AnimG

Neural Network Forward Pass

受众: Software Engineer类别: Cs

简介

Visualizes a forward pass through a [3, 4, 4, 2] neural network. Input activations propagate layer by layer through weighted connections, showing the weighted sum computation and activation function at each layer. The output layer applies softmax. Active neurons glow to indicate high activation values.

Neural Network Forward Pass

Description

Visualizes a forward pass through a [3, 4, 4, 2] neural network. Input activations propagate layer by layer through weighted connections, showing the weighted sum computation and activation function at each layer. The output layer applies softmax. Active neurons glow to indicate high activation values.

Phases

# Phase Name Duration Description
1 Intro 3s Title and network architecture displayed
2 Input Layer 4s Input values [0.5, 0.8, 0.3] shown at input neurons
3 Layer 1 Forward 10s Edges animate flowing to hidden layer 1; weighted sum and ReLU shown
4 Layer 2 Forward 8s Same for hidden layer 2
5 Output Layer 6s Output neurons computed; softmax applied
6 Prediction 5s Winning class highlighted; probability shown
7 Weight Matrix 6s Brief display of matrix multiplication representation
8 Outro 4s Full network with all activations visible

Layout

+--------------------------------------------------+
|  Title: Neural Network Forward Pass              |
+--------------------------------------------------+
|                                                  |
|  o           o   o   o   o       o   o           |
|  o  ------>  o   o   o   o  -->  o   o  (output) |
|  o           o   o   o   o       o   o           |
|              (hidden 1)  (hidden 2)              |
|                                                  |
|  Layer equation: z = Wx + b                      |
|  Activation:     a = ReLU(z)                     |
|                                                  |
|  Softmax output (bottom):                        |
|  Class 0: 0.73   Class 1: 0.27                   |
+--------------------------------------------------+

Area Descriptions

  • Center: Network diagram with neurons as circles and weighted edges
  • Bottom: Equation panel showing z=Wx+b and activation
  • Right: Output class probabilities

Assets & Dependencies

  • Fonts: LaTeX / sans-serif
  • Manim version: ManimCE 0.19.1

Notes

  • Neurons glow (bright fill) when activated with high values
  • Edge thickness/opacity proportional to weight magnitude
  • Show weight labels on a few selected edges
  • Matrix multiplication notation shown as a panel
Neural Network Forward Pass for Software Engineer in Cs | AnimG Library