dense.py

def forward_pass(self, a_prev: np.array) -> np.array:
    self._a_prev = np.array(a_prev, copy=True)
    return np.dot(a_prev, self._w.T) + self._b

def backward_pass(self, da_curr: np.array) -> np.array:
    n = self._a_prev.shape[0]
    self._dw = np.dot(da_curr.T, self._a_prev) / n
    self._db = np.sum(da_curr, axis=0, keepdims=True) / n
    return np.dot(da_curr, self._w)