Load custom filters to vgg

1

I need to create a new model, by loading selected vgg filters.
I am using the following function inside VGG(nn.Module) class (Defined in torchvision example)
Here weights, bias are 2 dictionaries having selected filters from vgg

	def _initialize_weights(self):
		v = list(self.features)
		for i in range(len(v)):
			if i in [0,2,5,7,14,17,10,12,24,26,19,21,28]: #left last layer 28. Load original weights
				if isinstance(i,nn.Conv2d):
					w = self.weights['layer_'+str(i)] 
					w = torch.nn.parameter.Parameter(torch.from_numpy(np.array(w)))

					b = self.bias['layer_'+str(i)]
					b = torch.nn.parameter.Parameter(torch.from_numpy(np.array(b)))

					self.features[i].weight = w
					self.features[i].bias = b

But I am getting weird results. The output class obtained for the same image, changes everytime code is run.

2

did you put the model in .eval() mode? otherwise dropout in VGG will give you different output class for same image.

3

Yes, After constructing the model with custom filters,
I did model.eval().