31 lines
1.3 KiB
Python
31 lines
1.3 KiB
Python
|
#--------------------------------------------#
|
|||
|
|
# 该部分代码用于看网络结构
|
|||
|
|
#--------------------------------------------#
|
|||
|
|
import torch
|
|||
|
|
from thop import clever_format, profile
|
|||
|
|
from torchsummary import summary
|
|||
|
|
|
|||
|
|
from nets.unet import Unet
|
|||
|
|
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
input_shape = [1024, 1024]
|
|||
|
|
num_classes = 2
|
|||
|
|
backbone = 'resnet50'
|
|||
|
|
|
|||
|
|
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
|
|||
|
|
model = Unet(num_classes = num_classes, backbone = backbone).to(device)
|
|||
|
|
summary(model, (3, input_shape[0], input_shape[1]))
|
|||
|
|
|
|||
|
|
dummy_input = torch.randn(1, 3, input_shape[0], input_shape[1]).to(device)
|
|||
|
|
flops, params = profile(model.to(device), (dummy_input, ), verbose=False)
|
|||
|
|
#--------------------------------------------------------#
|
|||
|
|
# flops * 2是因为profile没有将卷积作为两个operations
|
|||
|
|
# 有些论文将卷积算乘法、加法两个operations。此时乘2
|
|||
|
|
# 有些论文只考虑乘法的运算次数，忽略加法。此时不乘2
|
|||
|
|
# 本代码选择乘2，参考YOLOX。
|
|||
|
|
#--------------------------------------------------------#
|
|||
|
|
flops = flops * 2
|
|||
|
|
flops, params = clever_format([flops, params], "%.3f")
|
|||
|
|
print('Total GFLOPS: %s' % (flops))
|
|||
|
|
print('Total params: %s' % (params))
|