Commit 159001d8 by Andrei Roibu

### prepared execution of first VA code + fixed bugs

parent 1515a03b
 ... @@ -62,9 +62,9 @@ class Solver(): ... @@ -62,9 +62,9 @@ class Solver(): experiment_name, experiment_name, optimizer, optimizer, optimizer_arguments={}, optimizer_arguments={}, # loss_function=MSELoss(), loss_function=MSELoss(), # loss_function=torch.nn.L1Loss(), # loss_function=torch.nn.L1Loss(), loss_function=torch.nn.CosineEmbeddingLoss(), # loss_function=torch.nn.CosineEmbeddingLoss(), model_name='BrainMapper', model_name='BrainMapper', labels=None, labels=None, number_epochs=10, number_epochs=10, ... @@ -208,9 +208,8 @@ class Solver(): ... @@ -208,9 +208,8 @@ class Solver(): y_hat = torch.mul(y_hat, MNI152_T1_2mm_brain_mask) y_hat = torch.mul(y_hat, MNI152_T1_2mm_brain_mask) # loss = self.loss_function(y_hat, y) # Loss computation loss = self.loss_function(y_hat, y) # Loss computation loss = self.loss_function( # loss = self.loss_function(y_hat+1e-4, y+1e-4, torch.tensor(1.0).cuda(self.device, non_blocking=True)) y_hat+1e-4, y+1e-4, torch.tensor(1.0).cuda(self.device, non_blocking=True)) # We also calculate a separate MSE for cost function comparison! # We also calculate a separate MSE for cost function comparison! MSE = self.MSE(y_hat, y) MSE = self.MSE(y_hat, y) ... ...
 ... @@ -309,8 +309,8 @@ class ResNetClassifierBlock3D(nn.Module): ... @@ -309,8 +309,8 @@ class ResNetClassifierBlock3D(nn.Module): self.normalization = nn.InstanceNorm3d( self.normalization = nn.InstanceNorm3d( num_features=parameters['number_of_classes']) num_features=parameters['number_of_classes']) # self.activation = nn.Sigmoid() self.activation = nn.Sigmoid() self.activation = nn.Tanh() # self.activation = nn.Tanh() # TODO: Might be wworth looking at GANS for image generation, and adding padding # TODO: Might be wworth looking at GANS for image generation, and adding padding ... ...
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