This is how my model gonna look like after recursively calling the fuse_module_1
Sequential(
(0): BinConv2d(
(bn): BatchNorm1d(9216, eps=0.0001, momentum=0.1, affine=True, track_running_stats=True)
(linear): Linear(in_features=9216, out_features=4096, bias=True)
(relu): ReLU(inplace=True)
)
(1): BinConv2d(
(dropout): Dropout(p=0.5, inplace=False)
(bn): BatchNorm1d(4096, eps=0.0001, momentum=0.1, affine=True, track_running_stats=True)
(linear): Linear(in_features=4096, out_features=4096, bias=True)
(relu): ReLU(inplace=True)
)
(2): BatchNorm1d(4096, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
(3): Dropout(p=0.5, inplace=False)
(4): Linear(in_features=4096, out_features=1000, bias=True)

this is before m.classifier[1].linear = bc