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 Float2DSensor : ISensor | |
| { | |
| public int Width { get; } | |
| public int Height { get; } | |
| string m_Name; | |
| private ObservationSpec m_ObservationSpec; | |
| public float[,] floatData; | |
| public Float2DSensor(int width, int height, string name) | |
| { | |
| Width = width; | |
| Height = height; | |
| m_Name = name; | |
| m_ObservationSpec = ObservationSpec.Visual(height, width, 1); | |
| floatData = new float[Height, Width]; | |
| } | |
| public Float2DSensor(float[,] floatData, string name) | |
| { | |
| this.floatData = floatData; | |
| Height = floatData.GetLength(0); | |
| Width = floatData.GetLength(1); | |
| m_Name = name; | |
| m_ObservationSpec = ObservationSpec.Visual(Height, Width, 1); | |
| } | |
| public string GetName() | |
| { | |
| return m_Name; | |
| } | |
| public ObservationSpec GetObservationSpec() | |
| { | |
| return m_ObservationSpec; | |
| } | |
| public byte[] GetCompressedObservation() | |
| { | |
| return null; | |
| } | |
| public int Write(ObservationWriter writer) | |
| { | |
| using (TimerStack.Instance.Scoped("Float2DSensor.Write")) | |
| { | |
| for (var h = 0; h < Height; h++) | |
| { | |
| for (var w = 0; w < Width; w++) | |
| { | |
| writer[h, w, 0] = floatData[h, w]; | |
| } | |
| } | |
| var numWritten = Height * Width; | |
| return numWritten; | |
| } | |
| } | |
| public void Update() { } | |
| public void Reset() { } | |
| public CompressionSpec GetCompressionSpec() | |
| { | |
| return CompressionSpec.Default(); | |
| } | |
| } | |
| public class FloatVisualSensorTests | |
| { | |
| [] | |
| public void TestFloat2DSensorWrite() | |
| { | |
| var sensor = new Float2DSensor(3, 4, "floatsensor"); | |
| for (var h = 0; h < 4; h++) | |
| { | |
| for (var w = 0; w < 3; w++) | |
| { | |
| sensor.floatData[h, w] = 3 * h + w; | |
| } | |
| } | |
| var output = new float[12]; | |
| var writer = new ObservationWriter(); | |
| writer.SetTarget(output, sensor.GetObservationSpec(), 0); | |
| sensor.Write(writer); | |
| for (var i = 0; i < 9; i++) | |
| { | |
| Assert.AreEqual(i, output[i]); | |
| } | |
| } | |
| [] | |
| public void TestFloat2DSensorExternalData() | |
| { | |
| var data = new float[4, 3]; | |
| var sensor = new Float2DSensor(data, "floatsensor"); | |
| Assert.AreEqual(sensor.Height, 4); | |
| Assert.AreEqual(sensor.Width, 3); | |
| } | |
| } | |
| } | |