| 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) |