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Made new neural network forward pass animation

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This commit is contained in:
Alec Helbling
2022-03-28 21:24:49 -04:00
committed by Alec Helbling
parent 3be5c54d26
commit 068b0746f0
2 changed files with 49 additions and 51 deletions
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41
manim_ml/logo.py
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@ -1,41 +0,0 @@
"""
Logo for Manim Machine Learning
"""
from manim import *
from neural_network import NeuralNetwork
config.pixel_height = 500
config.pixel_width = 1920
config.frame_height = 10.0
config.frame_width = 10.0
class ManimMLLogo(Scene):
def construct(self):
self.text = Text("ManimML")
self.text.scale(1.3)
self.neural_network = NeuralNetwork([3, 5, 3, 6, 3], layer_spacing=0.6, node_color=BLUE)
self.neural_network.scale(0.8)
self.neural_network.move_to(self.text.get_right())
self.neural_network.shift(RIGHT * 1.3)
self.logo_group = VGroup(self.text, self.neural_network)
self.logo_group.scale(1.5)
self.logo_group.move_to(ORIGIN)
self.play(Write(self.text))
self.play(Create(self.neural_network))
# self.surrounding_rectangle = SurroundingRectangle(self.logo_group, buff=0.3, color=BLUE)
underline = Underline(self.text, color=BLUE)
animation_group = AnimationGroup(
self.neural_network.make_forward_propagation_animation(run_time=5),
Create(underline),
# Create(self.surrounding_rectangle)
)
# self.surrounding_rectangle = SurroundingRectangle(self.logo_group, buff=0.3, color=BLUE)
underline = Underline(self.text, color=BLUE)
animation_group = AnimationGroup(
self.neural_network.make_forward_propagation_animation(run_time=5),
Create(underline),
# Create(self.surrounding_rectangle)
)
self.play(animation_group)
self.wait(5)

57
manim_ml/neural_network.py
View File

@ -10,6 +10,18 @@ Example:
NeuralNetwork(layer_node_count) NeuralNetwork(layer_node_count)
""" """
from manim import * from manim import *
from matplotlib import animation
class ChangeColor(Animation):
CONFIG={
"rate_func":linear
}
def interpolate_submobject(self, submobject, starting_sumobject, alpha):
m = int(alpha * 10) % 2
if m == 0:
submobject.set_color(RED)
else:
submobject.set_color(YELLOW)
class NeuralNetworkLayer(VGroup): class NeuralNetworkLayer(VGroup):
"""Handles rendering a layer for a neural network""" """Handles rendering a layer for a neural network"""
@ -18,7 +30,7 @@ class NeuralNetworkLayer(VGroup):
self, num_nodes, layer_buffer=SMALL_BUFF/2, node_radius=0.08, self, num_nodes, layer_buffer=SMALL_BUFF/2, node_radius=0.08,
node_color=BLUE, node_outline_color=WHITE, rectangle_color=WHITE, node_color=BLUE, node_outline_color=WHITE, rectangle_color=WHITE,
node_spacing=0.3, rectangle_fill_color=BLACK, node_stroke_width=2.0, node_spacing=0.3, rectangle_fill_color=BLACK, node_stroke_width=2.0,
rectangle_stroke_width=2.0): rectangle_stroke_width=2.0, animation_dot_color=RED):
super(VGroup, self).__init__() super(VGroup, self).__init__()
self.num_nodes = num_nodes self.num_nodes = num_nodes
self.layer_buffer = layer_buffer self.layer_buffer = layer_buffer
@ -30,6 +42,7 @@ class NeuralNetworkLayer(VGroup):
self.rectangle_color = rectangle_color self.rectangle_color = rectangle_color
self.node_spacing = node_spacing self.node_spacing = node_spacing
self.rectangle_fill_color = rectangle_fill_color self.rectangle_fill_color = rectangle_fill_color
self.animation_dot_color = animation_dot_color
self.node_group = VGroup() self.node_group = VGroup()
@ -54,6 +67,16 @@ class NeuralNetworkLayer(VGroup):
# Add the objects to the class # Add the objects to the class
self.add(surrounding_rectangle, self.node_group) self.add(surrounding_rectangle, self.node_group)
def _make_highlight_nodes_animation(self):
# make highlight animation
succession = Succession(
ApplyMethod(self.node_group.set_color, self.animation_dot_color, run_time=0.25),
Wait(1.0),
ApplyMethod(self.node_group.set_color, self.node_color, run_time=0.25),
)
return succession
class NeuralNetwork(VGroup): class NeuralNetwork(VGroup):
def __init__( def __init__(
@ -84,7 +107,11 @@ class NeuralNetwork(VGroup):
layers = VGroup() layers = VGroup()
# Create each layer # Create each layer
for layer_index, node_count in enumerate(self.layer_node_count): for layer_index, node_count in enumerate(self.layer_node_count):
layer = NeuralNetworkLayer(node_count, node_color=self.node_color) layer = NeuralNetworkLayer(
node_count,
node_color=self.node_color,
animation_dot_color=self.animation_dot_color
)
# Manage spacing # Manage spacing
layer.move_to([self.layer_spacing * layer_index, 0, 0]) layer.move_to([self.layer_spacing * layer_index, 0, 0])
# Add layer to VGroup # Add layer to VGroup
@ -110,12 +137,12 @@ class NeuralNetwork(VGroup):
edge_layers.set_z_index(0) edge_layers.set_z_index(0)
return edge_layers return edge_layers
def make_forward_propagation_animation(self, run_time=2): def make_forward_propagation_animation(self, run_time=2, passing_flash = True):
"""Generates an animation for feed forward propogation""" """Generates an animation for feed forward propogation"""
all_animations = [] all_animations = []
per_layer_run_time = run_time / len(self.edge_layers) per_layer_run_time = run_time / len(self.edge_layers)
self.dots = VGroup() self.dots = VGroup()
for edge_layer in self.edge_layers: for i, edge_layer in enumerate(self.edge_layers):
path_animations = [] path_animations = []
for edge in edge_layer: for edge in edge_layer:
dot = Dot(color=self.animation_dot_color, fill_opacity=1.0, radius=self.dot_radius) dot = Dot(color=self.animation_dot_color, fill_opacity=1.0, radius=self.dot_radius)
@ -124,12 +151,24 @@ class NeuralNetwork(VGroup):
# Add to dots group # Add to dots group
self.dots.add(dot) self.dots.add(dot)
# Make the animation # Make the animation
if passing_flash:
anim = ShowPassingFlash(edge.copy().set_color(self.animation_dot_color), time_width=0.2, run_time=3)
else:
anim = MoveAlongPath(dot, edge, run_time=per_layer_run_time, rate_function=sigmoid) anim = MoveAlongPath(dot, edge, run_time=per_layer_run_time, rate_function=sigmoid)
path_animations.append(anim) path_animations.append(anim)
# Highlight each node
layer = self.layers[i]
highlight_animation = layer._make_highlight_nodes_animation()
all_animations.append(highlight_animation)
path_animation_group = AnimationGroup(*path_animations) path_animation_group = AnimationGroup(*path_animations)
all_animations.append(path_animation_group) all_animations.append(path_animation_group)
animation_group = AnimationGroup(*all_animations, run_time=run_time, lag_ratio=1) layer = self.layers[-1]
highlight_animation = layer._make_highlight_nodes_animation()
all_animations.append(highlight_animation)
animation_group = AnimationGroup(*all_animations, run_time=run_time, lag_ratio=1.0)
return animation_group return animation_group
@ -148,10 +187,10 @@ class TestNeuralNetworkScene(Scene):
nn.move_to(ORIGIN) nn.move_to(ORIGIN)
# Make Animation # Make Animation
self.add(nn) self.add(nn)
forward_propagation_animation = nn.make_forward_propagation_animation() forward_propagation_animation = nn.make_forward_propagation_animation(5)
second_nn = NeuralNetwork([3, 4]) # second_nn = NeuralNetwork([3, 4])
self.add(second_nn) # self.add(second_nn)
self.play(forward_propagation_animation) self.play(forward_propagation_animation)
self.play(second_nn.make_forward_propagation_animation()) # self.play(second_nn.make_forward_propagation_animation())