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)}")