TensorFlow - 根据另一个变量的形状动态定义变量的形状

Question

Say I have a certain the Tensor x whose dimensions are not defined upon graph initialization.

I can get its shape using:

x_shape = tf.shape(input=x)

Now if I want to create a variable based on the values defined in x_shape using:

y = tf.get_variable(variable_name="y", shape=[x_shape[0], 10])

I get an error, since the values passed to the argument shape must be int and not Tensor . How can I create such a dynamically shaped variable without using placeholders?

Answer 1

I'm running out of time so this is quick and dirty, but maybe it helps you to get to your solution... It's based on this (dynamic size for tf.zeros) but extends the idea to tf.Variables. Since your variable needs to be initialized anyway - I choose 0s...

import tensorflow as tf
I1_ph = tf.placeholder(name = "I1",shape=(None,None,None),dtype=tf_dtype)

zerofill = tf.fill(tf.shape(I1_ph), 0.0)
myVar = tf.Variable(0.0)
updateMyVar = tf.assign(myVar,zerofill,validate_shape=False)

res, = sess.run([updateMyVar], { I1_ph:np.zeros((1,2,2)) } )
print ("dynamic variable shape",res.shape)

res, = sess.run([updateMyVar], { I1_ph:np.zeros((3,5,2)) } )
print ("dynamic  variable shape",res.shape)

Answer 2

import tensorflow as tf

x = tf.zeros(shape=[10,20])
x_shape = x.get_shape().as_list()
y = tf.get_variable(shape=x_shape, name = 'y')

Update

You can't create tf.Variable with unknown size. For example this code is not valid:

y = tf.get_variable(shape=[None, 10], name = 'y')

Answer 3

您可以使用x.get_shape() ：

y = tf.get_variable('y', shape=[x.get_shape()[0], 10])

Answer 4

First argument is variable name.

x = tf.zeros(shape=[10,20])
x_shape = x.shape
variable_name ='y'
y = tf.get_variable(variable_name, shape=[x_shape[0], x_shape[1]])

Answer 5

To the best of my knowledge, you cannot create a Variable with a dynamic shape through the shape argument, instead you have to pass this dynamic shape through the initializer of the tf.Variable .

This should work:

zero_init = tf.fill([x_shape[0], 10], tf.constant(0))
# Initialize
y = tf.get_variable(
    "my_var", shape=None, validate_shape=False, initializer=zero_init
)

Note that the shape has to be defined before, or with the first execution of tf.Session.run(...) . So if your x is a placeholder, you will need to feed a value for it.