o i@sLddlmZddlmZddlmZmZeeZ GdddeZ dgZ dS))PretrainedConfig)logging)CONFIG_MAPPING AutoConfigc s`eZdZdZdZddddZeedZ   ddedededede f fdd Z Z S)ShieldGemma2Configa This is the configuration class to store the configuration of a [`ShieldGemma2ForImageClassification`]. It is used to instantiate an ShieldGemma2ForImageClassification according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the shieldgemma-2-4b-it. e.g. [google/gemma-3-4b](https://huggingface.co/google/gemma-3-4b) Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: text_config (`Union[ShieldGemma2TextConfig, dict]`, *optional*): The config object of the text backbone. vision_config (`Union[AutoConfig, dict]`, *optional*): Custom vision config or dict. mm_tokens_per_image (`int`, *optional*, defaults to 256): The number of tokens per image embedding. boi_token_index (`int`, *optional*, defaults to 255999): The begin-of-image token index to wrap the image prompt. eoi_token_index (`int`, *optional*, defaults to 256000): The end-of-image token index to wrap the image prompt. image_token_index (`int`, *optional*, defaults to 262144): The image token index to encode the image prompt. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. Example: ```python >>> from transformers import ShieldGemma2ForConditionalGeneration, ShieldGemma2Config, SiglipVisionConfig, ShieldGemma2TextConfig >>> # Initializing a Siglip-like vision config >>> vision_config = SiglipVisionConfig() >>> # Initializing a ShieldGemma2 Text config >>> text_config = ShieldGemma2TextConfig() >>> # Initializing a ShieldGemma2 gemma-3-4b style configuration >>> configuration = ShieldGemma2Config(vision_config, text_config) >>> # Initializing a model from the gemma-3-4b style configuration >>> model = ShieldGemma2TextConfig(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` shieldgemma2image_token_indexboi_token_indexeoi_token_index)image_token_id boi_token_id eoi_token_id) text_config vision_configN{Gz?mm_tokens_per_imageinitializer_rangec  st|tr|dd|d<t|ddi|}n |dur"td}||_t|tr>|dd|d<t|ddi|}n |durGtd}||_||_||_||_||_||_ ||_ t j di|dS)N model_typesiglip_vision_model gemma3_text) isinstancedictgetrrrrr r r rsuper__init__) selfrrrr r r rkwargs __class__rx/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/transformers/models/shieldgemma2/configuration_shieldgemma2.pyr Rs&    zShieldGemma2Config.__init__)NNrrrrr) __name__ __module__ __qualname____doc__r attribute_mapr sub_configsintfloatr __classcell__rrr#r%rs40 rN) configuration_utilsrutilsrautorr get_loggerr&loggerr__all__rrrr%s    ]