dataset/condition_classinput_inference/model.py

import torch
import torch.nn as nn
import timm


def Model():
    model = timm.create_model("vit_tiny_patch16_224", pretrained=True)
    model.head = nn.Sequential(
        nn.Linear(192, 192, bias=True),
        nn.SiLU(),
        nn.Linear(192, 2, bias=False),
    )
    for param in model.head.parameters():
        param = nn.Parameter(torch.ones_like(param) / 192)
        param.requires_grad = True
    return model, model.head


if __name__ == "__main__":
    model, _ = Model()
    print(model)
    num_param = 0
    for v in model.parameters():
        num_param += v.numel()
    print("num_param:", num_param)