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Use __call__ instead of forward #58

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Apr 10, 2017
Merged

Use __call__ instead of forward #58

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20 changes: 10 additions & 10 deletions advanced_source/neural_style_tutorial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -286,7 +286,7 @@ def __init__(self, target, weight):
self.criterion = nn.MSELoss()

def forward(self, input):
self.loss = self.criterion.forward(input * self.weight, self.target)
self.loss = self.criterion(input * self.weight, self.target)
self.output = input
return self.output

Expand Down Expand Up @@ -357,9 +357,9 @@ def __init__(self, target, weight):

def forward(self, input):
self.output = input.clone()
self.G = self.gram.forward(input)
self.G = self.gram(input)
self.G.mul_(self.weight)
self.loss = self.criterion.forward(self.G, self.target)
self.loss = self.criterion(self.G, self.target)
return self.output

def backward(self, retain_variables=True):
Expand Down Expand Up @@ -430,15 +430,15 @@ def get_style_model_and_losses(cnn, style_img, content_img,

if name in content_layers:
# add content loss:
target = model.forward(content_img).clone()
target = model(content_img).clone()
content_loss = ContentLoss(target, content_weight)
model.add_module("content_loss_" + str(i), content_loss)
content_losses.append(content_loss)

if name in style_layers:
# add style loss:
target_feature = model.forward(style_img).clone()
target_feature_gram = gram.forward(target_feature)
target_feature = model(style_img).clone()
target_feature_gram = gram(target_feature)
style_loss = StyleLoss(target_feature_gram, style_weight)
model.add_module("style_loss_" + str(i), style_loss)
style_losses.append(style_loss)
Expand All @@ -449,15 +449,15 @@ def get_style_model_and_losses(cnn, style_img, content_img,

if name in content_layers:
# add content loss:
target = model.forward(content_img).clone()
target = model(content_img).clone()
content_loss = ContentLoss(target, content_weight)
model.add_module("content_loss_" + str(i), content_loss)
content_losses.append(content_loss)

if name in style_layers:
# add style loss:
target_feature = model.forward(style_img).clone()
target_feature_gram = gram.forward(target_feature)
target_feature = model(style_img).clone()
target_feature_gram = gram(target_feature)
style_loss = StyleLoss(target_feature_gram, style_weight)
model.add_module("style_loss_" + str(i), style_loss)
style_losses.append(style_loss)
Expand Down Expand Up @@ -564,7 +564,7 @@ def closure():
input_param.data.clamp_(0, 1)

optimizer.zero_grad()
model.forward(input_param)
model(input_param)
style_score = 0
content_score = 0

Expand Down