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""" Variable exmaples

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Created by Chip Huyen ([email protected])

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CS20: "TensorFlow for Deep Learning Research"

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cs20.stanford.edu

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Lecture 02

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"""

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import os

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os.environ['TF_CPP_MIN_LOG_LEVEL']='2'

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import numpy as np

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import tensorflow as tf

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# Example 1: creating variables

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s = tf.Variable(2, name='scalar') 

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m = tf.Variable([[0, 1], [2, 3]], name='matrix') 

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W = tf.Variable(tf.zeros([784,10]), name='big_matrix')

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V = tf.Variable(tf.truncated_normal([784, 10]), name='normal_matrix')

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s = tf.get_variable('scalar', initializer=tf.constant(2)) 

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m = tf.get_variable('matrix', initializer=tf.constant([[0, 1], [2, 3]]))

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W = tf.get_variable('big_matrix', shape=(784, 10), initializer=tf.zeros_initializer())

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V = tf.get_variable('normal_matrix', shape=(784, 10), initializer=tf.truncated_normal_initializer())

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with tf.Session() as sess:

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    sess.run(tf.global_variables_initializer())

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    print(V.eval())

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# Example 2: assigning values to variables

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W = tf.Variable(10)

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W.assign(100)

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with tf.Session() as sess:

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    sess.run(W.initializer)

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    print(sess.run(W))                    	# >> 10

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W = tf.Variable(10)

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assign_op = W.assign(100)

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with tf.Session() as sess:

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    sess.run(assign_op)

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    print(W.eval())                     	# >> 100

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# create a variable whose original value is 2

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a = tf.get_variable('scalar', initializer=tf.constant(2)) 

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a_times_two = a.assign(a * 2)

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with tf.Session() as sess:

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    sess.run(tf.global_variables_initializer()) 

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    sess.run(a_times_two)                 	# >> 4

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    sess.run(a_times_two)                 	# >> 8

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    sess.run(a_times_two)                 	# >> 16

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W = tf.Variable(10)

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with tf.Session() as sess:

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    sess.run(W.initializer)

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    print(sess.run(W.assign_add(10)))     	# >> 20

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    print(sess.run(W.assign_sub(2)))     	# >> 18

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# Example 3: Each session has its own copy of variable

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W = tf.Variable(10)

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sess1 = tf.Session()

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sess2 = tf.Session()

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sess1.run(W.initializer)

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sess2.run(W.initializer)

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print(sess1.run(W.assign_add(10)))        	# >> 20

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print(sess2.run(W.assign_sub(2)))        	# >> 8

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print(sess1.run(W.assign_add(100)))        	# >> 120

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print(sess2.run(W.assign_sub(50)))        	# >> -42

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sess1.close()

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sess2.close()

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# Example 4: create a variable with the initial value depending on another variable

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W = tf.Variable(tf.truncated_normal([700, 10]))

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U = tf.Variable(W * 2)

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