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
ppo-Pyramids-Training / Project /Assets /ML-Agents /TestScenes /TestCompressedTexture /TestTextureSensorComponent.cs
| using UnityEngine; | |
| using Unity.MLAgents.Sensors; | |
| public class TestTextureSensorComponent : SensorComponent | |
| { | |
| TestTextureSensor m_Sensor; | |
| public Texture2D TestTexture; | |
| string m_SensorName = "TextureSensor"; | |
| public string SensorName | |
| { | |
| get { return m_SensorName; } | |
| set { m_SensorName = value; } | |
| } | |
| public int ObservationStacks = 4; | |
| public SensorCompressionType CompressionType = SensorCompressionType.PNG; | |
| /// <inheritdoc/> | |
| public override ISensor[] CreateSensors() | |
| { | |
| m_Sensor = new TestTextureSensor(TestTexture, SensorName, CompressionType); | |
| if (ObservationStacks != 1) | |
| { | |
| return new ISensor[] { new StackingSensor(m_Sensor, ObservationStacks) }; | |
| } | |
| return new ISensor[] { m_Sensor }; | |
| } | |
| } | |