test

affine_forward.py

def affine_forward(x, w, b):
    """
    Inputs:
    - x: A numpy array containing input data, of shape (N, d_1, ..., d_k) 样本
    - w: A numpy array of weights, of shape (D, M) 权重
    - b: A numpy array of biases, of shape (M,) 偏置
    Returns a tuple of:
    - out: output, of shape (N, M)
    - cache: (x, w, b)
    """
    out = None            # 初始化
    reshaped_x = np.reshape(x, (x.shape[0],-1))  # 确保x是一个规整的矩阵
    out = reshape_x.dot(w) +b                    # out = w x +b
    cache = (x, w, b)							
    # cache将该函数的输入值缓冲储存起来，以备后面计算梯度时使用
    return out, cache