sg1ZdZddlmZddlmZej eZGddeZy)zVAN model configuration)PretrainedConfig)loggingc VeZdZdZdZddgdgdgdgdgd d d d d ddf fd ZxZS) VanConfiga This is the configuration class to store the configuration of a [`VanModel`]. It is used to instantiate a VAN 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 VAN [Visual-Attention-Network/van-base](https://huggingface.co/Visual-Attention-Network/van-base) architecture. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: image_size (`int`, *optional*, defaults to 224): The size (resolution) of each image. num_channels (`int`, *optional*, defaults to 3): The number of input channels. patch_sizes (`List[int]`, *optional*, defaults to `[7, 3, 3, 3]`): Patch size to use in each stage's embedding layer. strides (`List[int]`, *optional*, defaults to `[4, 2, 2, 2]`): Stride size to use in each stage's embedding layer to downsample the input. hidden_sizes (`List[int]`, *optional*, defaults to `[64, 128, 320, 512]`): Dimensionality (hidden size) at each stage. depths (`List[int]`, *optional*, defaults to `[3, 3, 12, 3]`): Depth (number of layers) for each stage. mlp_ratios (`List[int]`, *optional*, defaults to `[8, 8, 4, 4]`): The expansion ratio for mlp layer at each stage. hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in each layer. If string, `"gelu"`, `"relu"`, `"selu"` and `"gelu_new"` are supported. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. layer_norm_eps (`float`, *optional*, defaults to 1e-06): The epsilon used by the layer normalization layers. layer_scale_init_value (`float`, *optional*, defaults to 0.01): The initial value for layer scaling. drop_path_rate (`float`, *optional*, defaults to 0.0): The dropout probability for stochastic depth. dropout_rate (`float`, *optional*, defaults to 0.0): The dropout probability for dropout. Example: ```python >>> from transformers import VanModel, VanConfig >>> # Initializing a VAN van-base style configuration >>> configuration = VanConfig() >>> # Initializing a model from the van-base style configuration >>> model = VanModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```van)r r r )rr r )@i@i)r r r )rrrgelug{Gz?gư>g{Gz?gc t|di|||_||_||_||_||_||_||_||_ | |_ | |_ | |_ | |_ | |_y)N)super__init__ image_size num_channels patch_sizesstrides hidden_sizesdepths mlp_ratios hidden_actinitializer_rangelayer_norm_epslayer_scale_init_valuedrop_path_rate dropout_rate)selfrrrrrrrrrrrr r!kwargs __class__s g/var/www/html/venv/lib/python3.12/site-packages/transformers/models/deprecated/van/configuration_van.pyrzVanConfig.__init__Msx" "6"$(& ( $$!2,&<#,()__name__ __module__ __qualname____doc__ model_typer __classcell__)r$s@r%rrsC0 dJ (#))r&rN) r*configuration_utilsrutilsr get_loggerr'loggerrrr&r%r1s34   H %S) S)r&