# import tensorflow as tf

# node1 = tf.constant(3.0, dtype=tf.float32)
# node2 = tf.constant(4.0)
# print(node1, node2)

# sess = tf.Session()
# print(sess.run([node1, node2]))

# node3 = tf.add(node1, node2)
# print("node3: ", node3)
# print("sess.run(node3): ", sess.run(node3))

# a = tf.placeholder(tf.float32)
# b = tf.placeholder(tf.float32)
# adder_node = a + b

# print(sess.run(adder_node, {a: 3, b: 4.5}))

# print(sess.run(adder_node, {a: [1, 3], b: [2, 4]}))
# add_and_triple = adder_node * 3.0
# print(sess.run(add_and_triple, {a: 3, b: 4.5}))

# W = tf.Variable([0.3], dtype=tf.float32)
# b = tf.Variable([-0.3], dtype=tf.float32)
# x = tf.placeholder(tf.float32)
# linear_model = W * x + b

# init = tf.global_variables_initializer()
# sess.run(init)

# print(sess.run(linear_model, {x: [1, 2, 3, 4]}))

# y = tf.placeholder(tf.float32)

# squared_deltas = tf.square(linear_model - y)
# loss = tf.reduce_sum(squared_deltas)

# print(sess.run(loss, {x: [1, 2, 3, 4], y: [0, -1, -2, -3]}))

# fixW = tf.assign(W, [-1.0])
# fixb = tf.assign(b, [1.0])
# sess.run([fixW, fixb])
# print(sess.run(loss, {x: [1, 2, 3, 4], y: [0, -1, -2, -3]}))
# import math
# import sys
# from os import rename

# import requests

# print(sys.version)
# print(sys.executable)


# def greet(who_to_greet):
#     greeting = "Hello, {}".format(who_to_greet)
#     return greeting


# r = requests.get("https://www.google.com")
# print(r.status_code)

# name = input("your name?")
# print("hello,", name)
# print("go good job")
# print("test2")
# print("test03")
# print("test04")
# print("test05")
