Files
ManimML/manim_ml/neural_network/feed_forward.py
2022-04-14 00:33:00 -04:00

129 lines
5.1 KiB
Python

from manim import *
from manim_ml.neural_network.layers import VGroupNeuralNetworkLayer, ConnectiveLayer
class FeedForwardLayer(VGroupNeuralNetworkLayer):
"""Handles rendering a layer for a neural network"""
def __init__(self, num_nodes, layer_buffer=SMALL_BUFF/2, node_radius=0.08,
node_color=BLUE, node_outline_color=WHITE, rectangle_color=WHITE,
node_spacing=0.3, rectangle_fill_color=BLACK, node_stroke_width=2.0,
rectangle_stroke_width=2.0, animation_dot_color=RED):
super(VGroupNeuralNetworkLayer, self).__init__()
self.num_nodes = num_nodes
self.layer_buffer = layer_buffer
self.node_radius = node_radius
self.node_color = node_color
self.node_stroke_width = node_stroke_width
self.node_outline_color = node_outline_color
self.rectangle_stroke_width = rectangle_stroke_width
self.rectangle_color = rectangle_color
self.node_spacing = node_spacing
self.rectangle_fill_color = rectangle_fill_color
self.animation_dot_color = animation_dot_color
self.node_group = VGroup()
self._construct_neural_network_layer()
def _construct_neural_network_layer(self):
"""Creates the neural network layer"""
# Add Nodes
for node_number in range(self.num_nodes):
node_object = Circle(radius=self.node_radius, color=self.node_color,
stroke_width=self.node_stroke_width)
self.node_group.add(node_object)
# Space the nodes
# Assumes Vertical orientation
for node_index, node_object in enumerate(self.node_group):
location = node_index * self.node_spacing
node_object.move_to([0, location, 0])
# Create Surrounding Rectangle
self.surrounding_rectangle = SurroundingRectangle(self.node_group, color=self.rectangle_color,
fill_color=self.rectangle_fill_color, fill_opacity=1.0,
buff=self.layer_buffer, stroke_width=self.rectangle_stroke_width)
# Add the objects to the class
self.add(self.surrounding_rectangle, self.node_group)
def make_forward_pass_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
@override_animation(Create)
def _create_animation(self, **kwargs):
animations = []
animations.append(Create(self.surrounding_rectangle))
for node in self.node_group:
animations.append(Create(node))
animation_group = AnimationGroup(*animations, lag_ratio=0.0)
return animation_group
class FeedForwardToFeedForward(ConnectiveLayer):
"""Layer for connecting FeedForward layer to FeedForwardLayer"""
def __init__(self, input_layer, output_layer, passing_flash=True,
dot_radius=0.05, animation_dot_color=RED, edge_color=WHITE,
edge_width=0.5):
super().__init__(input_layer, output_layer)
self.passing_flash = passing_flash
self.edge_color = edge_color
self.dot_radius = dot_radius
self.animation_dot_color = animation_dot_color
self.edge_width = edge_width
self.edges = self.construct_edges()
self.add(self.edges)
def construct_edges(self):
# Go through each node in the two layers and make a connecting line
edges = []
for node_i in self.input_layer.node_group:
for node_j in self.output_layer.node_group:
line = Line(node_i.get_center(), node_j.get_center(),
color=self.edge_color, stroke_width=self.edge_width)
edges.append(line)
edges = VGroup(*edges)
return edges
def make_forward_pass_animation(self, run_time=1):
"""Animation for passing information from one FeedForwardLayer to the next"""
path_animations = []
dots = []
for edge in self.edges:
dot = Dot(color=self.animation_dot_color, fill_opacity=1.0, radius=self.dot_radius)
# Add to dots group
dots.append(dot)
# Make the animation
if self.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=run_time, rate_function=sigmoid)
path_animations.append(anim)
if not self.passing_flash:
dots = VGroup(*dots)
self.add(dots)
path_animations = AnimationGroup(*path_animations)
return path_animations
@override_animation(Create)
def _create_animation(self, **kwargs):
animations = []
for edge in self.edges:
animations.append(Create(edge))
animation_group = AnimationGroup(*animations, lag_ratio=0.0)
return animation_group