Dawny33 Dawny33 - 1 year ago 300
Python Question

How to print the value of a Tensor object in TensorFlow?

I have been using the introductory example of matrix multiplication in TensorFlow.

matrix1 = tf.constant([[3., 3.]])
matrix2 = tf.constant([[2.],[2.]])
product = tf.matmul(matrix1, matrix2)

And when I print the product, it is displaying it as a TensorObject(obviously).


<tensorflow.python.framework.ops.Tensor object at 0x10470fcd0>

But how do I know the value of

The following doesn't help:

print product
Tensor("MatMul:0", shape=TensorShape([Dimension(1), Dimension(1)]), dtype=float32)

I know that graphs run on
, but isn't there any way I can check the output of a TensorObject without running the graph in a

Answer Source

The easiest* way to evaluate the actual value of a Tensor object is to pass it to the Session.run() method, or call Tensor.eval() when you have a default session (i.e. in a with tf.Session(): block, or see below). In general,** you cannot print the value of a tensor without running some code in a session.

If you are experimenting with the programming model, and want an easy way to evaluate tensors, the tf.InteractiveSession lets you open a session at the start of your program, and then use that session for all Tensor.eval() (and Operation.run()) calls. This can be easier in an interactive setting, such as the shell or an IPython notebook, when it's tedious to pass around a Session object everywhere.

This might seem silly for such a small expression, but one of the key ideas in Tensorflow is deferred execution: it's very cheap to build a large and complex expression, and when you want to evaluate it, the back-end (to which you connect with a Session) is able to schedule its execution more efficiently (e.g. executing independent parts in parallel and using GPUs).

*  To print the value of a tensor without returning it to your Python program, you can use the tf.Print() op, as And suggests in another answer. Note that you still need to run part of the graph to see the output of this op, which is printed to standard output. If you're running distributed TensorFlow, the tf.Print() op will print its output to the standard output of the task where that op runs.

**  You might be able to use the experimental tf.contrib.util.constant_value() function to get the value of a constant tensor, but it isn't intended for general use, and it isn't defined for many operators.

Recommended from our users: Dynamic Network Monitoring from WhatsUp Gold from IPSwitch. Free Download