% &hpdZddlmZddlmZddlmZmZeje Z GddeZ dgZ y) zLlava model configuration)PretrainedConfig)logging)CONFIG_MAPPING AutoConfigcFeZdZdZdZeedZdZ dfd ZxZ S) LlavaConfigaI This is the configuration class to store the configuration of a [`LlavaForConditionalGeneration`]. It is used to instantiate an Llava model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the Llava-9B. e.g. [llava-hf/llava-9b](https://huggingface.co/llava-hf/llava-9b) Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: vision_config (`Union[AutoConfig, dict]`, *optional*, defaults to `CLIPVisionConfig`): The config object or dictionary of the vision backbone. text_config (`Union[AutoConfig, dict]`, *optional*, defaults to `LlamaConfig`): The config object or dictionary of the text backbone. image_token_index (`int`, *optional*, defaults to 32000): The image token index to encode the image prompt. projector_hidden_act (`str`, *optional*, defaults to `"gelu"`): The activation function used by the multimodal projector. vision_feature_select_strategy (`str`, *optional*, defaults to `"default"`): The feature selection strategy used to select the vision feature from the vision backbone. Can be one of `"default"` or `"full"`. vision_feature_layer (`Union[int, List[int]]`, *optional*, defaults to -2): The index of the layer to select the vision feature. If multiple indices are provided, the vision feature of the corresponding indices will be concatenated to form the vision features. image_seq_length (`int`, *optional*, defaults to 576): Sequence length of one image embedding. multimodal_projector_bias (`bool`, *optional*, defaults to `True`): Whether to use bias in the multimodal projector. Example: ```python >>> from transformers import LlavaForConditionalGeneration, LlavaConfig, CLIPVisionConfig, LlamaConfig >>> # Initializing a CLIP-vision config >>> vision_config = CLIPVisionConfig() >>> # Initializing a Llama config >>> text_config = LlamaConfig() >>> # Initializing a Llava llava-1.5-7b style configuration >>> configuration = LlavaConfig(vision_config, text_config) >>> # Initializing a model from the llava-1.5-7b style configuration >>> model = LlavaForConditionalGeneration(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```llava) text_config vision_configTc ||_||_||_|dvrtd|||_||_t |tr d|vr|dnd|d<t|ddi|}n|tdddddd d d d }||_ t |tr d|vr|dnd|d<t|ddi|}n| td}||_ ||_ t |4di| y)N)defaultfullzGvision_feature_select_strategy should be one of 'default', 'full'.Got: model_typeclip_vision_modeliiiP}i)intermediate_size hidden_size patch_size image_sizenum_hidden_layersnum_attention_heads vocab_sizeprojection_dimllama)image_token_indexprojector_hidden_actimage_seq_length ValueErrorvision_feature_select_strategyvision_feature_layer isinstancedictrr r multimodal_projector_biassuper__init__) selfr r r r!r$r%r"r(kwargs __class__s /var/www/pru.catia.catastroantioquia-mas.com/valormas/lib/python3.12/site-packages/transformers/models/llava/configuration_llava.pyr*zLlavaConfig.__init__Qs;"3$8! 0 )1D D679  /M+$8! mT */;}/L l+Re , '+=+FGX-XM  "*+>?"& "$$& " M+ k4 (EQU`E` L(AfmK %(\)BCRkRK  (13K&)B& "6")NNrgeluri@T) __name__ __module__ __qualname____doc__rr sub_configsis_compositionr* __classcell__)r-s@r.r r sC2 hJ",zJKN#'0"&5#5#r/r N) r5configuration_utilsrutilsrautorr get_loggerr2loggerr __all__rr/r.r?s@ 3-   H %n#"n#b /r/