



'''simple docstring'''




import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowerCamelCase							:int       =						logging.get_logger(__name__)

lowerCamelCase							:Tuple       =						{
    '''Salesforce/instruct-blip-flan-t5''': '''https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json''',
}







class      _lowerCAmelCase							(      __UpperCAmelCase			):
	__SCREAMING_SNAKE_CASE       :		Optional[int]		      = 'instructblip_vision_model'


	def __init__(self	,				lowercase=1408	,				lowercase=6144	,				lowercase=39	,				lowercase=16	,				lowercase=224	,				lowercase=14	,				lowercase="gelu"	,				lowercase=1E-6	,				lowercase=0.0	,				lowercase=1E-10	,				lowercase=True	,				**lowercase	,				):
				super().__init__(**lowercase							)

				A_     :						Tuple     =					hidden_size
				A_     :						Any     =					intermediate_size
				A_     :						List[str]     =					num_hidden_layers
				A_     :						str     =					num_attention_heads
				A_     :						str     =					patch_size
				A_     :						Dict     =					image_size
				A_     :						Optional[Any]     =					initializer_range
				A_     :						str     =					attention_dropout
				A_     :						Optional[int]     =					layer_norm_eps
				A_     :						Union[str, Any]     =					hidden_act
				A_     :						int     =					qkv_bias


	@classmethod
	def    _a     (cls	,				lowercase	,				**lowercase							):
				cls._set_token_in_kwargs(lowercase							)

				A_     :						Optional[int]     =					cls.get_config_dict(lowercase	,				**lowercase							)

				# get the vision config dict if we are loading from InstructBlipConfig
				if config_dict.get("""model_type"""							) == "instructblip":
							A_     :						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(lowercase	,				**lowercase							)







class      _lowerCAmelCase							(      __UpperCAmelCase			):
	__SCREAMING_SNAKE_CASE       :		Union[str, Any]		      = 'instructblip_qformer'


	def __init__(self	,				lowercase=30522	,				lowercase=768	,				lowercase=12	,				lowercase=12	,				lowercase=3072	,				lowercase="gelu"	,				lowercase=0.1	,				lowercase=0.1	,				lowercase=512	,				lowercase=0.02	,				lowercase=1E-12	,				lowercase=0	,				lowercase="absolute"	,				lowercase=2	,				lowercase=1408	,				**lowercase	,				):
				super().__init__(pad_token_id=lowercase	,				**lowercase							)

				A_     :						Dict     =					vocab_size
				A_     :						Optional[int]     =					hidden_size
				A_     :						Dict     =					num_hidden_layers
				A_     :						Dict     =					num_attention_heads
				A_     :						int     =					hidden_act
				A_     :						List[str]     =					intermediate_size
				A_     :						Union[str, Any]     =					hidden_dropout_prob
				A_     :						Tuple     =					attention_probs_dropout_prob
				A_     :						str     =					max_position_embeddings
				A_     :						int     =					initializer_range
				A_     :						Tuple     =					layer_norm_eps
				A_     :						Optional[Any]     =					position_embedding_type
				A_     :						Tuple     =					cross_attention_frequency
				A_     :						Union[str, Any]     =					encoder_hidden_size


	@classmethod
	def    _a     (cls	,				lowercase	,				**lowercase							):
				cls._set_token_in_kwargs(lowercase							)

				A_     :						Optional[Any]     =					cls.get_config_dict(lowercase	,				**lowercase							)

				# get the qformer config dict if we are loading from InstructBlipConfig
				if config_dict.get("""model_type"""							) == "instructblip":
							A_     :						Union[str, Any]     =					config_dict["""qformer_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      _lowerCAmelCase							(      __UpperCAmelCase			):
	__SCREAMING_SNAKE_CASE       :		Optional[int]		      = 'instructblip'
	__SCREAMING_SNAKE_CASE       :		Optional[int]		      = True


	def __init__(self	,				lowercase=None	,				lowercase=None	,				lowercase=None	,				lowercase=32	,				**lowercase							):
				super().__init__(**lowercase							)

				if vision_config is None:
							A_     :						Tuple     =					{}
							logger.info("""vision_config is None. initializing the InstructBlipVisionConfig with default values."""							)

				if qformer_config is None:
							A_     :						Tuple     =					{}
							logger.info("""qformer_config is None. Initializing the InstructBlipQFormerConfig with default values."""							)

				if text_config is None:
							A_     :						str     =					{}
							logger.info("""text_config is None. Initializing the text config with default values (`OPTConfig`)."""							)

				A_     :						List[Any]     =					InstructBlipVisionConfig(**lowercase							)
				A_     :						Optional[int]     =					InstructBlipQFormerConfig(**lowercase							)
				A_     :						Union[str, Any]     =					text_config["""model_type"""] if """model_type""" in text_config else """opt"""
				A_     :						Any     =					CONFIG_MAPPING[text_model_type](**lowercase							)

				A_     :						int     =					self.text_config.tie_word_embeddings
				A_     :						List[str]     =					self.text_config.is_encoder_decoder

				A_     :						Dict     =					num_query_tokens
				A_     :						Any     =					self.vision_config.hidden_size
				A_     :						str     =					self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
				A_     :						Any     =					1.0
				A_     :						Any     =					0.02


	@classmethod
	def    _a     (cls	,				lowercase	,				lowercase	,				lowercase	,				**lowercase	,				):
				return cls(
				    vision_config=vision_config.to_dict()	,				qformer_config=qformer_config.to_dict()	,				text_config=text_config.to_dict()	,				**lowercase	,				)


	def    _a     (self							):
				A_     :						List[Any]     =					copy.deepcopy(self.__dict__							)
				A_     :						str     =					self.vision_config.to_dict()
				A_     :						Optional[Any]     =					self.qformer_config.to_dict()
				A_     :						List[str]     =					self.text_config.to_dict()
				A_     :						List[Any]     =					self.__class__.model_type
				return output




'''simple docstring'''




lowerCamelCase							:Any       = {
    '''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
    '''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',
    '''O''': '''---''', '''P''': '''.--.''', '''Q''': '''--.-''', '''R''': '''.-.''', '''S''': '''...''', '''T''': '''-''', '''U''': '''..-''',
    '''V''': '''...-''', '''W''': '''.--''', '''X''': '''-..-''', '''Y''': '''-.--''', '''Z''': '''--..''', '''1''': '''.----''',
    '''2''': '''..---''', '''3''': '''...--''', '''4''': '''....-''', '''5''': '''.....''', '''6''': '''-....''', '''7''': '''--...''',
    '''8''': '''---..''', '''9''': '''----.''', '''0''': '''-----''', '''&''': '''.-...''', '''@''': '''.--.-.''',
    ''':''': '''---...''', ''',''': '''--..--''', '''.''': '''.-.-.-''', '''\'''': '''.----.''', '''"''': '''.-..-.''',
    '''?''': '''..--..''', '''/''': '''-..-.''', '''=''': '''-...-''', '''+''': '''.-.-.''', '''-''': '''-....-''',
    '''(''': '''-.--.''', ''')''': '''-.--.-''', '''!''': '''-.-.--''', ''' ''': '''/'''
}  # Exclamation mark is not in ITU-R recommendation
# fmt: on
lowerCamelCase							:Any       = {value: key for key, value in MORSE_CODE_DICT.items()}



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			return " ".join(MORSE_CODE_DICT[char] for char in message.upper()   )



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			return "".join(REVERSE_DICT[char] for char in message.split()   )



def      a      (			):
			'''simple docstring'''





			A_     :						List[str]     =					"""Morse code here!"""
			print(lowerCamelCase__   )
			A_     :						str     =					encrypt(lowerCamelCase__   )
			print(lowerCamelCase__   )
			A_     :						Dict     =					decrypt(lowerCamelCase__   )
			print(lowerCamelCase__   )


if __name__ == "__main__":
						main()