Hi @ptrblck,
can you help me with the code snippet on custom nn.Module?
Below I try to use nn.Linear but the weights are still updating.
# eign_vectors == it is a tensor contains eign value for each layer.
for i, layer in enumerate(layers):
    alpha = torch.nn.Linear(shape[0], shape[1], bias=False)
    addn_to_weights = torch.matmul(alpha.weight, eign_vectors[i])
    model.layers[i].weight = model.layers[i].weight = torch.nn.Parameter(
                    torch.add(model.layers[i].weight.clone.detach(), addn_to_weights)
                )

# here i don't want to update weights, Only update the alpha value in a next training process.

Thanks!