Question

我在tensorboard中写了一些总结代码..但是当我将链接粘贴到浏览器中时...显示了上面的错误... 我正在使用代理，并且在运行代码时会在Data文件夹中创建事件文件

我在Windows的CMD上使用以下命令： cd D：\反向传播\ Mycode tensorboard --logdir = data / --host本地主机--port 8088


class NeuralNetwork:
    def add_layer(inputs,in_size,out_size,activation_function=None):
        with tf.name_scope("layer"):
            with tf.name_scope("weights"):
                Weights= tf.Variable(tf.random_normal([in_size,out_size]),name="W")
            with tf.name_scope("biases"):
                biases= tf.Variable(tf.zeros([out_size])+0.1,name="b")
            with tf.name_scope("layer"):
                Wx_plus_b = tf.add(tf.matmul(inputs,Weights),biases)
            if activation_function is None:
                outputs = Wx_plus_b
            else:
                outputs = activation_function(Wx_plus_b)
            return outputs
x_data =np.linspace(-1,1,300)[:,np.newaxis]
noise =np.random.normal(0,0.05,x_data.shape)
y_data=np.square(x_data) -0.5 +noise

with tf.name_scope("inputs"):
    xs = tf.placeholder(tf.float32,[None, 1],name='x_inputs')
    ys = tf.placeholder(tf.float32,[None, 1],name='y_inputs')

l1=NeuralNetwork.add_layer(xs ,1,10,activation_function=tf.nn.relu)

prediction= NeuralNetwork.add_layer(l1,10,1,activation_function=None)
with tf.name_scope("loss"):
    loss=tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction),
                  reduction_indices=[1]))
    tf.summary.scalar("loss",loss)
with tf.name_scope("train"):
    train_step=tf.train.GradientDescentOptimizer(0.1).minimize(loss)

init=tf.global_variables_initializer()

sess=tf.Session()
writer =tf.summary.FileWriter("data/")
writer.add_graph(sess.graph)

sess.run(init)

for i in range(1000):
    sess.run(train_step, feed_dict={xs:x_data, ys:y_data})
    if i % 50==0: #print loss every 50 step
        print(sess.run(loss,feed_dict={xs:x_data,ys:y_data}))

当前数据集没有活动的仪表板

0 个答案: