import numpy as np
def initialize_parameters(n_x, n_h, n_y):
np.random.seed(2) # we set up a seed so that our output matches ours although the initialization is random.
W1 = np.random.randn(n_h, n_x) * 0.01 #weight matrix of shape (n_h, n_x)
b1 = np.zeros(shape=(n_h, 1)) #bias vector of shape (n_h, 1)
W2 = np.random.randn(n_y, n_h) * 0.01 #weight matrix of shape (n_y, n_h)
b2 = np.zeros(shape=(n_y, 1)) #bias vector of shape (n_y, 1)
#store parameters into a dictionary
parameters = {"W1": W1,
"b1": b1,
"W2": W2,
"b2": b2}
return parameters
#Function to define the size of the layer
def layer_sizes(X, Y):
n_x = X.shape[0] # size of input layer
n_h = 6# size of hidden layer
n_y = Y.shape[0] # size of output layer
return (n_x, n_h, n_y)
但是出现此错误:文件“”,第4行np.random.seed(2)#尽管初始化是随机的,但我们设置了一个种子以使我们的输出与我们的种子匹配。^IndentationError:预期为缩进的块
所有来自:
def initialize_parameters(n_x, n_h, n_y):
到
return parameters
在上面的示例中,需要缩进四个空格。