IgY$dZddlZddlmZddlmZddlmZddlm Z eje Z Gd d eZ Gd d eZy) zIdefics3 model configurationN)Union)PretrainedConfig)logging)CONFIG_MAPPINGcveZdZdZdZ dfd Zedeee jfddfdZ xZ S) Idefics3VisionConfiga This is the configuration class to store the configuration of a [`Idefics3VisionModel`]. It is used to instantiate a Idefics3 vision encoder according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the SigLIP checkpoint [google/siglip-base-patch16-224](https://huggingface.co/google/siglip-base-patch16-224) used in the Idefics3 model [HuggingFaceM4/Idefics3-8B-Llama3](https://huggingface.co/HuggingFaceM4/Idefics3-8B-Llama3). Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: hidden_size (`int`, *optional*, defaults to 1152): Dimensionality of the encoder layers and the pooler layer. intermediate_size (`int`, *optional*, defaults to 3072): Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. num_hidden_layers (`int`, *optional*, defaults to 12): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 16): Number of attention heads for each attention layer in the Transformer encoder. num_channels (`int`, *optional*, defaults to 3): Number of channels in the input images. image_size (`int`, *optional*, defaults to 224): The size (resolution) of each image. patch_size (`int`, *optional*, defaults to 32): The size (resolution) of each patch. hidden_act (`str` or `function`, *optional*, defaults to `"gelu_pytorch_tanh"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` `"quick_gelu"` are supported. layer_norm_eps (`float`, *optional*, defaults to 1e-06): The epsilon used by the layer normalization layers. attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. intializer_range (`float`, *optional*, defaults to 0.02): The standard deviation for initializing all weight matrices in the model. Example: ```python >>> from transformers.models.idefics3.modeling_idefics3 import Idefics3VisionTransformer >>> from transformers.models.idefics3.configuration_idefics3 import Idefics3VisionConfig >>> # Initializing a Idefics3VisionConfig with google/siglip-base-patch16-224 style configuration >>> configuration = Idefics3VisionConfig() >>> # Initializing a Idefics3VisionTransformer (with random weights) from the google/siglip-base-patch16-224 style configuration >>> model = Idefics3VisionTransformer(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```idefics3c  t |di| ||_||_||_||_||_||_||_| |_ | |_ ||_ | |_ y)N) super__init__ hidden_sizeintermediate_sizenum_hidden_layersnum_attention_heads num_channels patch_size image_sizeattention_dropoutlayer_norm_eps hidden_actinitializer_range)selfrrrrrrrrrrrkwargs __class__s p/var/www/html/answerous/venv/lib/python3.12/site-packages/transformers/models/idefics3/configuration_idefics3.pyrzIdefics3VisionConfig.__init__Qsj "6"&!2!2#6 ($$!2,$!2pretrained_model_name_or_pathreturnrc >|j||j|fi|\}}|jddk(r|d}d|vrGt|dr;|d|jk7r)t j d|dd|jd|j|fi|S)N model_typer vision_configzYou are using a model of type z to instantiate a model of type zN. This is not supported for all configurations of models and can yield errors.)_set_token_in_kwargsget_config_dictgethasattrr#loggerwarning from_dict)clsr r config_dicts rfrom_pretrainedz$Idefics3VisionConfig.from_pretrainedns   (1c112OZSYZ V ??< (J 6%o6K ; &73 +E+VbJcgjguguJu NN0\1J0KKk>>""pr  s}}[3F33r) ii r gelu_pytorch_tanhgư>gg{Gz?) __name__ __module__ __qualname____doc__r#r classmethodrstrosPathLiker. __classcell__rs@rr r si1 fJ&3:4E#r{{BR>> from transformers import Idefics3Model, Idefics3Config >>> # Initializing configuration >>> configuration = Idefics3Config() >>> # Initializing a model from the configuration >>> model = Idefics3Model(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```r Tc ||_||_||_|%t|_t j dn8t|trtd i||_nt|tr||_t|tr d|vr|dnd|d<t|dd i|}n(|&t j dtdd|d}||_ ||_ t |4d i|d|iy) Nz2vision_config is None, using default vision configr#llamaz.text_config is None, using default text configgh㈵>F) rms_norm_eps pad_token_idtie_word_embeddingsrDr )image_token_id use_cacherDr r$r)info isinstancedictr text_config scale_factorrr) rrFrErDr$rJrKrCrrs rrzIdefics3Config.__init__s-"#6  !5!7D  KKL M  t ,!5!F !FD   '; rRsN# 3!   H %c4+c4LNL%NLr