can use GPU

Author: whyboris

gan.py

@@ -63,8 +63,8 @@
 
 discriminator.trainable = False
 
-gan_input = keras.Input(shape=(latent_dim,)) 
-gan_output = discriminator(generator(gan_input)) 
+gan_input = keras.Input(shape=(latent_dim,))
+gan_output = discriminator(generator(gan_input))
 gan = keras.models.Model(gan_input, gan_output)
 
 gan_optimizer = keras.optimizers.RMSprop(lr=0.0004, clipvalue=1.0, decay=1e-8)
@@ -92,7 +92,7 @@
     random_latent_vectors = np.random.normal(size=(batch_size, latent_dim))
 
     generated_images = generator.predict(random_latent_vectors)
-    
+
     stop = start + batch_size
     real_images = x_train[start: stop]
     combined_images = np.concatenate([generated_images, real_images])

gpu.py

@@ -0,0 +1,5 @@
+print('checking what CPU / GPU you have available for Keras & Tensorflow')
+
+from tensorflow.python.client import device_lib
+print(device_lib.list_local_devices())
+

requirements.txt

@@ -7,5 +7,9 @@ numpy==1.13.0
 opencv-python
 pylint
 tensorflow
+# get that GPU speed!
+tensorflow-gpu
 # html5lib newer version needed to get tensorboard to work
-html5lib==1.0.1
+html5lib==1.0.1
+# required for PIL -- image manipulation, at least in gan.py
+pillow