How to assign tensor value in to another function's tensor variable?

Question

I am calculating some features from a set of data. I made as function for each calculation. I want to put all of those values in an array in another function and I want to call the function. how to do it ?

The 3 functions that I have are

def peak_value(x):
    return tf.reduce_max(tf.abs(x))
def rootms(x):
    return tf.sqrt(tf.reduce_mean(tf.square(x)))
def meanofabs(x):
    return tf.reduce_mean(tf.abs(x))

I want these values to be assigned to a array inside function

def pooldata(x,size):
    pool = tf.zeros([1,size],tf.float32)
    # i want to 
    # assign pool[0] with peak_value(x)
    # assign pool[1] with rootms(x)
    # assign pool[2] with meanofabs(x)
    return pool

then I want to call the function

# define x, size
model = tf.intialize_all_variables()
sess = tf.Session()
sess.run(model)
print(sess.run(pooldata)) # print all the three values

How can i do it ?

I tried

tf.assign(pool[0],peak_value(x))

but it gives me error

TypeError: Input 'ref' of 'Assign' Op requires l-value input

keveman · Accepted Answer · 2017-01-20 16:41:15Z

tf.assign only lets you assign a value to the entire variable, and not to a slice of a variable. You would have to use tf.scatter_update to assign to a slice of a variable. However, in your case, you can simply create the pool tensor by concatenating the three values. Here is the complete working program :

import tensorflow as tf

def peak_value(x):
    return tf.reduce_max(tf.abs(x))
def rootms(x):
    return tf.sqrt(tf.reduce_mean(tf.square(x)))
def meanofabs(x):
    return tf.reduce_mean(tf.abs(x))


def pooldata(x,size):
    pool = tf.concat_v2([tf.expand_dims(peak_value(x), 0),
                         tf.expand_dims(rootms(x), 0),
                         tf.expand_dims(meanofabs(x), 0)], axis=0)
    # i want to
    # assign pool[0] with peak_value(x)
    # assign pool[1] with rootms(x)
    # assign pool[2] with meanofabs(x)
    return pool

sess = tf.Session()
size = 1
x = [1.0]

print(sess.run(pooldata(x, size)))

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