如何在张量流中使用张量的动态形状

Question

如何为以下计算建立张量流图？我现在面临的问题是如何使用张量A的形状信息，它具有可变的形状大小。

A = tf.placeholder(tf.float32, [None,10]) 
B = tf.Variable(tf.random_normal([10,20])) 
C = tf.matmul(A, B) 
D = tf.matmul(tf.transpose(C), A) # the value of A.shape[0] 

Answer 1

你是一个张A的价值已经传递给一个占位符，当你这样做，你就知道它的形状。我会为您关心的形状创建另一个占位符，并通过它：

import tensorflow as tf 
import numpy as np 

A = tf.placeholder(tf.float32, [None,10]) 
L = tf.placeholder(tf.float32, None) 

B = tf.Variable(tf.random_normal([10,20])) 
C = tf.matmul(A, B) 
D = tf.multiply(tf.transpose(C), L) // L is a number, matmul does not multiply matrix with a number 

with tf.Session() as sess: 
    sess.run(tf.global_variables_initializer()) 
    a = np.zeros((5, 10), dtype=np.float32) 
    l = a.shape[0] 
    sess.run(D, {A: a, L: l})