Load custom filters to vgg

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.

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

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