在恒定张量上评估时，Tensorflow的Argmax函数不显示值

Question

I'm new at Tensorflow. I am having a litte trouble at understanding its constants. I have this simple code mentioned below:

import tensorflow as tf
vector = tf.constant([[1,2,3,4],[4,5,6,7],[8,9,1,2]],tf.int32,name="vector")
with tf.Session() as sess:
    v = sess.run(vector)
    argm = tf.argmax(v,1)
    print(argm)

I expect this to return something like [4,7,8] , as I understood from the documentation. Instead, I get this:

 Tensor("ArgMax:0", shape=(3,), dtype=int64). 

So, i don't know what am I doing wrong.

Answer 1

Alternatively to the answer of @James, you might want to use tensorflow's eager execution , which behaves more like "standard" python: operations are executed as you type them, no more graphs and Session .

import tensorflow as tf

tf.enable_eager_execution()

vector = tf.constant([[1,2,3,4],[4,5,6,7],[8,9,1,2]],tf.int32,name="vector")
argm = tf.argmax(vector,1)
print(argm)

Answer 2

Tensorflow operations like tf.argmax somewhat unintuitively don't perform the operation that they're stating, but add an operation to a graph that will be performed. When you run argm = tf.argmax(v,1) , the return value is tensor that isn't evaluated yet.

If you want the result of the argmax operation, you can run something like this:

import tensorflow as tf
vector = tf.constant([[1,2,3,4],[4,5,6,7],[8,9,1,2]],tf.int32,name="vector")
argm = tf.argmax(vector,1)
with tf.Session() as sess:
    a = sess.run(argm)
    print(a)

With this code, we're explicitly asking Tensorflow to run the computations to compute the result of the tf.argmax operation. With your previous code, we ran the computation to compute v (which is a constant, so that's pretty quick), then define a new graph operation to compute argmax on that - but never actually do the computation.