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))
|