NOT logical problem with Tensorflow

TensorflowNOT.py

from __future__ import absolute_import, division, print_function

import tensorflow as tf
import tflearn

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

# Logical NOT operator
X = [[0.], [1.]]
Y = [[1.], [0.]]

# Graph definition
with tf.Graph().as_default():
    g = tflearn.input_data(shape=[None, 1])
    g = tflearn.fully_connected(g, 128, activation='linear')
    g = tflearn.fully_connected(g, 128, activation='linear')
    g = tflearn.fully_connected(g, 1, activation='sigmoid')
    g = tflearn.regression(g, optimizer='sgd', learning_rate=2.,
                           loss='mean_square')

    # Model training
    m = tflearn.DNN(g)
    m.fit(X, Y, n_epoch=100, snapshot_epoch=False)

    # Test model
    print("Testing NOT operator")
    print("NOT 0:", round(m.predict([[0.]])))
    print("NOT 1:", round(m.predict([[1.]])))