ,					UpperCAmelCase_   :						Tuple=0.02  ,					UpperCAmelCase_   :						Tuple=1.0  ,					UpperCAmelCase_   :						List[Any]=0  ,					UpperCAmelCase_   :						Dict=49_406  ,					UpperCAmelCase_   :						str=49_407  ,					**UpperCAmelCase_   :						List[str]  ,					):
			super().__init__(pad_token_id=UpperCAmelCase_  ,					bos_token_id=UpperCAmelCase_  ,					eos_token_id=UpperCAmelCase_  ,					**UpperCAmelCase_)

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





	@classmethod
	def      __UpperCamelCase							(      cls   :						List[Any]  ,					UpperCAmelCase_   :						Optional[int]  ,					**UpperCAmelCase_   :						Tuple):
			cls._set_token_in_kwargs(UpperCAmelCase_)

			UpperCamelCase__,	UpperCamelCase__				:					Dict					=					cls.get_config_dict(UpperCAmelCase_  ,					**UpperCAmelCase_)

			# get the text config dict if we are loading from OwlViTConfig
			if config_dict.get('model_type') == "owlvit":
					UpperCamelCase__				:					str					=					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       __lowercase					(__lowerCamelCase    ):
	_lowerCamelCase              =  '''owlvit_vision_model'''

	def __init__(      self   :						List[Any]  ,					UpperCAmelCase_   :						Tuple=768  ,					UpperCAmelCase_   :						int=3_072  ,					UpperCAmelCase_   :						Optional[int]=12  ,					UpperCAmelCase_   :						List[Any]=12  ,					UpperCAmelCase_   :						Any=3  ,					UpperCAmelCase_   :						List[str]=768  ,					UpperCAmelCase_   :						Optional[Any]=32  ,					UpperCAmelCase_   :						Tuple="quick_gelu"  ,					UpperCAmelCase_   :						List[str]=1e-5  ,					UpperCAmelCase_   :						List[str]=0.0  ,					UpperCAmelCase_   :						Tuple=0.02  ,					UpperCAmelCase_   :						Optional[int]=1.0  ,					**UpperCAmelCase_   :						Union[str, Any]  ,					):
			super().__init__(**UpperCAmelCase_)

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





	@classmethod
	def      __UpperCamelCase							(      cls   :						Union[str, Any]  ,					UpperCAmelCase_   :						List[Any]  ,					**UpperCAmelCase_   :						List[str]):
			cls._set_token_in_kwargs(UpperCAmelCase_)

			UpperCamelCase__,	UpperCamelCase__				:					Tuple					=					cls.get_config_dict(UpperCAmelCase_  ,					**UpperCAmelCase_)

			# get the vision config dict if we are loading from OwlViTConfig
			if config_dict.get('model_type') == "owlvit":
					UpperCamelCase__				:					Optional[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       __lowercase					(__lowerCamelCase    ):
	_lowerCamelCase              =  '''owlvit'''
	_lowerCamelCase              =  True

	def __init__(      self   :						Tuple  ,					UpperCAmelCase_   :						Any=None  ,					UpperCAmelCase_   :						Optional[Any]=None  ,					UpperCAmelCase_   :						List[Any]=512  ,					UpperCAmelCase_   :						Union[str, Any]=2.65_92  ,					UpperCAmelCase_   :						Tuple=True  ,					**UpperCAmelCase_   :						Any  ,					):
			super().__init__(**UpperCAmelCase_)

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

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

			UpperCamelCase__				:					int					=					OwlViTTextConfig(**UpperCAmelCase_)
			UpperCamelCase__				:					Union[str, Any]					=					OwlViTVisionConfig(**UpperCAmelCase_)

			UpperCamelCase__				:					Tuple					=					projection_dim
			UpperCamelCase__				:					Optional[int]					=					logit_scale_init_value
			UpperCamelCase__				:					Optional[Any]					=					return_dict
			UpperCamelCase__				:					int					=					1.0

	@classmethod
	def      __UpperCamelCase							(      cls   :						Optional[int]  ,					UpperCAmelCase_   :						Tuple  ,					**UpperCAmelCase_   :						Optional[int]):
			cls._set_token_in_kwargs(UpperCAmelCase_)

			UpperCamelCase__,	UpperCamelCase__				:					List[str]					=					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      __UpperCamelCase							(      cls   :						List[str]  ,					UpperCAmelCase_   :						Tuple  ,					UpperCAmelCase_   :						int  ,					**UpperCAmelCase_   :						Union[str, Any]):
			UpperCamelCase__				:					Optional[Any]					=					{}
			UpperCamelCase__				:					Union[str, Any]					=					text_config
			UpperCamelCase__				:					List[str]					=					vision_config

			return cls.from_dict(UpperCAmelCase_  ,					**UpperCAmelCase_)





	def      __UpperCamelCase							(      self   :						Optional[int]):
			UpperCamelCase__				:					Any					=					copy.deepcopy(self.__dict__)
			UpperCamelCase__				:					Union[str, Any]					=					self.text_config.to_dict()
			UpperCamelCase__				:					str					=					self.vision_config.to_dict()
			UpperCamelCase__				:					Union[str, Any]					=					self.__class__.model_type
			return output







class       __lowercase					(__lowerCamelCase    ):

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

	@property
	def      __UpperCamelCase							(      self   :						Optional[int]):
			return 1e-4

	def      __UpperCamelCase							(      self   :						List[Any]  ,					UpperCAmelCase_   :						Optional[int]  ,					UpperCAmelCase_   :						List[Any] = -1  ,					UpperCAmelCase_   :						List[str] = -1  ,					UpperCAmelCase_   :						Optional[Any] = None  ,					):
			UpperCamelCase__				:					int					=					super().generate_dummy_inputs(
			    processor.tokenizer  ,					batch_size=UpperCAmelCase_  ,					seq_length=UpperCAmelCase_  ,					framework=UpperCAmelCase_)
			UpperCamelCase__				:					List[str]					=					super().generate_dummy_inputs(
			    processor.image_processor  ,					batch_size=UpperCAmelCase_  ,					framework=UpperCAmelCase_)
			return {**text_input_dict, **image_input_dict}





	@property
	def      __UpperCamelCase							(      self   :						Dict):
			return 14







'''simple docstring'''




class       __lowercase					:

	def __init__(      self   :						List[str]  ,					UpperCAmelCase_   :						str = ""  ,					UpperCAmelCase_   :						bool = False):
			# Mapping from the first character of the prefix of the node
			UpperCamelCase__				:					dict[str, RadixNode]					=					{}

			# A node will be a leaf if the tree contains its word
			UpperCamelCase__				:					List[Any]					=					is_leaf

			UpperCamelCase__				:					Optional[Any]					=					prefix

	def      __UpperCamelCase							(      self   :						List[Any]  ,					UpperCAmelCase_   :						str):
			UpperCamelCase__				:					Optional[int]					=					0
			for q, w in zip(self.prefix  ,					UpperCAmelCase_):
					if q != w:
							break

					x += 1

			return self.prefix[:x], self.prefix[x:], word[x:]

	def      __UpperCamelCase							(      self   :						str  ,					UpperCAmelCase_   :						list[str]):
			for word in words:
					self.insert(UpperCAmelCase_)

	def      __UpperCamelCase							(      self   :						Optional[int]  ,					UpperCAmelCase_   :						str):
			# Case 1: If the word is the prefix of the node
			# Solution: We set the current node as leaf
			if self.prefix == word:
					UpperCamelCase__				:					Optional[Any]					=					True

			# Case 2: The node has no edges that have a prefix to the word
			# Solution: We create an edge from the current node to a new one
			# containing the word
			elif word[0] not in self.nodes:
					UpperCamelCase__				:					Optional[Any]					=					RadixNode(prefix=UpperCAmelCase_  ,					is_leaf=UpperCAmelCase_)

			else:
					UpperCamelCase__				:					int					=					self.nodes[word[0]]
					UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__				:					List[Any]					=					incoming_node.match(
					    UpperCAmelCase_)

					# Case 3: The node prefix is equal to the matching
					# Solution: We insert remaining word on the next node
					if remaining_prefix == "":
							self.nodes[matching_string[0]].insert(UpperCAmelCase_)

					# Case 4: The word is greater equal to the matching
					# Solution: Create a node in between both nodes, change
					# prefixes and add the new node for the remaining word
					else:
							UpperCamelCase__				:					Tuple					=					remaining_prefix

							UpperCamelCase__				:					str					=					self.nodes[matching_string[0]]
							UpperCamelCase__				:					Optional[Any]					=					RadixNode(UpperCAmelCase_  ,					UpperCAmelCase_)
							UpperCamelCase__				:					str					=					aux_node

							if remaining_word == "":
									UpperCamelCase__				:					int					=					True
							else:
									self.nodes[matching_string[0]].insert(UpperCAmelCase_)

	def      __UpperCamelCase							(      self   :						Union[str, Any]  ,					UpperCAmelCase_   :						str):
			UpperCamelCase__				:					Optional[Any]					=					self.nodes.get(word[0]  ,					UpperCAmelCase_)
			if not incoming_node:
					return False
			else:
					UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__				:					int					=					incoming_node.match(
					    UpperCAmelCase_)
					# If there is remaining prefix, the word can't be on the tree
					if remaining_prefix != "":
							return False
					# This applies when the word and the prefix are equal
					elif remaining_word == "":
							return incoming_node.is_leaf
					# We have word remaining so we check the next node
					else:
							return incoming_node.find(UpperCAmelCase_)

	def      __UpperCamelCase							(      self   :						str  ,					UpperCAmelCase_   :						str):
			UpperCamelCase__				:					Optional[int]					=					self.nodes.get(word[0]  ,					UpperCAmelCase_)
			if not incoming_node:
					return False
			else:
					UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__				:					Union[str, Any]					=					incoming_node.match(
					    UpperCAmelCase_)
					# If there is remaining prefix, the word can't be on the tree
					if remaining_prefix != "":
							return False
					# We have word remaining so we check the next node
					elif remaining_word != "":
							return incoming_node.delete(UpperCAmelCase_)
					else:
							# If it is not a leaf, we don't have to delete
							if not incoming_node.is_leaf:
									return False
							else:
									# We delete the nodes if no edges go from it
									if len(incoming_node.nodes) == 0:
											del self.nodes[word[0]]
											# We merge the current node with its only child
											if len(self.nodes) == 1 and not self.is_leaf:
													UpperCamelCase__				:					List[str]					=					list(self.nodes.values())[0]
													UpperCamelCase__				:					Tuple					=					merging_node.is_leaf
													self.prefix += merging_node.prefix
													UpperCamelCase__				:					Tuple					=					merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
									elif len(incoming_node.nodes) > 1:
											UpperCamelCase__				:					str					=					False
									# If there is 1 edge, we merge it with its child
									else:
											UpperCamelCase__				:					List[Any]					=					list(incoming_node.nodes.values())[0]
											UpperCamelCase__				:					Optional[Any]					=					merging_node.is_leaf
											incoming_node.prefix += merging_node.prefix
											UpperCamelCase__				:					Union[str, Any]					=					merging_node.nodes

									return True





	def      __UpperCamelCase							(      self   :						str  ,					UpperCAmelCase_   :						int = 0):
			if self.prefix != "":
					print('-' * height  ,					self.prefix  ,					'  (leaf)' if self.is_leaf else '')

			for value in self.nodes.values():
					value.print_tree(height + 1)







def       __UpperCAmelCase						(  )							->     bool:
		UpperCamelCase__				:					Union[str, Any]					=					'banana bananas bandana band apple all beast'.split()
		UpperCamelCase__				:					List[Any]					=					RadixNode()
		root.insert_many(lowerCamelCase_)

		assert all(root.find(lowerCamelCase_) for word in words)
		assert not root.find('bandanas')
		assert not root.find('apps')
		root.delete('all')
		assert not root.find('all')
		root.delete('banana')
		assert not root.find('banana')
		assert root.find('bananas')

		return True







def       __UpperCAmelCase						(  )							->     None:
		assert test_trie()







def       __UpperCAmelCase						(  )							->     None:
		UpperCamelCase__				:					List[Any]					=					RadixNode()
		UpperCamelCase__				:					List[str]					=					'banana bananas bandanas bandana band apple all beast'.split()
		root.insert_many(lowerCamelCase_)

		print('Words:'     ,      lowerCamelCase_)
		print('Tree:')
		root.print_tree()


if __name__ == "__main__":
		main()




