| 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) |
