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@hchasestevens
Last active January 14, 2020 18:19
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import tensorflow as tf
# 1000 * 1.07 ** X = 2000
# p * r ** X = y
p = tf.constant(1000.)
r = tf.constant(1.07)
X = tf.Variable(1., constraint=tf.keras.constraints.non_neg())
y = tf.constnat(2000.)
lhs = p * tf.pow(r, X)
err = tf.abs(lhs - y)
train_step = tf.train.AdamOptimizer(0.01).minimize(err)
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
print()
for i in range(1000):
sess.run(train_step)
if not (i % 100):
_X = sess.run(X)
print(f"{i}:\tX: {_X},\terr: {sess.run(err)},\ty: {sess.run(p * r ** _X)}")
print(f"X: {sess.run(X)}, y: {sess.run(p * r ** _X)}")
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