diff --git a/.floydexpt b/.floydexpt
new file mode 100644
index 0000000..398db57
--- /dev/null
+++ b/.floydexpt
@@ -0,0 +1 @@
+{"name": "cnn-test-visualized", "family_id": "qNGVhmKB7MjGF7oh6KSFPc"}
\ No newline at end of file
diff --git a/.floydignore b/.floydignore
new file mode 100644
index 0000000..02f9be9
--- /dev/null
+++ b/.floydignore
@@ -0,0 +1,14 @@
+
+# Directories and files to ignore when uploading code to floyd
+
+.git
+.eggs
+eggs
+lib
+lib64
+parts
+sdist
+var
+*.pyc
+*.swp
+.DS_Store
diff --git a/ConvolutionalNeuralNetwork.py b/ConvolutionalNeuralNetwork.py
index 4c1ed9d..2385377 100644
--- a/ConvolutionalNeuralNetwork.py
+++ b/ConvolutionalNeuralNetwork.py
@@ -1,5 +1,6 @@
 import tensorflow as tf
 from tensorflow.examples.tutorials.mnist import input_data
+import os
 
 mnist = input_data.read_data_sets("../MNIST_data/", one_hot=True)
 
@@ -116,9 +117,9 @@
 with tf.Session() as sess:
     sess.run(tf.global_variables_initializer())
 
-    training_writer = tf.summary.FileWriter("../LogsCNN/training", sess.graph)
-    testing_writer = tf.summary.FileWriter("../LogsCNN/testing", sess.graph)
-    accuracy_writer = tf.summary.FileWriter("../LogsCNN/accuracy", sess.graph)
+    training_writer = tf.summary.FileWriter("/output/training_log", sess.graph)
+    testing_writer = tf.summary.FileWriter("/output/testing_log", sess.graph)
+    accuracy_writer = tf.summary.FileWriter("/output/accuracy_log", sess.graph)
 
     for epoch in range(training_epochs):
         train_batch_data, train_batch_labels = mnist.train.next_batch(batch_size)
@@ -143,7 +144,7 @@
 
         if epoch % 100 == 0:
             print("Saving the model.")
-            save_path = saver.save(sess, "../saveCNN/trained_model" + str(epoch) + ".ckpt")
+            save_path = saver.save(sess, "/output/trained_model" + str(epoch) + ".ckpt")
 
     final_accuracy = sess.run(accuracy, feed_dict={X: mnist.test.images, Y: mnist.test.labels})