np.dot（）>> TypeError：*：不支持的操作数类型：“ float”和“ NoneType”

Question

我看不到问题：A，W和b都是已初始化的数组。 np.dot（）可在另一个笔记本中使用。我敢肯定这是微不足道的，任何帮助将不胜感激。

def linear_forward(A, W, b):
    """
    Implement the linear part of a layer's forward propagation.

    Arguments:
    A -- activations from previous layer (or input data): (size of previous 
    layer, number of examples)
    W -- weights matrix: numpy array of shape (size of current layer, size of 
    previous layer)
    b -- bias vector, numpy array of shape (size of the current layer, 1)

    Returns:
    Z -- the input of the activation function, also called pre-activation 
    parameter 
    cache -- a python dictionary containing "A", "W" and "b" ; stored for 
    computing the backward pass efficiently
    """

    print(type(W), type(A), type(b))
    Z = np.sum(np.dot(W,A), b)

    assert(Z.shape == (W.shape[0], A.shape[1]))
    cache = (A, W, b)

    return Z, cache

Z, linear_cache = linear_forward(train_X, parameters["W1"], parameters["b1"])

<class 'numpy.ndarray'> <class 'numpy.ndarray'> <class 'numpy.ndarray'>
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-46-acc623b98d4c> in <module>
----> 1 Z, linear_cache = linear_forward(train_X, parameters["W1"], parameters["b1"])

<ipython-input-45-82f7e782daed> in linear_forward(A, W, b)
     14 
     15     print(type(W), type(A), type(b))
---> 16     Z = np.sum(np.dot(W,A), b)
     17 
     18     assert(Z.shape == (W.shape[0], A.shape[1]))

TypeError: unsupported operand type(s) for *: 'float' and 'NoneType'