【暂存】‘--selfcon_pos‘, type=str, default=‘[True,True,True]‘

2023-12-14 23:09:47

/home/wangbin/anaconda3/envs/partial_cuda_v1/bin/python /home/wangbin/Desktop
Files already downloaded and verified
Sequential(
? (0): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (3): Bottleneck(
????? (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
? (1): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (3): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (4): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (5): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
? (2): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
)
Sequential(
? (0): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (3): Bottleneck(
????? (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
? (1): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (3): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (4): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (5): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
? (2): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
)
******************


Sequential(
? (0): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (3): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (4): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (5): Bottleneck(
????? (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
? (1): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
)
******************


Sequential(
? (0): Sequential(
??? (0): Bottleneck(
????? (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential(
??????? (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
??????? (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? )
??? )
??? (1): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
??? (2): Bottleneck(
????? (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
????? (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
????? (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
????? (shortcut): Sequential()
??? )
? )
)
******************

文章来源:https://blog.csdn.net/nyist_yangguang/article/details/135004790
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