def forward(self, t, h):
        """dh/dt as a function of time and h(t)."""
        if self.i == 0:
            self.A = self.beta * (self.B - self.B.transpose(1, 0)) + (
                1 - self.beta) * (self.B +
                                  self.B.transpose(1, 0)) - self.gamma * self.I
            self.W = self.beta * (self.C - self.C.transpose(1, 0)) + (
                1 - self.beta) * (self.C +
                                  self.C.transpose(1, 0)) - self.gamma * self.I

        return torch.matmul(
            h, self.A) + self.tanh(torch.matmul(h, self.W) + self.z)
dh/dt as a function of time and h(t).
analyze/convnexts4nd/src/models/baselines/lipschitzrnn.py