Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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129 行
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using System.Collections.Generic;
using System.Text;
using UnityEditor;
using Unity.MLAgents.Demonstrations;
using Unity.MLAgents.Policies;
namespace Unity.MLAgents.Editor
{
/// <summary>
/// Renders a custom UI for DemonstrationSummary ScriptableObject.
/// </summary>
[CustomEditor(typeof(DemonstrationSummary))]
[CanEditMultipleObjects]
internal class DemonstrationEditor : UnityEditor.Editor
{
SerializedProperty m_BrainParameters;
SerializedProperty m_DemoMetaData;
SerializedProperty m_ObservationShapes;
void OnEnable()
{
m_BrainParameters = serializedObject.FindProperty("brainParameters");
m_DemoMetaData = serializedObject.FindProperty("metaData");
m_ObservationShapes = serializedObject.FindProperty("observationSummaries");
}
/// <summary>
/// Renders Inspector UI for Demonstration metadata.
/// </summary>
void MakeMetaDataProperty(SerializedProperty property)
{
var nameProp = property.FindPropertyRelative("demonstrationName");
var experiencesProp = property.FindPropertyRelative("numberSteps");
var episodesProp = property.FindPropertyRelative("numberEpisodes");
var rewardsProp = property.FindPropertyRelative("meanReward");
var nameLabel = nameProp.displayName + ": " + nameProp.stringValue;
var experiencesLabel = experiencesProp.displayName + ": " + experiencesProp.intValue;
var episodesLabel = episodesProp.displayName + ": " + episodesProp.intValue;
var rewardsLabel = rewardsProp.displayName + ": " + rewardsProp.floatValue;
EditorGUILayout.LabelField(nameLabel);
EditorGUILayout.LabelField(experiencesLabel);
EditorGUILayout.LabelField(episodesLabel);
EditorGUILayout.LabelField(rewardsLabel);
}
/// <summary>
/// Constructs label for a serialized integer array.
/// </summary>
static string BuildIntArrayLabel(SerializedProperty actionSizeProperty)
{
var actionSize = actionSizeProperty.arraySize;
var actionLabel = new StringBuilder("[ ");
for (var i = 0; i < actionSize; i++)
{
actionLabel.Append(actionSizeProperty.GetArrayElementAtIndex(i).intValue);
if (i < actionSize - 1)
{
actionLabel.Append(", ");
}
}
actionLabel.Append(" ]");
return actionLabel.ToString();
}
/// <summary>
/// Renders Inspector UI for BrainParameters of a DemonstrationSummary.
/// Only the Action size and type are used from the BrainParameters.
/// </summary>
void MakeActionsProperty(SerializedProperty property)
{
var actSizeProperty = property.FindPropertyRelative("VectorActionSize");
var actSpaceTypeProp = property.FindPropertyRelative("VectorActionSpaceType");
var vecActSizeLabel =
actSizeProperty.displayName + ": " + BuildIntArrayLabel(actSizeProperty);
var actSpaceTypeLabel = actSpaceTypeProp.displayName + ": " +
(SpaceType)actSpaceTypeProp.enumValueIndex;
EditorGUILayout.LabelField(vecActSizeLabel);
EditorGUILayout.LabelField(actSpaceTypeLabel);
}
/// <summary>
/// Render the observation shapes of a DemonstrationSummary.
/// </summary>
/// <param name="obsSummariesProperty"></param>
void MakeObservationsProperty(SerializedProperty obsSummariesProperty)
{
var shapesLabels = new List<string>();
var numObservations = obsSummariesProperty.arraySize;
for (var i = 0; i < numObservations; i++)
{
var summary = obsSummariesProperty.GetArrayElementAtIndex(i);
var shapeProperty = summary.FindPropertyRelative("shape");
shapesLabels.Add(BuildIntArrayLabel(shapeProperty));
}
var shapeLabel = $"Shapes: {string.Join(", ", shapesLabels)}";
EditorGUILayout.LabelField(shapeLabel);
}
public override void OnInspectorGUI()
{
serializedObject.Update();
EditorGUILayout.LabelField("Meta Data", EditorStyles.boldLabel);
EditorGUI.indentLevel++;
MakeMetaDataProperty(m_DemoMetaData);
EditorGUI.indentLevel--;
EditorGUILayout.LabelField("Observations", EditorStyles.boldLabel);
EditorGUI.indentLevel++;
MakeObservationsProperty(m_ObservationShapes);
EditorGUI.indentLevel--;
EditorGUILayout.LabelField("Actions", EditorStyles.boldLabel);
EditorGUI.indentLevel++;
MakeActionsProperty(m_BrainParameters);
EditorGUI.indentLevel--;
serializedObject.ApplyModifiedProperties();
}
}
}