





import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_									=       logging.get_logger(__name__)

UpperCAmelCase_									=       {
    'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/blip-vqa-base/resolve/main/config.json',
    'Salesforce/blip-vqa-capfit-large': (
        'https://huggingface.co/Salesforce/blip-vqa-base-capfit/resolve/main/config.json'
    ),
    'Salesforce/blip-image-captioning-base': (
        'https://huggingface.co/Salesforce/blip-image-captioning-base/resolve/main/config.json'
    ),
    'Salesforce/blip-image-captioning-large': (
        'https://huggingface.co/Salesforce/blip-image-captioning-large/resolve/main/config.json'
    ),
    'Salesforce/blip-itm-base-coco': 'https://huggingface.co/Salesforce/blip-itm-base-coco/resolve/main/config.json',
    'Salesforce/blip-itm-large-coco': 'https://huggingface.co/Salesforce/blip-itm-large-coco/resolve/main/config.json',
    'Salesforce/blip-itm-base-flikr': 'https://huggingface.co/Salesforce/blip-itm-base-flikr/resolve/main/config.json',
    'Salesforce/blip-itm-large-flikr': (
        'https://huggingface.co/Salesforce/blip-itm-large-flikr/resolve/main/config.json'
    ),
}
class      UpperCamelCase_						(					lowerCamelCase__   ):
					lowerCAmelCase_							=		'''blip_text_model'''




					def __init__(						self			,  lowerCAmelCase_=3_0524			,  lowerCAmelCase_=768			,  lowerCAmelCase_=768			,  lowerCAmelCase_=3072			,  lowerCAmelCase_=768			,  lowerCAmelCase_=12			,  lowerCAmelCase_=8			,  lowerCAmelCase_=512			,  lowerCAmelCase_="gelu"			,  lowerCAmelCase_=1E-12			,  lowerCAmelCase_=0.0			,  lowerCAmelCase_=0.0			,  lowerCAmelCase_=0.02			,  lowerCAmelCase_=3_0522			,  lowerCAmelCase_=2			,  lowerCAmelCase_=0			,  lowerCAmelCase_=102			,  lowerCAmelCase_=True			,  lowerCAmelCase_=True			,  **lowerCAmelCase_			,  )						->							Any:
										super().__init__(
										    pad_token_id=__snake_case			,  bos_token_id=__snake_case			,  eos_token_id=__snake_case			,  sep_token_id=__snake_case			,  **__snake_case			,  )

										_snake_case													=			vocab_size
										_snake_case													=			hidden_size
										_snake_case													=			encoder_hidden_size
										_snake_case													=			intermediate_size
										_snake_case													=			projection_dim
										_snake_case													=			hidden_dropout_prob
										_snake_case													=			num_hidden_layers
										_snake_case													=			num_attention_heads
										_snake_case													=			max_position_embeddings
										_snake_case													=			layer_norm_eps
										_snake_case													=			hidden_act
										_snake_case													=			initializer_range
										_snake_case													=			attention_probs_dropout_prob
										_snake_case													=			is_decoder
										_snake_case													=			use_cache






					@classmethod
					def 		lowerCAmelCase     (						cls			,  lowerCAmelCase_			,  **lowerCAmelCase_					)						->							Optional[int]:
										cls._set_token_in_kwargs(__snake_case					)

										_snake_case													=			cls.get_config_dict(__snake_case			,  **__snake_case					)

										# get the text config dict if we are loading from BlipConfig
										if config_dict.get('model_type'					) == "blip":
															_snake_case													=			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(__snake_case			,  **__snake_case					)





class      UpperCamelCase_						(					lowerCamelCase__   ):
					lowerCAmelCase_							=		'''blip_vision_model'''




					def __init__(						self			,  lowerCAmelCase_=768			,  lowerCAmelCase_=3072			,  lowerCAmelCase_=512			,  lowerCAmelCase_=12			,  lowerCAmelCase_=12			,  lowerCAmelCase_=384			,  lowerCAmelCase_=16			,  lowerCAmelCase_="gelu"			,  lowerCAmelCase_=1E-5			,  lowerCAmelCase_=0.0			,  lowerCAmelCase_=1E-10			,  **lowerCAmelCase_			,  )						->							Union[str, Any]:
										super().__init__(**__snake_case					)

										_snake_case													=			hidden_size
										_snake_case													=			intermediate_size
										_snake_case													=			projection_dim
										_snake_case													=			num_hidden_layers
										_snake_case													=			num_attention_heads
										_snake_case													=			patch_size
										_snake_case													=			image_size
										_snake_case													=			initializer_range
										_snake_case													=			attention_dropout
										_snake_case													=			layer_norm_eps
										_snake_case													=			hidden_act






					@classmethod
					def 		lowerCAmelCase     (						cls			,  lowerCAmelCase_			,  **lowerCAmelCase_					)						->							List[Any]:
										cls._set_token_in_kwargs(__snake_case					)

										_snake_case													=			cls.get_config_dict(__snake_case			,  **__snake_case					)

										# get the vision config dict if we are loading from BlipConfig
										if config_dict.get('model_type'					) == "blip":
															_snake_case													=			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(__snake_case			,  **__snake_case					)





class      UpperCamelCase_						(					lowerCamelCase__   ):
					lowerCAmelCase_							=		'''blip'''
					lowerCAmelCase_							=		True




					def __init__(						self			,  lowerCAmelCase_=None			,  lowerCAmelCase_=None			,  lowerCAmelCase_=512			,  lowerCAmelCase_=2.65_92			,  lowerCAmelCase_=256			,  **lowerCAmelCase_			,  )						->							Optional[Any]:
										super().__init__(**__snake_case					)

										if text_config is None:
															_snake_case													=			{}
															logger.info('`text_config` is `None`. Initializing the `BlipTextConfig` with default values.'					)

										if vision_config is None:
															_snake_case													=			{}
															logger.info('`vision_config` is `None`. Initializing the `BlipVisionConfig` with default values.'					)

										_snake_case													=			BlipTextConfig(**__snake_case					)
										_snake_case													=			BlipVisionConfig(**__snake_case					)

										_snake_case													=			self.vision_config.hidden_size

										_snake_case													=			projection_dim
										_snake_case													=			logit_scale_init_value
										_snake_case													=			1.0
										_snake_case													=			0.02
										_snake_case													=			image_text_hidden_size




					@classmethod
					def 		lowerCAmelCase     (						cls			,  lowerCAmelCase_			,  lowerCAmelCase_			,  **lowerCAmelCase_					)						->							int:
										return cls(text_config=text_config.to_dict()			,  vision_config=vision_config.to_dict()			,  **__snake_case					)






					def 		lowerCAmelCase     (						self					)						->							Optional[int]:
										_snake_case													=			copy.deepcopy(self.__dict__					)
										_snake_case													=			self.text_config.to_dict()
										_snake_case													=			self.vision_config.to_dict()
										_snake_case													=			self.__class__.model_type
										return output










from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst





def   lowerCamelCase__       (       )     ->	List[str]:



					'''simple docstring'''




					_snake_case							,       _snake_case													=			9, 14  # noqa: F841
					_snake_case													=			[
					    [0, 1, 4],
					    [0, 7, 8],
					    [1, 2, 8],
					    [7, 8, 7],
					    [7, 6, 1],
					    [2, 8, 2],
					    [8, 6, 6],
					    [2, 3, 7],
					    [2, 5, 4],
					    [6, 5, 2],
					    [3, 5, 14],
					    [3, 4, 9],
					    [5, 4, 10],
					    [1, 7, 11],
					]

					_snake_case													=			defaultdict(UpperCamelCase__  )
					for nodea, nodea, cost in edges:
										adjancency[nodea].append([nodea, cost]  )
										adjancency[nodea].append([nodea, cost]  )

					_snake_case													=			mst(UpperCamelCase__  )

					_snake_case													=			[
					    [7, 6, 1],
					    [2, 8, 2],
					    [6, 5, 2],
					    [0, 1, 4],
					    [2, 5, 4],
					    [2, 3, 7],
					    [0, 7, 8],
					    [3, 4, 9],
					]

					for answer in expected:
										_snake_case													=			tuple(answer[:2]  )
										_snake_case													=			tuple(edge[::-1]  )
										assert edge in result or reverse in result



