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sync stuff

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This commit is contained in:
Jonas Weinz 2023-05-14 20:45:24 +02:00
parent 9ed5f8bc3d
commit 41b5fa7d27
8 changed files with 232 additions and 0 deletions
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2
02_GraduallyDescentIntoTheSingularity/.gitattributes vendored Normal file
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# Normalize EOL for all files that Git considers text files.
* text=auto eol=lf

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02_GraduallyDescentIntoTheSingularity/.gitignore vendored Normal file
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# Godot 4+ specific ignores
.godot/

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02_GraduallyDescentIntoTheSingularity/2DScene.tscn Normal file
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[gd_scene load_steps=5 format=3 uid="uid://bdred3heq7qc6"]
[ext_resource type="Script" path="res://MLP.gd" id="1_m8mw3"]
[ext_resource type="Script" path="res://MLP_Visualization.gd" id="2_570bb"]
[sub_resource type="CircleShape2D" id="CircleShape2D_e4ydk"]
radius = 50.0
[sub_resource type="PlaceholderTexture2D" id="PlaceholderTexture2D_pd6fs"]
[node name="Node2D" type="Node2D"]
position = Vector2(534, 283)
[node name="RigidBody2D" type="RigidBody2D" parent="."]
[node name="CollisionShape2D" type="CollisionShape2D" parent="RigidBody2D"]
shape = SubResource("CircleShape2D_e4ydk")
[node name="Sprite2D" type="Sprite2D" parent="RigidBody2D"]
scale = Vector2(70.25, 64.25)
texture = SubResource("PlaceholderTexture2D_pd6fs")
[node name="MLP" type="Node" parent="."]
script = ExtResource("1_m8mw3")
[node name="MLP_Visualization" type="Node2D" parent="." node_paths=PackedStringArray("mlp")]
script = ExtResource("2_570bb")
mlp = NodePath("../MLP")

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02_GraduallyDescentIntoTheSingularity/MLP.gd Normal file
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extends Node
class_name MLP
@export var weights: Array[Array] = []
@export var biases: Array[Array] = []
@export var learning_rate: float = 0.01
func _init(sizes: Array = [3,2]) -> void:
randomize()
weights = []
biases = []
for i in range(sizes.size() - 1):
weights.append([])
biases.append([])
for _j in range(sizes[i]):
weights[i].append([])
for _k in range(sizes[i + 1]):
weights[i][_j].append(randf() * 2 - 1)
biases[i].append(randf() * 2 - 1)
# Feedforward: compute the output of the MLP for a given input.
func feedforward(input: Array) -> Array:
var a = input
for i in range(weights.size()):
var dp = dot_product(a, weights[i])
for j in range(a.size()):
a[j] = sigmoid(dp[j] + + biases[i][j])
return a
# Backpropagation: update the weights and biases based on the input and target output.
func backpropagate(input: Array, target: Array) -> void:
var nabla_b: Array = []
var nabla_w: Array = []
# Feedforward
var activation:Array[float] = input
var activations: Array[Array] = [input] # List to store all the activations, layer by layer
var zs: Array[Array] = [] # List to store all the z vectors, layer by layer
var z: int = 0
var sp: float = 0.0
var delta: Array = []
for i in range(weights.size()):
var dp = dot_product(activation, weights[i])
var zs_i:Array[float] = []
var activations_i: Array[float] = []
for j in range(dp.size()):
z = dp[j] + biases[i][j]
zs_i.append(z)
activations_i.append(sigmoid(z))
activation = activations_i
zs.append(zs_i)
activations.append(activations_i)
# Backward pass
sp = sigmoid_prime(zs[zs.size() - 1])
for cd in cost_derivative(activations[activations.size() - 1], target):
delta.append(cd * sp)
nabla_b.append(delta)
nabla_w.append(dot_product(delta, activations[activations.size() - 2].transpose()))
for l in range(2, weights.size() + 1):
z = zs[zs.size() - l]
sp = sigmoid_prime(z)
delta = []
for dp in dot_product(weights[weights.size() - l + 1].transpose(), delta):
delta.append(dp * sp)
nabla_b.append(delta)
nabla_w.append(dot_product(delta, activations[activations.size() - l - 1].transpose()))
# Update weights and biases
for i in range(weights.size()):
weights[i] -= learning_rate * nabla_w[nabla_w.size() - i - 1]
biases[i] -= learning_rate * nabla_b[nabla_b.size() - i - 1]
func sigmoid(x: float) -> float:
return 1.0 / (1.0 + exp(-x))
func sigmoid_prime(x: float) -> float:
return sigmoid(x) * (1 - sigmoid(x))
func cost_derivative(output_activations: Array, y: Array) -> Array:
var output: Array = []
for i in range(0, output_activations.size()):
output[i] = output_activations[i] - y[i]
return output
func dot_product(a: Array, b: Array) -> Array:
var result: Array = []
for i in range(a.size()):
var sum: float = 0.0
for j in range(a[i].size()):
sum += a[i][j] * b[j]
result.append(sum)
return result
# Called when the node enters the scene tree for the first time.
func _ready():
pass # Replace with function body.
# Called every frame. 'delta' is the elapsed time since the previous frame.
func _process(delta):
pass

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02_GraduallyDescentIntoTheSingularity/MLP_Visualization.gd Normal file
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extends Node2D
@export var mlp: MLP
@export var neuron_radius: float = 10.0
@export var space_between_layers: float = 100.0
@export var space_between_neurons: float = 50.0
@export var neuron_color = Color(1, 1, 1) # white
@export var connection_color = Color(0, 0, 1) # blue
func _draw():
if mlp:
var layer_position = Vector2(0, 0)
for i in range(mlp.weights.size()):
var neuron_position = Vector2(layer_position)
for j in range(mlp.weights[i].size()):
var neuron = mlp.weights[i][j]
# draw neuron
draw_circle(neuron_position, neuron_radius, neuron_color)
# draw connections to the next layer
if i < mlp.weights.size() - 1:
var next_layer_position = Vector2(layer_position.x + space_between_layers, 0)
for k in range(mlp.weights[i + 1].size()):
var next_neuron_position = Vector2(next_layer_position)
draw_line(neuron_position, next_neuron_position, connection_color)
next_layer_position.y += space_between_neurons
neuron_position.y += space_between_neurons
layer_position.x += space_between_layers
func update_mlp(new_mlp: MLP):
mlp = new_mlp

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02_GraduallyDescentIntoTheSingularity/icon.svg Normal file
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02_GraduallyDescentIntoTheSingularity/icon.svg.import Normal file
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importer="texture"
type="CompressedTexture2D"
uid="uid://dw0t8inj75cb5"
path="res://.godot/imported/icon.svg-218a8f2b3041327d8a5756f3a245f83b.ctex"
metadata={
"vram_texture": false
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[deps]
source_file="res://icon.svg"
dest_files=["res://.godot/imported/icon.svg-218a8f2b3041327d8a5756f3a245f83b.ctex"]
[params]
compress/mode=0
compress/high_quality=false
compress/lossy_quality=0.7
compress/hdr_compression=1
compress/normal_map=0
compress/channel_pack=0
mipmaps/generate=false
mipmaps/limit=-1
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roughness/src_normal=""
process/fix_alpha_border=true
process/premult_alpha=false
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process/hdr_as_srgb=false
process/hdr_clamp_exposure=false
process/size_limit=0
detect_3d/compress_to=1
svg/scale=1.0
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editor/convert_colors_with_editor_theme=false

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02_GraduallyDescentIntoTheSingularity/project.godot Normal file
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; Engine configuration file.
; It's best edited using the editor UI and not directly,
; since the parameters that go here are not all obvious.
;
; Format:
; [section] ; section goes between []
; param=value ; assign values to parameters
config_version=5
[application]
config/name="Gradually Descent Into The Singularity"
run/main_scene="res://2DScene.tscn"
config/features=PackedStringArray("4.0", "Forward Plus")
config/icon="res://icon.svg"
[physics]
2d/default_gravity=0.0