From 1b9872187d386235388566ff200a68b0e0332d5c Mon Sep 17 00:00:00 2001
From: Michael Mandl <mandlm@molez.net>
Date: Thu, 27 Dec 2018 16:47:45 +0100
Subject: [PATCH] Initial commit

---
 flow.py | 51 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 51 insertions(+)
 create mode 100755 flow.py

diff --git a/flow.py b/flow.py
new file mode 100755
index 0000000..62a8ca3
--- /dev/null
+++ b/flow.py
@@ -0,0 +1,51 @@
+#!/usr/bin/python3
+
+import tensorflow as tf
+from tensorflow import keras
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+import random
+
+print(tf.__version__)
+
+fashion_mnist = keras.datasets.fashion_mnist
+
+(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
+
+train_images = train_images / 255.0
+test_images = test_images / 255.0
+
+class_names = [
+    "T-shirt/top",
+    "Trouser",
+    "Pullover",
+    "Dress",
+    "Coat",
+    "Sandal",
+    "Shirt",
+    "Sneaker",
+    "Bag",
+    "Ankle boot",
+]
+
+model = keras.Sequential(
+    [
+        keras.layers.Flatten(input_shape=(28, 28)),
+        keras.layers.Dense(128, activation=tf.nn.relu),
+        keras.layers.Dense(10, activation=tf.nn.softmax),
+    ]
+)
+
+model.compile(
+    optimizer=tf.train.AdamOptimizer(),
+    loss="sparse_categorical_crossentropy",
+    metrics=["accuracy"],
+)
+
+model.fit(train_images, train_labels, epochs=5)
+
+test_loss, test_acc = model.evaluate(test_images, test_labels)
+
+print("Test accuracy:", test_acc)