无法为 Tensor 'x_17:0' 提供形状 (500,) 的值，其形状为“(?, 500)”

Question

我刚开始学习 TensorFlow，如果这很明显，我深表歉意。我已经检查了文档并做了很多实验，但我似乎无法让它工作。

def train_network():
    OUT_DIMS = 1
    FIN_SIZE = 500
    x = tf.placeholder(tf.float32, [OUT_DIMS, FIN_SIZE], name="x")
    w = tf.Variable(tf.zeros([FIN_SIZE, OUT_DIMS]), name="w")
    b = tf.Variable(tf.zeros([OUT_DIMS]), name="b")
    y = tf.tanh(tf.matmul(x, w) + b)

    yhat = tf.placeholder(tf.float32, [None, OUT_DIMS])
    cross_entropy = -tf.reduce_sum(yhat*tf.log(y))

    train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)

    # Launch the model
    init = tf.initialize_all_variables()
    sess = tf.Session()
    sess.run(init)

    for this_x, this_y in yield_financials():
        sess.run(train_step, feed_dict={x:    this_x,
                                        yhat: this_y})
        print(end=".")
        sys.stdout.flush()

yield_financials() 输出一个包含 500 个数字的 numpy 数组和我希望它猜测的数字。我试过改组 OUT_DIMS 和 FIN_SIZE，我尝试将它们累积成批次以更接近教程的样子，我尝试将 OUT_DIMS 设置为 0，将其完全删除，然后我尝试用其他数字替换 None，但没有取得任何进展。

Answer 1

尝试

    this_x = np.reshape(this_x,(1, FIN_SIZE))
    sess.run(train_step, feed_dict={x:    this_x,
                                    yhat: this_y})

Answer 2

我遇到了同样的问题，我解决了这个问题problem.I希望对你有帮助。

首先，我将负载数据转换为：

train_data = np.genfromtxt(train_data1, delimiter=',')
train_label = np.transpose(train_label1, delimiter=',')
test_data = np.genfromtxt(test_data1, delimiter=',')
test_label = np.transpose(test_label1, delimiter=',')

然后，将trX, trY, teX, teY数据转化为：

# convert the data
trX, trY, teX, teY = train_data,train_label, test_data, test_label
temp = trY.shape
trY = trY.reshape(temp[0], 1)
trY = np.concatenate((1-trY, trY), axis=1)
temp = teY.shape
teY = teY.reshape(temp[0], 1)
teY = np.concatenate((1-teY, teY), axis=1)

最后，我将在会话中启动图形转换为：

with tf.Session() as sess:
    # you need to initialize all variables
    tf.initialize_all_variables().run()

    for i in range(100):
            sess.run(train_op, feed_dict={X:  trX, Y: trY})        
            print(i, np.mean(np.argmax(teY, axis=1) == sess.run(predict_op, feed_dict={X: teX})))

就这些了。

无法为 Tensor 'x_17:0' 提供形状 (500,) 的值，其形状为“(?, 500)”

Cannot feed value of shape (500,) for Tensor 'x_17:0', which has shape '(?, 500)'

python

tensorflow