How to get the derivative of a layer with respect to another one

Hello! I have a neural network like this (this is a simplified version):

class SimpleNet(nn.Module):
    def __init__(self):
        super().__init__()
        self.linear1 = nn.Linear(2, 1,  bias=False)
        self.linear2 = nn.Linear(1, 2,  bias=False)
            
    def forward(self, x):
        z = self.linear1(x)
        y_pred = self.linear2(z)

        return y_pred, z

and the loss is just MSE. After I call loss.backwards(), I want to get the value of the gradient of y_pred with respect to z. How can I do this? Thank you!