In [ ]:

    

import tensorflow as tf

with tf.Graph().as_default() as g:
    # Note: we can omit the above line. By default, 
    # TensorFlow will add nodes to the default graph.
    # If you like, you can comment it out, then unindent the
    # code below.
    

    # Add code that will calculate and output the Fibonacci sequence
    # using TF. You will need to make use of tf.matmul() and
    # tf.assign() to perform the multiplications and assign the result
    # back to the variable fib_seq.

    fib_matrix = tf.constant([[0.0, 1.0],
                              [1.0, 1.0]])

    ### SOLUTION START ###
    # Put your solution code here.

    # Change this line to initialize fib_seq to a 2x1 TensorFlow
    # tensor *Variable* with the initial values of 0.0 and 1.0. Hint:
    # You'll need to make sure you specify a 2D tensor of shape 2x1,
    # not a 1D tensor. See fib_matrix above (a 2x2 2D tensor) to guide
    # you.
    fib_sequence = tf.Variable([[0.0], [1.0]])
    
    # Change this line to multiply fib_matrix and fib_sequence using tf.matmul()
    next_fib = tf.matmul(fib_matrix, fib_sequence)
    
    # And assign the result back to fig_sequence using tf.assign()
    assign_op = tf.assign(fib_sequence, next_fib)
    
    ### SOLUTION END ###
    
    init = tf.global_variables_initializer()
    with tf.Session() as sess:
        sess.run(init)
        for step in range(10):
            sess.run(assign_op)
            print(sess.run(fib_sequence))