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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118 行
5.0 KiB

using System.Collections;
using System.Collections.Generic;
using UnityEngine;
using UnityEditor;
using System.Linq;
namespace MLAgents
{
/*
This code is meant to modify the behavior of the inspector on Brain Components.
Depending on the type of brain that is used, the available fields will be modified in the inspector accordingly.
*/
[CustomEditor(typeof(Brain))]
public class BrainEditor : Editor
{
[SerializeField] bool _Foldout = true;
public override void OnInspectorGUI()
{
Brain myBrain = (Brain) target;
SerializedObject serializedBrain = serializedObject;
if (myBrain.transform.parent == null)
{
EditorGUILayout.HelpBox(
"A Brain GameObject must be a child of an Academy GameObject!",
MessageType.Error);
}
else if (myBrain.transform.parent.GetComponent<Academy>() == null)
{
EditorGUILayout.HelpBox(
"The Parent of a Brain must have an Academy Component attached to it!",
MessageType.Error);
}
BrainParameters parameters = myBrain.brainParameters;
if (parameters.vectorActionDescriptions == null ||
parameters.vectorActionDescriptions.Length != parameters.vectorActionSize)
parameters.vectorActionDescriptions = new string[parameters.vectorActionSize];
serializedBrain.Update();
_Foldout = EditorGUILayout.Foldout(_Foldout, "Brain Parameters");
int indentLevel = EditorGUI.indentLevel;
if (_Foldout)
{
EditorGUI.indentLevel++;
EditorGUILayout.LabelField("Vector Observation");
EditorGUI.indentLevel++;
SerializedProperty bpVectorObsSize =
serializedBrain.FindProperty("brainParameters.vectorObservationSize");
EditorGUILayout.PropertyField(bpVectorObsSize, new GUIContent("Space Size",
"Length of state " +
"vector for brain (In Continuous state space)." +
"Or number of possible values (in Discrete state space)."));
SerializedProperty bpNumStackedVectorObs =
serializedBrain.FindProperty("brainParameters.numStackedVectorObservations");
EditorGUILayout.PropertyField(bpNumStackedVectorObs, new GUIContent(
"Stacked Vectors", "Number of states that" +
" will be stacked before beeing fed to the neural network."));
EditorGUI.indentLevel--;
SerializedProperty bpCamResol =
serializedBrain.FindProperty("brainParameters.cameraResolutions");
EditorGUILayout.PropertyField(bpCamResol, new GUIContent("Visual Observation",
"Describes height, " +
"width, and whether to greyscale visual observations for the Brain."), true);
EditorGUILayout.LabelField("Vector Action");
EditorGUI.indentLevel++;
SerializedProperty bpVectorActionType =
serializedBrain.FindProperty("brainParameters.vectorActionSpaceType");
EditorGUILayout.PropertyField(bpVectorActionType, new GUIContent("Space Type",
"Corresponds to whether state" +
" vector contains a single integer (Discrete) " +
"or a series of real-valued floats (Continuous)."));
SerializedProperty bpVectorActionSize =
serializedBrain.FindProperty("brainParameters.vectorActionSize");
EditorGUILayout.PropertyField(bpVectorActionSize, new GUIContent("Space Size",
"Length of action vector " +
"for brain (In Continuous state space)." +
"Or number of possible values (In Discrete action space)."));
SerializedProperty bpVectorActionDescription =
serializedBrain.FindProperty("brainParameters.vectorActionDescriptions");
EditorGUILayout.PropertyField(bpVectorActionDescription, new GUIContent(
"Action Descriptions", "A list of strings used to name" +
" the available actions for the Brain."), true);
}
EditorGUI.indentLevel = indentLevel;
SerializedProperty bt = serializedBrain.FindProperty("brainType");
EditorGUILayout.PropertyField(bt);
if (bt.enumValueIndex < 0)
{
bt.enumValueIndex = (int) BrainType.Player;
}
serializedBrain.ApplyModifiedProperties();
myBrain.UpdateCoreBrains();
myBrain.coreBrain.OnInspector();
#if !NET_4_6 && ENABLE_TENSORFLOW
EditorGUILayout.HelpBox ("You cannot have ENABLE_TENSORFLOW without NET_4_6", MessageType.Error);
#endif
}
}
}