In [1]:

    

# Solution is available in the other "solution.py" tab
import tensorflow as tf


def run():
    output = None
    logit_data = [2.0, 1.0, 0.1]
    logits = tf.placeholder(tf.float32)
    
    # TODO: Calculate the softmax of the logits
    # softmax =     
    softmax = tf.nn.softmax(logits)
    
    with tf.Session() as sess:
        # TODO: Feed in the logit data
        # output = sess.run(softmax,    )
        output = sess.run(softmax, feed_dict={logits: logit_data})

    return output


    

In [4]:

    

run()


    

    
Out[4]:





array([ 0.65900117,  0.24243298,  0.09856589], dtype=float32)

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