


"""simple docstring"""


import copy
import os
from typing import Union

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


_snake_case          =							logging.get_logger(__name__)

_snake_case          =							{
    "BridgeTower/bridgetower-base": "https://huggingface.co/BridgeTower/bridgetower-base/blob/main/config.json",
    "BridgeTower/bridgetower-base-itm-mlm": (
        "https://huggingface.co/BridgeTower/bridgetower-base-itm-mlm/blob/main/config.json"
    ),
}



class   _a      (      snake_case__ ):
    a_    :				Optional[int]             =    'bridgetower_vision_model'
    def __init__( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					List[Any]=7_68							,					SCREAMING_SNAKE_CASE__							:					str=12							,					SCREAMING_SNAKE_CASE__							:					List[Any]=3							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=16							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=2_88							,					SCREAMING_SNAKE_CASE__							:					Any=1							,					SCREAMING_SNAKE_CASE__							:					Dict=1e-05							,					SCREAMING_SNAKE_CASE__							:					List[Any]=False							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=True							,					SCREAMING_SNAKE_CASE__							:					str=False							,					**SCREAMING_SNAKE_CASE__							:					Union[str, Any]							,					):
          super().__init__(**lowercase_				)
          lowerCamelCase__           =		hidden_size
          lowerCamelCase__           =		num_hidden_layers
          lowerCamelCase__           =		num_channels
          lowerCamelCase__           =		patch_size
          lowerCamelCase__           =		image_size
          lowerCamelCase__           =		initializer_factor
          lowerCamelCase__           =		layer_norm_eps
          lowerCamelCase__           =		stop_gradient
          lowerCamelCase__           =		share_layernorm
          lowerCamelCase__           =		remove_last_layer


    @classmethod
    def      _UpperCamelCase       ( cls							:					int							,					SCREAMING_SNAKE_CASE__							:					int							,					**SCREAMING_SNAKE_CASE__							:					Union[str, Any]				):
          lowerCamelCase__           =		cls.get_config_dict(lowercase_							,					**lowercase_				)

          if config_dict.get('model_type'				) == "bridgetower":
                lowerCamelCase__           =		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      (      snake_case__ ):
    a_    :				Tuple             =    'bridgetower_text_model'
    def __init__( self							:					Optional[Any]							,					SCREAMING_SNAKE_CASE__							:					Dict=5_02_65							,					SCREAMING_SNAKE_CASE__							:					List[Any]=7_68							,					SCREAMING_SNAKE_CASE__							:					Dict=12							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=12							,					SCREAMING_SNAKE_CASE__							:					List[Any]=1							,					SCREAMING_SNAKE_CASE__							:					Tuple=30_72							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]="gelu"							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=0.1							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=0.1							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=5_14							,					SCREAMING_SNAKE_CASE__							:					Dict=1							,					SCREAMING_SNAKE_CASE__							:					Dict=1e-05							,					SCREAMING_SNAKE_CASE__							:					str=1							,					SCREAMING_SNAKE_CASE__							:					int=0							,					SCREAMING_SNAKE_CASE__							:					Tuple=2							,					SCREAMING_SNAKE_CASE__							:					List[str]="absolute"							,					SCREAMING_SNAKE_CASE__							:					List[Any]=True							,					**SCREAMING_SNAKE_CASE__							:					Optional[int]							,					):
          super().__init__(**lowercase_				)

          lowerCamelCase__           =		vocab_size
          lowerCamelCase__           =		hidden_size
          lowerCamelCase__           =		num_hidden_layers
          lowerCamelCase__           =		num_attention_heads
          lowerCamelCase__           =		hidden_act
          lowerCamelCase__           =		initializer_factor
          lowerCamelCase__           =		intermediate_size
          lowerCamelCase__           =		hidden_dropout_prob
          lowerCamelCase__           =		attention_probs_dropout_prob
          lowerCamelCase__           =		max_position_embeddings
          lowerCamelCase__           =		type_vocab_size
          lowerCamelCase__           =		layer_norm_eps
          lowerCamelCase__           =		position_embedding_type
          lowerCamelCase__           =		use_cache
          lowerCamelCase__           =		pad_token_id
          lowerCamelCase__           =		bos_token_id
          lowerCamelCase__           =		eos_token_id


    @classmethod
    def      _UpperCamelCase       ( cls							:					str							,					SCREAMING_SNAKE_CASE__							:					Tuple							,					**SCREAMING_SNAKE_CASE__							:					Optional[Any]				):
          lowerCamelCase__           =		cls.get_config_dict(lowercase_							,					**lowercase_				)

          if config_dict.get('model_type'				) == "bridgetower":
                lowerCamelCase__           =		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      (      snake_case__ ):
    a_    :				int             =    'bridgetower'
    def __init__( self							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					Tuple=True							,					SCREAMING_SNAKE_CASE__							:					List[str]="gelu"							,					SCREAMING_SNAKE_CASE__							:					Dict=7_68							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]=1							,					SCREAMING_SNAKE_CASE__							:					Any=1e-05							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=False							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]="add"							,					SCREAMING_SNAKE_CASE__							:					Dict=12							,					SCREAMING_SNAKE_CASE__							:					List[str]=6							,					SCREAMING_SNAKE_CASE__							:					str=False							,					SCREAMING_SNAKE_CASE__							:					str=False							,					SCREAMING_SNAKE_CASE__							:					Tuple=None							,					SCREAMING_SNAKE_CASE__							:					str=None							,					**SCREAMING_SNAKE_CASE__							:					Any							,					):
          # TODO: remove this once the Hub files are updated.
          lowerCamelCase__           =		kwargs.pop('text_config_dict'							,					lowercase_				)
          lowerCamelCase__           =		kwargs.pop('vision_config_dict'							,					lowercase_				)

          super().__init__(**lowercase_				)
          lowerCamelCase__           =		share_cross_modal_transformer_layers
          lowerCamelCase__           =		hidden_act
          lowerCamelCase__           =		hidden_size
          lowerCamelCase__           =		initializer_factor
          lowerCamelCase__           =		layer_norm_eps
          lowerCamelCase__           =		share_link_tower_layers
          lowerCamelCase__           =		link_tower_type
          lowerCamelCase__           =		num_attention_heads
          lowerCamelCase__           =		num_hidden_layers
          lowerCamelCase__           =		tie_word_embeddings
          lowerCamelCase__           =		init_layernorm_from_vision_encoder

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

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

          lowerCamelCase__           =		BridgeTowerTextConfig(**lowercase_				)
          lowerCamelCase__           =		BridgeTowerVisionConfig(**lowercase_				)
    @classmethod
    def      _UpperCamelCase       ( cls							:					Dict							,					SCREAMING_SNAKE_CASE__							:					int							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]							,					**SCREAMING_SNAKE_CASE__							:					List[Any]				):
          return cls(text_config=text_config.to_dict()							,					vision_config=vision_config.to_dict()							,					**lowercase_				)


    def      _UpperCamelCase       ( self							:					List[str]				):
          lowerCamelCase__           =		copy.deepcopy(self.__dict__				)
          lowerCamelCase__           =		self.text_config.to_dict()
          lowerCamelCase__           =		self.vision_config.to_dict()
          lowerCamelCase__           =		self.__class__.model_type
          return output







"""simple docstring"""


from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import ShapEPipeline
else:
   from .camera import create_pan_cameras
   from .pipeline_shap_e import ShapEPipeline
   from .pipeline_shap_e_img2img import ShapEImgaImgPipeline
   from .renderer import (
       BoundingBoxVolume,
       ImportanceRaySampler,
       MLPNeRFModelOutput,
       MLPNeRSTFModel,
       ShapEParamsProjModel,
       ShapERenderer,
       StratifiedRaySampler,
       VoidNeRFModel,
   )



