from model.backbone.DViT import DeepVisionTransformer
import torch
from torch import nn

if __name__ == '__main__':
    input=torch.randn(1,3,224,224)
    model = DeepVisionTransformer(
        patch_size=16, embed_dim=384,
        depth=[False] * 16,
        apply_transform=[False] * 0 + [True] * 32,
        num_heads=12,
        mlp_ratio=3,
        qkv_bias=True,
        norm_layer=partial(nn.LayerNorm, eps=1e-6),
        )
    output=model(input)
    print(output.shape)