The classifier you defined uses 2d BatchNorm, which means it acts on the two spatial dimensions of an image, hence expecting a 4d tensor(batch x channels x height x width).
For tensors of the forms  3d tensors (batch x time-step x features) or 2d tensors (batch x features), you should use 1d BatchNorm
Modified code shown below
self.classifier = nn.Sequential( 
    nn.Dropout(), 
    nn.Linear(256 * 6 * 6, 4096), 
    nn.BatchNorm1d(4096), 
    nn.ReLU(inplace=True), 
    nn.Dropout(), 
    nn.Linear(4096, 4096), 
    nn.BatchNorm1d(4096), 
    nn.ReLU(inplace=True), 
    nn.Linear(4096, 6), 
    )