我是Tensorflow的新手,并且想知道是否可以使用Tensorflow最小化一个变量的函数.
例如,我们可以使用Tensorflow使用初始猜测(比如x = 1)来最小化2*x ^ 2 - 5 ^ x + 4吗？
我正在尝试以下方法:
import tensorflow as tf
import numpy as np
X = tf.placeholder(tf.float32, shape = ())
xvar = tf.Variable(np.random.randn())
f = 2*mul(X,X) - 5*X + 4
opt = tf.train.GradientDescentOptimizer(0.5).minimize(f)
with tf.Session() as sess:
tf.global_variables_initializer().run()
y = sess.run(opt, feed_dict = {X : 5.0}) #initial guess = 5.0
print(y)
但是这会产生以下错误:
ValueError: No gradients provided for any variable, check your graph for ops that do not support gradients, between variables
请帮我理解我在这里做错了什么.
我试图通过一个按钮将仪表板中的谷歌图表导出到png图像.但我得到以下错误 -
一个或多个参与者未能绘制()undefined不是一个函数
这是代码:
<html>
<head>
<!--Load the AJAX API-->
<script type="text/javascript" src="https://www.google.com/jsapi"></script>
<script type="text/javascript">
// Load the Visualization API and the controls package.
google.load('visualization', '1.0', {'packages':['controls']});
// Set a callback to run when the Google Visualization API is loaded.
google.setOnLoadCallback(drawDashboard);
// Callback that creates and populates a data table,
// instantiates a dashboard, a range slider and a pie chart,
// passes in the data and draws it.
function drawDashboard() {
// Create our data table.
var data = …