TypeError: 'Tensor' object cannot be interpreted as an integer

Question

I am trying to run a loop based on the size of the array. how to do that in tensorflow ? For example

# input pipeline with all files available in the folder
a = tf.Variable([1,2,3,4,5],dtype = tf.int32)
loop = tf.size(a)
....
for i in range(loop):
    print(sess.run(a))

I wanted to print the array a for 5 times. but it says loop is a tensor object and cannot taken as integer. I have tried taking the loop variable as

loop = tf.cast(tf.size(a),tf.int32),
loop = tf.shape_n(a),
loop = tf.shape(a)[0]

it has the same error.

Engineero · Accepted Answer · 2020-05-15 17:36:30Z

3

Not really sure what you want to achieve here. loop is a tf.Tensor and range expects an integer as argument, hence the error. If you just want to print a 5 times, why don't you just set loop to the numerical value of 5?

Otherwise, the following code should work, as loop.eval() returns the value of loop which is 5:

a = tf.Variable([1,2,3,4,5],dtype = tf.int32)
loop = tf.size(a)
....
for i in range(loop.eval()):
    print(sess.run(a))

If you don't want to execute the TF graph multiple times, take a look at tf.while_loop.

edited May 15, 2020 at 17:36

Engineero

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answered Jan 22, 2017 at 8:15

guinny

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Comments

Shobeir · Accepted Answer · 2017-01-22 08:14:55Z

2

tf.size() does not give you a value or list.

a = tf.Variable([1,2,3,4,5],dtype = tf.int32)

v = a.get_shape()
loop = v.num_elements()

...

Perhaps, try this.

answered Jan 22, 2017 at 8:14

Shobeir

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1 Comment

Raady Over a year ago

I have used tf.shape in place of tf.size in the above answer.

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