Hi folks,
I am trying to build an ensemble with the following code:
class PytorchMnistEnsModel(nn.Module):
    """ Basic MNIST model from github
    https://github.com/rickiepark/pytorch-examples/blob/master/mnist.ipynb
    """
    def __init__(self, num_models=5):
        super(PytorchMnistEnsModel, self).__init__()
        # input is 28x28
        # padding=2 for same padding
        self.conv1 = {}
        self.conv2 = {}
        self.fc1 = {}
        self.fc2 = {}
        self.num_models = num_models

        for i in range(self.num_models):
            self.conv1[i] = nn.Conv2d(1, 32, 5, padding=2)
            # feature map size is 14*14 by pooling
            # padding=2 for same padding
            self.conv2[i] = nn.Conv2d(32, 64, 5, padding=2)
            # feature map size is 7*7 by pooling
            self.fc1[i] = nn.Linear(64 * 7 * 7, 1024)
            self.fc2[i] = nn.Linear(1024, 10)

    def forward(self, x):
        preds_list = []
        y = {}
        for i in range(self.num_models):
            y[i] = torch.tensor(x, requires_grad=True)
            y[i] = F.relu((self.conv1[i](y[i])))
            y[i] = F.max_pool2d(y[i], 2)
            y[i] = F.relu(self.conv2[i](y[i]))
            y[i] = F.max_pool2d(y[i], 2)
            y[i] = y[i].view(-1, 64 * 7 * 7)  # reshape Variable
            y[i] = F.relu(self.fc1[i](y[i]))
            y[i] = self.fc2[i](y[i])
            preds_list.append(F.log_softmax(y[i], dim=-1))
        preds_avg = torch.mean(torch.stack(preds_list), dim = 0)
        return preds_avg

When I call model.parameters() on this, it returns an empty list. I am guessing it has something to do with my usage of dictionary for defining conv and fc layers. How do I go about fixing this?
Thanks in advance!