from model.backbone.CoaT import CoaT
import torch
from torch import nn

if __name__ == '__main__':
    input=torch.randn(1,3,224,224)
    model = CoaT(patch_size=4, embed_dims=[152, 152, 152, 152], serial_depths=[2, 2, 2, 2], parallel_depth=6, num_heads=8, mlp_ratios=[4, 4, 4, 4])
    output=model(input)
    print(output.shape) # torch.Size([1, 1000])