# coding=utf-8 # Copyright 2025 Google Inc. HuggingFace Inc. team. All rights reserved. # # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING, AutoConfig logger = logging.get_logger(__name__) class ShieldGemma2Config(PretrainedConfig): r""" 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 ```""" model_type = "shieldgemma2" attribute_map = { "image_token_id": "image_token_index", "boi_token_id": "boi_token_index", "eoi_token_id": "eoi_token_index", } sub_configs = {"text_config": AutoConfig, "vision_config": AutoConfig} def __init__( self, text_config=None, vision_config=None, mm_tokens_per_image: int = 256, boi_token_index: int = 255_999, eoi_token_index: int = 256_000, image_token_index: int = 262_144, initializer_range: float = 0.02, **kwargs, ): if isinstance(vision_config, dict): vision_config["model_type"] = ( vision_config["model_type"] if "model_type" in vision_config else "siglip_vision_model" ) vision_config = CONFIG_MAPPING[vision_config["model_type"]](**vision_config) elif vision_config is None: vision_config = CONFIG_MAPPING["siglip_vision_model"]() self.vision_config = vision_config if isinstance(text_config, dict): text_config["model_type"] = text_config["model_type"] if "model_type" in text_config else "gemma3_text" text_config = CONFIG_MAPPING[text_config["model_type"]](**text_config) elif text_config is None: text_config = CONFIG_MAPPING["gemma3_text"]() self.text_config = text_config self.vision_config = vision_config self.mm_tokens_per_image = mm_tokens_per_image self.boi_token_index = boi_token_index self.eoi_token_index = eoi_token_index self.image_token_index = image_token_index self.initializer_range = initializer_range super().__init__(**kwargs) __all__ = ["ShieldGemma2Config"]