Reinforcement Learning
ml-agents
TensorBoard
ONNX
Pyramids
deep-reinforcement-learning
ML-Agents-Pyramids
Instructions to use AnnaMats/ppo-Pyramids-Training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use AnnaMats/ppo-Pyramids-Training with ml-agents:
mlagents-load-from-hf --repo-id="AnnaMats/ppo-Pyramids-Training" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
| using NUnit.Framework; | |
| using Unity.MLAgents.Inference.Utils; | |
| namespace Unity.MLAgents.Tests | |
| { | |
| public class MultinomialTest | |
| { | |
| [] | |
| public void TestDim1() | |
| { | |
| var m = new Multinomial(2018); | |
| var cdf = new[] { 1f }; | |
| Assert.AreEqual(0, m.Sample(cdf)); | |
| Assert.AreEqual(0, m.Sample(cdf)); | |
| Assert.AreEqual(0, m.Sample(cdf)); | |
| } | |
| [] | |
| public void TestDim1Unscaled() | |
| { | |
| var m = new Multinomial(2018); | |
| var cdf = new[] { 0.1f }; | |
| Assert.AreEqual(0, m.Sample(cdf)); | |
| Assert.AreEqual(0, m.Sample(cdf)); | |
| Assert.AreEqual(0, m.Sample(cdf)); | |
| } | |
| [] | |
| public void TestDim3() | |
| { | |
| var m = new Multinomial(2018); | |
| var cdf = new[] { 0.1f, 0.3f, 1.0f }; | |
| Assert.AreEqual(2, m.Sample(cdf)); | |
| Assert.AreEqual(2, m.Sample(cdf)); | |
| Assert.AreEqual(2, m.Sample(cdf)); | |
| Assert.AreEqual(1, m.Sample(cdf)); | |
| } | |
| [] | |
| public void TestDim3Unscaled() | |
| { | |
| var m = new Multinomial(2018); | |
| var cdf = new[] { 0.05f, 0.15f, 0.5f }; | |
| Assert.AreEqual(2, m.Sample(cdf)); | |
| Assert.AreEqual(2, m.Sample(cdf)); | |
| Assert.AreEqual(2, m.Sample(cdf)); | |
| Assert.AreEqual(1, m.Sample(cdf)); | |
| } | |
| } | |
| } | |