Hi,
I have a trained a UNet model on some images but now, I want to extract the encoder part of the model. My UNet has the following architecture:
UNet(
(conv_final): Conv2d(8, 1, kernel_size=(1, 1), stride=(1, 1))
(down_convs): ModuleList(
(0): DownConv(
(conv1): Conv2d(1, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(8, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
)
(1): DownConv(
(conv1): Conv2d(8, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
)
(2): DownConv(
(conv1): Conv2d(16, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
)
(3): DownConv(
(conv1): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
)
(4): DownConv(
(conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
)
)
(up_convs): ModuleList(
(0): UpConv(
(upconv): ConvTranspose2d(128, 64, kernel_size=(2, 2), stride=(2, 2))
(conv1): Conv2d(128, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
)
(1): UpConv(
(upconv): ConvTranspose2d(64, 32, kernel_size=(2, 2), stride=(2, 2))
(conv1): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
)
(2): UpConv(
(upconv): ConvTranspose2d(32, 16, kernel_size=(2, 2), stride=(2, 2))
(conv1): Conv2d(32, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
)
(3): UpConv(
(upconv): ConvTranspose2d(16, 8, kernel_size=(2, 2), stride=(2, 2))
(conv1): Conv2d(16, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(conv2): Conv2d(8, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
)
)
)
I have tried to load the encoder layers through model.down_convs
but I get the following error:
TypeError Traceback (most recent call last)
in
----> 1 res = encoder(train_img)~/anaconda3/envs/work/lib/python3.8/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
548 result = self._slow_forward(*input, **kwargs)
549 else:
→ 550 result = self.forward(*input, **kwargs)
551 for hook in self._forward_hooks.values():
552 hook_result = hook(self, input, result)TypeError: forward() takes 1 positional argument but 2 were given
What should I do?