Update unsuper.
This commit is contained in:
parent
45d5701835
commit
22464e7724
|
@ -115,43 +115,27 @@ for epoch in range(epochs):
|
||||||
images = images.to(device)
|
images = images.to(device)
|
||||||
outputs = model.forward_unsuper(images)
|
outputs = model.forward_unsuper(images)
|
||||||
|
|
||||||
# outputs = outputs.permute(0, 2, 3, 1) # 64 8 24 24 -> 64 24 24 8
|
|
||||||
# sample = outputs.reshape(-1, outputs.shape[3]) # -> 36864 8
|
|
||||||
# abs = torch.abs(sample)
|
|
||||||
# max, max_index = torch.max(abs, dim=1)
|
|
||||||
# min, min_index = torch.min(abs, dim=1)
|
|
||||||
# label = sample * 0.9
|
|
||||||
# all = range(0, label.shape[0])
|
|
||||||
# label[all, max_index] = label[all, max_index]*1.1
|
|
||||||
# loss = F.l1_loss(sample, label)
|
|
||||||
# model.conv1.weight.grad = None
|
|
||||||
# loss.backward()
|
|
||||||
|
|
||||||
outputs = outputs.permute(0, 2, 3, 1) # 64 8 24 24 -> 64 24 24 8
|
outputs = outputs.permute(0, 2, 3, 1) # 64 8 24 24 -> 64 24 24 8
|
||||||
sample = outputs.reshape(outputs.shape[0], -1, outputs.shape[3]) # -> 64 24x24 8
|
sample = outputs.reshape(-1, outputs.shape[3]) # -> 36864 8
|
||||||
abs = torch.abs(sample)
|
abs = torch.abs(sample)
|
||||||
sum = torch.sum(abs, dim=1, keepdim=False)
|
max, max_index = torch.max(abs, dim=1)
|
||||||
max, max_index = torch.max(sum, dim=1)
|
|
||||||
label = sample * 0.9
|
label = sample * 0.9
|
||||||
all = range(0, label.shape[0])
|
all = range(0, label.shape[0])
|
||||||
all_wh = range(0, 24 * 24)
|
label[all, max_index] = label[all, max_index] * 1.1
|
||||||
label[all, :, max_index] = label[all, :, max_index] * 1.1
|
|
||||||
loss = F.l1_loss(sample, label)
|
loss = F.l1_loss(sample, label)
|
||||||
model.conv1.weight.grad = None
|
model.conv1.weight.grad = None
|
||||||
loss.backward()
|
loss.backward()
|
||||||
|
|
||||||
# show.DumpTensorToImage(images.view(-1, images.shape[2], images.shape[3]), "input_image.png", Contrast=[0, 1.0])
|
model.conv1.weight.data = model.conv1.weight.data - model.conv1.weight.grad * 100
|
||||||
# w = model.conv1.weight.data
|
|
||||||
# show.DumpTensorToImage(w.view(-1, w.shape[2], w.shape[3]), "conv1_weight.png", Contrast=[-1.0, 1.0])
|
|
||||||
# w = model.conv1.weight.grad
|
|
||||||
# show.DumpTensorToImage(w.view(-1, w.shape[2], w.shape[3]).cpu(), "conv1_weight_grad.png")
|
|
||||||
model.conv1.weight.data = model.conv1.weight.data - model.conv1.weight.grad * 1000
|
|
||||||
# w = model.conv1.weight.data
|
|
||||||
# show.DumpTensorToImage(w.view(-1, w.shape[2], w.shape[3]), "conv1_weight_update.png", Contrast=[-1.0, 1.0])
|
|
||||||
|
|
||||||
if (i + 1) % 100 == 0:
|
if (i + 1) % 100 == 0:
|
||||||
print(f"Epoch [{epoch+1}/{epochs}], Step [{i+1}/{n_total_steps}], Loss: {loss.item():.8f}")
|
print(f"Epoch [{epoch+1}/{epochs}], Step [{i+1}/{n_total_steps}], Loss: {loss.item():.8f}")
|
||||||
|
|
||||||
|
w = model.conv1.weight.grad
|
||||||
|
show.DumpTensorToImage(w.view(-1, w.shape[2], w.shape[3]).cpu(), "conv1_weight_grad.png")
|
||||||
|
w = model.conv1.weight.data
|
||||||
|
show.DumpTensorToImage(w.view(-1, w.shape[2], w.shape[3]), "conv1_weight_update.png", Contrast=[-1.0, 1.0])
|
||||||
|
|
||||||
# Train the model
|
# Train the model
|
||||||
model.conv1.weight.requires_grad = False
|
model.conv1.weight.requires_grad = False
|
||||||
model.conv2.weight.requires_grad = True
|
model.conv2.weight.requires_grad = True
|
||||||
|
|
Loading…
Reference in New Issue