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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Control Flow
Step1:  NOTE on notation
* _x, _y, _z, ...
Step2:  Q5. Given x, return the truth value of NOT x element-wise.
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Python Code:
from __future__ import print_function
import tensorflow as tf
import numpy as np
from datetime import date
date.today()
author = "kyubyong. https://github.com/Kyubyong/tensorflow-exercises"
tf.__version__
np.__version__
sess = tf.InteractiveSession()
Explanation: Control Flow
End of explanation
x = tf.constant([True, False, False], tf.bool)
y = tf.constant([True, True, False], tf.bool)
Explanation: NOTE on notation
* _x, _y, _z, ...: NumPy 0-d or 1-d arrays
* _X, _Y, _Z, ...: NumPy 2-d or higer dimensional arrays
* x, y, z, ...: 0-d or 1-d tensors
* X, Y, Z, ...: 2-d or higher dimensional tensors
Control Flow Operations
Q1. Let x and y be random 0-D tensors. Return x + y 
if x < y and x - y otherwise.
Q2. Let x and y be 0-D int32 tensors randomly selected from 0 to 5. Return x + y 2 if x < y, x - y elif x > y, 0 otherwise.
Q3. Let X be a tensor [[-1, -2, -3], [0, 1, 2]] and Y be a tensor of zeros with the same shape as X. Return a boolean tensor that yields True if X equals Y elementwise.
Logical Operators
Q4. Given x and y below, return the truth value x AND/OR/XOR y element-wise.
End of explanation
x = tf.constant([True, False, False], tf.bool)
Explanation: Q5. Given x, return the truth value of NOT x element-wise.
End of explanation
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