Added GAN visualization.

examples/variational_autoencoder/variational_autoencoder.py

@@ -8,7 +8,12 @@ from manim import *
 import pickle
 import numpy as np
 import os
+from PIL import Image
 import manim_ml.neural_network as neural_network
+from manim_ml.neural_network.embedding import EmbeddingLayer
+from manim_ml.neural_network.feed_forward import FeedForwardLayer
+from manim_ml.neural_network.image import ImageLayer
+from manim_ml.neural_network.neural_network import NeuralNetwork
 
 class VariationalAutoencoder(VGroup):
     """Variational Autoencoder Manim Visualization"""
@@ -239,6 +244,29 @@ class VariationalAutoencoder(VGroup):
 
         return animation_group
 
+class VariationalAutoencoder(VGroup):
+
+    def __init__(self):
+        embedding_layer = EmbeddingLayer()
+        
+        image = Image.open('images/image.jpeg')
+        numpy_image = np.asarray(image)
+        # Make nn
+        neural_network = NeuralNetwork([
+            ImageLayer(numpy_image, height=1.4),
+            FeedForwardLayer(5),
+            FeedForwardLayer(3),
+            embedding_layer,
+            FeedForwardLayer(3),
+            FeedForwardLayer(5),
+            ImageLayer(numpy_image, height=1.4),
+        ])
+
+        neural_network.scale(1.3)
+
+        self.play(Create(neural_network))
+        self.play(neural_network.make_forward_pass_animation(run_time=15))
+
 class MNISTImageHandler():
     """Deals with loading serialized VAE mnist images from "autoencoder_models" """
 
@@ -295,19 +323,4 @@ class VAEScene(Scene):
         # Interpolation animation
         interpolation_images = mnist_image_handler.interpolation_images
         interpolation_animation = vae.make_interpolation_animation(interpolation_images)
-        self.play(interpolation_animation)
-
-class VAEImage(Scene):
-
-    def construct(self):
-        # Set Scene config
-        vae = VariationalAutoencoder()
-        mnist_image_handler = MNISTImageHandler()
-        image_pair = mnist_image_handler.image_pairs[3]
-        vae.move_to(ORIGIN)
-        vae.scale(1.3)
-        self.play(Create(vae), run_time=3)
-        # Make a forward pass animation
-        forward_pass_animation = vae.make_forward_pass_animation(image_pair)
-        self.play(forward_pass_animation)
- 
+        self.play(interpolation_animation)