我尝试在Numpy中使用两个不同维度的矩阵的点积。w是（1，5），X是（3，5）。我不确定我可以使用哪个命令来更改维度，因为我是python的新手。谢谢。
当我尝试运行我的函数时，它给我一个错误消息：

ValueError: shapes (1,5) and (3,5) not aligned: 5 (dim 1) != 3 (dim 0)

from numpy.core.memmap import ndarray
def L(w, X, y):
    """
    Arguments:
    w -- vector of size n representing weights of input features n
    X -- matrix of size m x n represnting input data, m data sample with n features each 
    y -- vector of size m (true labels)
  
    Returns:
    loss -- the value of the loss function defined above
    """
    
    ### START CODE HERE ### (2-4 lines of code)
    #w needs to match X matrix
    # w = (1, 5)
    # x = (3, 5)
    yhat = np.dot(w, X)
    L1 = y - yhat
    loss = np.dot(L1, L1)

    
    ### END CODE HERE ###
    
    return loss

下面是方向的图片：image of directions