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.Sensors; | |
| namespace Unity.MLAgents.Tests | |
| { | |
| [] | |
| public class CompressionSpecTests | |
| { | |
| [] | |
| public void TestIsTrivialMapping() | |
| { | |
| Assert.IsTrue(CompressionSpec.Default().IsTrivialMapping()); | |
| var spec = new CompressionSpec(SensorCompressionType.PNG, null); | |
| Assert.AreEqual(spec.IsTrivialMapping(), true); | |
| spec = new CompressionSpec(SensorCompressionType.PNG, new[] { 0, 0, 0 }); | |
| Assert.AreEqual(spec.IsTrivialMapping(), true); | |
| spec = new CompressionSpec(SensorCompressionType.PNG, new[] { 0, 1, 2, 3, 4 }); | |
| Assert.AreEqual(spec.IsTrivialMapping(), true); | |
| spec = new CompressionSpec(SensorCompressionType.PNG, new[] { 1, 2, 3, 4, -1, -1 }); | |
| Assert.AreEqual(spec.IsTrivialMapping(), false); | |
| spec = new CompressionSpec(SensorCompressionType.PNG, new[] { 0, 0, 0, 1, 1, 1 }); | |
| Assert.AreEqual(spec.IsTrivialMapping(), false); | |
| } | |
| } | |
| } | |