Bug fixes and linting for the activation functions addition.

examples/cnn/activation_functions.py

@@ -0,0 +1,75 @@
+from pathlib import Path
+
+from manim import *
+from PIL import Image
+
+from manim_ml.neural_network.layers.convolutional_2d import Convolutional2DLayer
+from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
+from manim_ml.neural_network.layers.image import ImageLayer
+from manim_ml.neural_network.neural_network import NeuralNetwork
+
+# Make the specific scene
+config.pixel_height = 1200
+config.pixel_width = 1900
+config.frame_height = 7.0
+config.frame_width = 7.0
+ROOT_DIR = Path(__file__).parents[2]
+
+def make_code_snippet():
+    code_str = """
+        # Make the neural network
+        nn = NeuralNetwork([
+            # ... Layers at start
+            Convolutional2DLayer(3, 5, 3, activation_function="ReLU"),
+            # ... Layers at end
+        ])
+        # Play the animation
+        self.play(nn.make_forward_pass_animation()) 
+    """
+
+    code = Code(
+        code=code_str,
+        tab_width=4,
+        background_stroke_width=1,
+        background_stroke_color=WHITE,
+        insert_line_no=False,
+        style="monokai",
+        font="Monospace",
+        background="window",
+        language="py",
+    )
+    code.scale(0.45)
+
+    return code
+
+class CombinedScene(ThreeDScene):
+    def construct(self):
+        image = Image.open(ROOT_DIR / "assets/mnist/digit.jpeg")
+        numpy_image = np.asarray(image)
+        # Make nn
+        nn = NeuralNetwork(
+            [
+                ImageLayer(numpy_image, height=1.5),
+                Convolutional2DLayer(1, 7),
+                Convolutional2DLayer(3, 5, 3, activation_function="ReLU"),
+                Convolutional2DLayer(5, 3, 3, activation_function="ReLU"),
+                FeedForwardLayer(3),
+                FeedForwardLayer(1),
+            ],
+            layer_spacing=0.25,
+        )
+        # nn.scale(0.7)
+        # Center the nn
+        nn.move_to(ORIGIN)
+        self.add(nn)
+        # Make code snippet
+        code = make_code_snippet()
+        code.next_to(nn, DOWN)
+        self.add(code)
+        nn.move_to(ORIGIN)
+        # Move everything up
+        Group(nn, code).move_to(ORIGIN)
+        # Play animation
+        forward_pass = nn.make_forward_pass_animation()
+        self.wait(1)
+        self.play(forward_pass)