import tensorflow as tf

# Define a placeholder that expects a vector of three floating-point values

# and a computation that depends on it

x = tf.placeholder(tf.float32, shape=[3])

y = tf.square(x)

with tf.Session() as sess:

    # Feeding a value changes the result that is returned when you evaluate y

    print(sess.run(y, {x:[1.0, 2.0, 3.0]}))  # => "[1.0,4.0,9.0]"

    print(sess.run(y, {x:[0.0, 0.0, 5.0]}))  # => "[0.0,0.0,25.0]"

    # Raises "tf.errors.InvalidArgumentError" , because you must feed a value for

    # a 'tf.placeholder()' when evaluating a tensor that depends on it

    sess.run(y)

    # Raise 'ValueError', because the shape of 37.0 does not match the shape

    # of placeholder x

    sess.run(y, {x:37.0})

2018-02-17 11:11:35.215329: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\35\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

[ 1.  4.  9.]

[  0.   0.  25.]