# -*- coding: utf-8 -*-
"""
Created on Fri Sep 15 21:59:00 2017

@author: ellie
"""

from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
import numpy as np

n_input = 784  # MNIST data input (img shape: 28*28)
n_classes = 10  # MNIST total classes (0-9 digits)

# Import MNIST data
mnist = input_data.read_data_sets('/datasets/ud730/mnist', one_hot=True)

# The features are already scaled and the data is shuffled
train_features = mnist.train.images
test_features = mnist.test.images

train_labels = mnist.train.labels.astype(np.float32)
test_labels = mnist.test.labels.astype(np.float32)

# Weights & bias
weights = tf.Variable(tf.random_normal([n_input, n_classes]))
bias = tf.Variable(tf.random_normal([n_classes]))

# Features and Labels
features = tf.placeholder(tf.float32, [None, n_input])
labels = tf.placeholder(tf.float32, [None, n_classes])

# 4 Samples of features
example_features = [
    ['F11','F12','F13','F14'],
    ['F21','F22','F23','F24'],
    ['F31','F32','F33','F34'],
    ['F41','F42','F43','F44']]
# 4 Samples of labels
example_labels = [
    ['L11','L12'],
    ['L21','L22'],
    ['L31','L32'],
    ['L41','L42']]