You would need to set requires_grad=True for the weights and it would also work as nn.Conv2d internally just calls the functional API, see here 316. 
However, if you prefer to use the module, you could try the following code:
weights = ...
conv = nn.Conv2d(nb_channels, 1, 3, bias=False)
with torch.no_grad():
    conv.weight = nn.Parameter(weights)

output = conv(x)
output.mean().backward()
print(conv.weight.grad)