In my NeuralNetwork, I can’t get model.parameters()
this is my NN
class NeuralNetwork(nn.Module):
def __init__(self):
super(NeuralNetwork, self).__init__()
#down
input_ch = 1
output_ch = 64
self.down = []
for i in range(4):
self.down.append(
nn.Sequential(
nn.Conv2d(input_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.Conv2d(output_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.MaxPool2d(2,2)
)
)
input_ch = output_ch
output_ch *= 2
#bottom
bottom = nn.Sequential(
nn.Conv2d(input_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.Conv2d(output_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.ConvTranspose2d(output_ch, input_ch, kernel_size=2, stride=1)
)
#up
input_ch = output_ch
output_ch = input_ch // 2
self.up = []
for i in range(3):
self.up.append(
nn.Sequential(
nn.Conv2d(input_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.Conv2d(output_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.ConvTranspose2d(output_ch, output_ch // 2, kernel_size=2, stride=2)
)
)
input_ch = output_ch
output_ch = input_ch // 2
#end
end = nn.Sequential(
nn.Conv2d(input_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.Conv2d(output_ch, output_ch, 3, padding=1),
nn.ReLU(inplace=True),
nn.Conv2d(output_ch, 1, 3, padding=1)
)
def forward(self, x):
enc_out = []
#encoder
for i in range(4):
if i == 0:
enc_out[i] = self.down[i](x)
else:
enc_out[i] = self.down[i](enc_out[i-1])
#bottom
dec_out = self.bottom(enc_out[3])
#decoder
for i in range(3):
dec_out = self.up[i](torch.cat((enc_out[3 - i], dec_out), dim=1))
#end
dec_out = self.end(torch.cat((enc_out[0], dec_out), dim=1))
return dec_out
and the optimizer is here
class DenoiseImage():
def __init__(self, model, learning_late=1e-3, batch_size=64):
self.model = model
self.loss_fn = nn.MSELoss()
self.optimizer = torch.optim.AdamW(self.model.parameters(), lr=learning_late)
def training(dataloader, epochs):
for i in range(epochs):
for batch, (x, y) in enumerate(dataloader):
predict = self.model(x)
loss = self.loss_fn(predict, y)
self.optimizer.zero_grad()
loss.backward()
self.optimizer.step()
error message
ValueError Traceback (most recent call last)
<ipython-input-23-293c39f65724> in <module>()
221 model = NeuralNetwork()
--> 222 dino = DenoiseImage(model, batch_size=64)
223
2 frames
/usr/local/lib/python3.7/dist-packages/torch/optim/optimizer.py in __init__(self, params, defaults)
47 param_groups = list(params)
48 if len(param_groups) == 0:
---> 49 raise ValueError("optimizer got an empty parameter list")
50 if not isinstance(param_groups[0], dict):
51 param_groups = [{'params': param_groups}]
ValueError: optimizer got an empty parameter list
<Figure size 576x576 with 0 Axes>
