Delete near Enemy Detect future. Use different density sensor.
Unity: No more detect Closest enemy info. Add different density sensor let agent get more state information on the center of view. Adjust Start Scene UI manager. Add in game visible rayCast & information that rayCast detect. Python: Start use mypy black and flake8 to format Python.
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@ -77,4 +77,5 @@ crashlytics-build.properties
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/Aimbot-PPO-Python/PPO-Model/
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|
||||
LoadDirDate = DataTransfer.LoadDirDate;
|
||||
LoadDirTime = DataTransfer.LoadDirTime;
|
||||
LoadDirDateF = float.Parse(LoadDirDate);
|
||||
loadDirTimeF = float.Parse(LoadDirTime);
|
||||
|
||||
// get load directory.
|
||||
LoadDirDate = DataTransfer.LoadDirDate;
|
||||
LoadDirTime = DataTransfer.LoadDirTime;
|
||||
LoadDirDateF = float.Parse(LoadDirDate);
|
||||
loadDirTimeF = float.Parse(LoadDirTime);
|
||||
// get Default reward.
|
||||
nonRewardDefault = DataTransfer.nonReward;
|
||||
shootRewardDefault = DataTransfer.shootReward;
|
||||
shootWithoutReadyRewardDefault = DataTransfer.shootWithoutReadyReward;
|
||||
hitRewardDefault = DataTransfer.hitReward;
|
||||
killRewardDefault = DataTransfer.killReward;
|
||||
winRewardDefault = DataTransfer.winReward;
|
||||
loseRewardDefault = DataTransfer.loseReward;
|
||||
|
||||
// get Default reward.
|
||||
nonRewardDefault = DataTransfer.nonReward;
|
||||
shootRewardDefault = DataTransfer.shootReward;
|
||||
shootWithoutReadyRewardDefault = DataTransfer.shootWithoutReadyReward;
|
||||
hitRewardDefault = DataTransfer.hitReward;
|
||||
killRewardDefault = DataTransfer.killReward;
|
||||
winRewardDefault = DataTransfer.winReward;
|
||||
loseRewardDefault = DataTransfer.loseReward;
|
||||
|
||||
// give default Reward to Reward value will be used.
|
||||
nonReward = nonRewardDefault;
|
||||
shootReward = shootRewardDefault;
|
||||
shootWithoutReadyReward = shootWithoutReadyRewardDefault;
|
||||
hitReward = hitRewardDefault;
|
||||
winReward = winRewardDefault;
|
||||
loseReward = loseRewardDefault;
|
||||
killReward = killRewardDefault;
|
||||
// change Decision Period & Take Actions Between Decisions
|
||||
transform.GetComponent<DecisionRequester>().DecisionPeriod = DataTransfer.DecisionPeriod;
|
||||
transform.GetComponent<DecisionRequester>().TakeActionsBetweenDecisions = DataTransfer.ActionsBetweenDecisions;
|
||||
|
||||
// change Decision Period & Take Actions Between Decisions
|
||||
transform.GetComponent<DecisionRequester>().DecisionPeriod = DataTransfer.DecisionPeriod;
|
||||
transform.GetComponent<DecisionRequester>().TakeActionsBetweenDecisions = DataTransfer.ActionsBetweenDecisions;
|
||||
}
|
||||
catch (NullReferenceException)
|
||||
{
|
||||
// Enemy Num
|
||||
enemyNum = 3;
|
||||
|
||||
//initialize remainTime
|
||||
remainTime = (int)(timeLimit - Time.time + startTime);
|
||||
// Time Limit
|
||||
timeLimit = 30;
|
||||
|
||||
// get load directory.
|
||||
LoadDirDate = "0";
|
||||
LoadDirTime = "0";
|
||||
LoadDirDateF = float.Parse(LoadDirDate);
|
||||
loadDirTimeF = float.Parse(LoadDirTime);
|
||||
|
||||
// get Default reward.
|
||||
nonRewardDefault = -0.05f;
|
||||
shootRewardDefault = -0.06f;
|
||||
shootWithoutReadyRewardDefault = -0.06f;
|
||||
hitRewardDefault = 5.0f;
|
||||
killRewardDefault = 10.0f;
|
||||
winRewardDefault = 20.0f;
|
||||
loseRewardDefault = -10.0f;
|
||||
|
||||
// change Decision Period & Take Actions Between Decisions
|
||||
transform.GetComponent<DecisionRequester>().DecisionPeriod = 1;
|
||||
transform.GetComponent<DecisionRequester>().TakeActionsBetweenDecisions = true;
|
||||
}
|
||||
finally
|
||||
{
|
||||
UICon = transform.GetComponent<UIController>();
|
||||
HistoryRec = transform.GetComponent<HistoryRecorder>();
|
||||
rayScript = GetComponent<RaySensors>();
|
||||
|
||||
// give default Reward to Reward value will be used.
|
||||
nonReward = nonRewardDefault;
|
||||
shootReward = shootRewardDefault;
|
||||
shootWithoutReadyReward = shootWithoutReadyRewardDefault;
|
||||
hitReward = hitRewardDefault;
|
||||
winReward = winRewardDefault;
|
||||
loseReward = loseRewardDefault;
|
||||
killReward = killRewardDefault;
|
||||
//initialize remainTime
|
||||
remainTime = (int)(timeLimit - Time.time + startTime);
|
||||
}
|
||||
}
|
||||
|
||||
/* ----------此Update用于debug，Build前删除或注释掉！----------*/
|
||||
@ -300,7 +332,7 @@ public class AgentWithGun : Agent
|
||||
//且绕轴旋转的坐标轴是父节点本地坐标系的坐标轴
|
||||
}
|
||||
|
||||
// GotKill 获得击杀时用于呼出
|
||||
// GotKill 获得击杀时用于被呼出
|
||||
public void GotKill()
|
||||
{
|
||||
enemyKillCount += 1;
|
||||
@ -493,19 +525,17 @@ public class AgentWithGun : Agent
|
||||
//List<float> enemyLDisList = RaySensors.enemyLDisList;// All Enemy Lside Distances
|
||||
//List<float> enemyRDisList = RaySensors.enemyRDisList;// All Enemy Rside Distances
|
||||
|
||||
|
||||
int allEnemyNum = RaySensors.allEnemyNum;
|
||||
rayScript.updateRayInfo();
|
||||
float[] myObserve = { thisAgent.position.x, thisAgent.position.y, thisAgent.position.z, thisAgent.rotation.w };
|
||||
float[] rayTagResult = RaySensors.rayTagResult;// 探测用RayTag结果 float[](raySensorNum,1)
|
||||
float[] rayDisResult = RaySensors.rayDisResult; // 探测用RayDis结果 float[](raySensorNum,1)
|
||||
float[] focusEnemyObserve = RaySensors.focusEnemyInfo;// 最近的Enemy情报 float[](3,1) MinEnemyIndex,x,z
|
||||
int raySensorNum = rayScript.rayNum;// raySensor数量 int
|
||||
float[] rayTagResult = rayScript.rayTagResult;// 探测用RayTag结果 float[](raySensorNum,1)
|
||||
float[] rayDisResult = rayScript.rayDisResult; // 探测用RayDis结果 float[](raySensorNum,1)
|
||||
//float[] focusEnemyObserve = RaySensors.focusEnemyInfo;// 最近的Enemy情报 float[](3,1) MinEnemyIndex,x,z
|
||||
|
||||
//sensor.AddObservation(allEnemyNum); // 敌人数量 int
|
||||
sensor.AddObservation(myObserve); // 自机位置xyz+朝向 float[](4,1)
|
||||
sensor.AddObservation(rayTagResult); // 探测用RayTag结果 float[](raySensorNum,1)
|
||||
sensor.AddObservation(rayDisResult); // 探测用RayDis结果 float[](raySensorNum,1)
|
||||
sensor.AddObservation(focusEnemyObserve); // 最近的Enemy情报 float[](3,1) MinEnemyIndex,x,z
|
||||
//sensor.AddObservation(focusEnemyObserve); // 最近的Enemy情报 float[](3,1) MinEnemyIndex,x,z
|
||||
//sensor.AddObservation(raySensorNum); // raySensor数量 int
|
||||
sensor.AddObservation(LoadDirDateF); // 用于loadModel的第一级dir
|
||||
sensor.AddObservation(loadDirTimeF); // 用于loadModel的第二级dir
|
||||
|
||||
@ -6,6 +6,7 @@ public class CameraChange : MonoBehaviour
|
||||
{
|
||||
public Camera FPSCamera;
|
||||
public Camera TPSCamera;
|
||||
public GameObject AgentOBJ;
|
||||
|
||||
public void switchCamera()
|
||||
{
|
||||
@ -26,10 +27,12 @@ public class CameraChange : MonoBehaviour
|
||||
{
|
||||
TPSCamera.enabled = true;
|
||||
FPSCamera.enabled = false;
|
||||
AgentOBJ.GetComponent<RaySensors>().showInGameRay = true;
|
||||
}
|
||||
public void ShowFPSView()
|
||||
{
|
||||
FPSCamera.enabled = true;
|
||||
TPSCamera.enabled = false;
|
||||
AgentOBJ.GetComponent<RaySensors>().showInGameRay = false;
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,52 +0,0 @@
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
|
||||
public class Camera_Control : MonoBehaviour
|
||||
{
|
||||
public Transform Agent;
|
||||
public Camera Cam;
|
||||
public float MouseSensitivity = 100;
|
||||
public float yRotation = 0.1f;//定义一个浮点类型的量，记录‘围绕’X轴旋转的角度
|
||||
public float viewDistance = 100;
|
||||
|
||||
private float Mouse_X;
|
||||
private float Mouse_Y;
|
||||
|
||||
void Start()
|
||||
{
|
||||
Cursor.lockState = CursorLockMode.Locked;// 隐藏并且锁定鼠标
|
||||
}
|
||||
|
||||
void Update()
|
||||
{
|
||||
//Mouse_X = Input.GetAxis("Mouse X") * MouseSensitivity * Time.deltaTime;
|
||||
//Debug.Log(Input.GetAxis("Mouse X"));
|
||||
//Mouse_Y = Input.GetAxis("Mouse Y") * MouseSensitivity * Time.deltaTime;
|
||||
|
||||
//yRotation = yRotation - Mouse_Y;
|
||||
//xRotation值为正时，屏幕下移，当xRotation值为负时，屏幕上移
|
||||
//当鼠标向上滑动，Mouse_Y值为正,xRotation-Mouse_Y的值为负,xRotation总的值为负，屏幕视角向上滑动
|
||||
//当鼠标向下滑动，Mouse_Y值为负,xRotation-Mouse_Y的值为正,xRotation总的值为正，屏幕视角向下滑动
|
||||
//简单来说就是要控制鼠标滑动的方向与屏幕移动的方向要相同
|
||||
|
||||
//limit UP DOWN between -90 -> 90
|
||||
//yRotation = Mathf.Clamp(yRotation, -90f, 90f);
|
||||
|
||||
|
||||
//相机左右旋转时，是以Y轴为中心旋转的，上下旋转时，是以X轴为中心旋转的
|
||||
//Agent.Rotate(Vector3.up * Mouse_X);
|
||||
//Vector3.up相当于Vector3(0,1,0),CameraRotation.Rotate(Vector3.up * Mouse_X)相当于使CameraRotation对象绕y轴旋转Mouse_X个单位
|
||||
//即相机左右旋转时，是以Y轴为中心旋转的，此时Mouse_X控制着值的大小
|
||||
|
||||
//相机在上下旋转移动时，相机方向不会随着移动，类似于低头和抬头，左右移动时，相机方向会随着向左向右移动，类似于向左向右看
|
||||
//所以在控制相机向左向右旋转时，要保证和父物体一起转动
|
||||
//this.transform.localRotation = Quaternion.Euler(yRotation, 0, 0);
|
||||
//this.transform指这个CameraRotation的位置,localRotation指的是旋转轴
|
||||
//transform.localRotation = Quaternion.Eular(x,y,z)控制旋转的时候，按照X-Y-Z轴的旋转顺规
|
||||
//即以围绕X轴旋转x度，围绕Y轴旋转y度，围绕Z轴旋转z度
|
||||
//且绕轴旋转的坐标轴是父节点本地坐标系的坐标轴
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
@ -15,6 +15,10 @@ public class EnemyHPBar : MonoBehaviour
|
||||
EnemyOBJ = transform.parent.gameObject;
|
||||
BGOBJ = transform.GetChild(0).gameObject;
|
||||
gaugeImgOBJ = BGOBJ.transform.GetChild(0).gameObject;
|
||||
Vector3 v = Camera.main.transform.position - transform.position;
|
||||
v.x = v.z = 0.0f;
|
||||
transform.LookAt(Camera.main.transform.position - v);
|
||||
transform.Rotate(0,180,0);
|
||||
}
|
||||
|
||||
void Update()
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
using System.Collections;
|
||||
using System;
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
|
||||
@ -7,30 +8,59 @@ using UnityEngine;
|
||||
|
||||
public class RaySensors : MonoBehaviour
|
||||
{
|
||||
|
||||
public Camera agentCam;
|
||||
public GameObject myself;
|
||||
public int rayNum = 6;
|
||||
public string EnemyTagName;
|
||||
public string WallTagName;
|
||||
public float viewDistance = 100; // how long the ray can detect
|
||||
public float Damage = 50; // damage to enemy
|
||||
public float attentionRange = 1f; //注意力范围，1为最大
|
||||
public float MaxDistance = 9999999999f;
|
||||
public float EnemyWidthRedundancy = 0.01f; //为了确保Ray可以击中Enemy，用于缩小EnemyWidth的长度
|
||||
//public List<string> tagNames = new List<string>();
|
||||
public static int allEnemyNum = 0;//All Enemy Num
|
||||
public static float[] focusEnemyInfo = new float[3];
|
||||
public static float[] rayTagResult; // Array to save Tag Result
|
||||
public static float[] rayDisResult; // Array to save Distance Result
|
||||
public static List<float> enemyLDisList = new List<float>();// All Enemy Lside Distances
|
||||
public static List<float> enemyRDisList = new List<float>();// All Enemy Rside Distances
|
||||
public Material lineMeterial;
|
||||
public GameObject rayInfoPrefab;
|
||||
public GameObject agentCanvas;
|
||||
|
||||
[SerializeField, Range(0, 500)] public float viewDistance = 100; // how long the ray can detect
|
||||
//[SerializeField, Range(0, 1)] public float totalRange = 1f; // Total view range Max = 1
|
||||
[SerializeField, Range(0, 1)] public float focusRange = 0.15f; // center focus range
|
||||
public int halfOuterRayNum = 3; // >=2
|
||||
public int focusRayNum = 5; // >= 1 and must be odd num!
|
||||
|
||||
[Header("InGameLineSetting")]
|
||||
public bool showInGameRay = true;
|
||||
public bool showDebugRay = true;
|
||||
public bool showInGameRayInfo = true;
|
||||
public float lineWidth = 0.05f;
|
||||
|
||||
public bool showEnemySensor = true;
|
||||
public bool showEyeSensor = true;
|
||||
[Header("RayCastResult")]
|
||||
public float[] rayTagResult;
|
||||
public float[] rayDisResult;
|
||||
|
||||
[System.NonSerialized] public int totalRayNum;
|
||||
GameObject[] linesOBJ;
|
||||
GameObject[] rayInfoOBJ;
|
||||
LineRenderer[] lineRenderers;
|
||||
rayInfoUI[] rayInfoUIs;
|
||||
|
||||
|
||||
private void Start()
|
||||
{
|
||||
|
||||
totalRayNum = halfOuterRayNum * 2 + focusRayNum;
|
||||
rayTagResult = new float[totalRayNum];
|
||||
rayDisResult = new float[totalRayNum];
|
||||
linesOBJ = new GameObject[totalRayNum];
|
||||
lineRenderers = new LineRenderer[totalRayNum];
|
||||
rayInfoOBJ = new GameObject[totalRayNum];
|
||||
rayInfoUIs = new rayInfoUI[totalRayNum];
|
||||
for(int i = 0; i < totalRayNum; i++)
|
||||
{
|
||||
linesOBJ[i] = new GameObject();
|
||||
linesOBJ[i].name = "rayCastLine-" + Convert.ToString(i);
|
||||
linesOBJ[i].transform.parent = agentCam.transform;
|
||||
linesOBJ[i].AddComponent<LineRenderer>();
|
||||
lineRenderers[i] = linesOBJ[i].GetComponent<LineRenderer>();
|
||||
lineRenderers[i].material = lineMeterial;
|
||||
|
||||
rayInfoOBJ[i] = (GameObject)Instantiate(rayInfoPrefab);
|
||||
rayInfoOBJ[i].transform.SetParent(agentCanvas.transform,false);
|
||||
rayInfoOBJ[i].name = "rayInfo-" + Convert.ToString(i);
|
||||
rayInfoUIs[i] = rayInfoOBJ[i].GetComponent<rayInfoUI>();
|
||||
}
|
||||
}
|
||||
|
||||
static int tagToInt(string tag)
|
||||
{
|
||||
@ -45,277 +75,107 @@ public class RaySensors : MonoBehaviour
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
// 敌人Ray探测处理
|
||||
// 返回
|
||||
(int, List<float>, List<float>, float[]) enemySensorRay(GameObject myself, Camera agentCam, float attentionRange)
|
||||
private void singleRaycastUpdate(Ray ray,LineRenderer thisLineRenderer,rayInfoUI thisRayInfoUI, out float rayTagResult, out float rayDisResult)
|
||||
{
|
||||
List<float> thisLDistanceList = new List<float>();
|
||||
List<float> thisRDistanceList = new List<float>();
|
||||
|
||||
GameObject[] EnemyGameObjs;
|
||||
EnemyGameObjs = GameObject.FindGameObjectsWithTag("Enemy");
|
||||
int EnemyIndex = 0;
|
||||
float MinEnemyDis = MaxDistance+1.0f;
|
||||
int MinEnemyIndex = 0;
|
||||
float[] MinEnemyInfo = new float[3];
|
||||
|
||||
//遍历所有Enemy
|
||||
foreach (GameObject EnemyObj in EnemyGameObjs)
|
||||
// get Raycast hit infomation and return Tag and distance
|
||||
RaycastHit thisHit;
|
||||
Color rayColor = Color.cyan;
|
||||
float lineLength = viewDistance;
|
||||
string rayInfoText = "";
|
||||
Vector3 rayInfoPosition;
|
||||
if (Physics.Raycast(ray, out thisHit, viewDistance)) // 若在viewDistance范围内有碰撞
|
||||
{
|
||||
Vector3 thisEnemyPosition = EnemyObj.transform.position;
|
||||
Vector3 thisEnemyScale = EnemyObj.transform.localScale;
|
||||
Vector3 MyselfPosition = myself.transform.position;
|
||||
float thisEnemyWidth = (float)(thisEnemyScale.x / 2) - EnemyWidthRedundancy;
|
||||
float thisEnemyDistance = Vector3.Distance(MyselfPosition, thisEnemyPosition);
|
||||
|
||||
//探测到Agent为自己时的处理
|
||||
if (thisEnemyPosition == MyselfPosition)
|
||||
rayInfoText = thisHit.collider.tag;
|
||||
rayTagResult = tagToInt(thisHit.collider.tag);
|
||||
rayDisResult = thisHit.distance;
|
||||
lineLength = rayDisResult;
|
||||
rayInfoText += "\n" + Convert.ToString(rayDisResult);
|
||||
//输出log
|
||||
switch (rayTagResult)
|
||||
{
|
||||
//Debug.Log("OH It's me");
|
||||
thisLDistanceList.Add(MaxDistance);
|
||||
thisRDistanceList.Add(MaxDistance);
|
||||
}
|
||||
//非己Agent处理
|
||||
else
|
||||
{
|
||||
EnemyIndex += 1;
|
||||
Vector3 Vertical = new Vector3(0, 100, 0);//垂直向上的向量
|
||||
Vector3 EnemytoMe = MyselfPosition - thisEnemyPosition;//Enemy和自机连线，指向自机的向量
|
||||
Vector3 LHorizontal = Vector3.Cross(Vertical, EnemytoMe);// 垂直于EnemytoMe与Vertical向量所组成的面的，且指向<-左侧的小向量<- Enemy
|
||||
Vector3 RHorizontal = Vector3.Cross(EnemytoMe, Vertical);// 垂直于EnemytoMe与Vertical向量所组成的面的，且指向->右侧的小向量Enemy ->
|
||||
//此时RHorizontal，LHorizontal的长度巨几把长，需要下面操作标准化为1/2Enemy宽度
|
||||
float standaedization = (float)thisEnemyWidth / Vector3.Distance(thisEnemyPosition, RHorizontal);//计算需要缩小的比例
|
||||
RHorizontal *= standaedization;//应用缩小比例，标准化完成
|
||||
LHorizontal *= standaedization;//应用缩小比例，标准化完成
|
||||
Vector3 LMetoEnemy = LHorizontal - EnemytoMe;//自机与左侧边界连线Me<- Enemy
|
||||
Vector3 RMetoEnemy = RHorizontal - EnemytoMe;//自机与右侧边界连线Enemy ->Me
|
||||
Vector3 L0toEnemy = LHorizontal + thisEnemyPosition;// Enemy左侧绝对坐标
|
||||
Vector3 R0toEnemy = RHorizontal + thisEnemyPosition;// Enemy右侧绝对坐标
|
||||
float LMetoEnemyDist = Vector3.Distance(MyselfPosition, L0toEnemy);
|
||||
float RMetoEnemyDist = Vector3.Distance(MyselfPosition, R0toEnemy);
|
||||
Vector3 LEnemyInView = agentCam.WorldToViewportPoint(L0toEnemy);//Enemy左侧于视角中位置
|
||||
Vector3 REnemyInView = agentCam.WorldToViewportPoint(R0toEnemy);//Enemy右侧于视角中位置
|
||||
//Debug连线，颜色遵循飞机航行灯基本使用规则，左红右绿尾翼白。
|
||||
//Debug.DrawRay(thisEnemyPosition, EnemytoMe, Color.white);//Enemy和自机连线，指向自机的向量
|
||||
//Debug.DrawRay(thisEnemyPosition, Vertical, Color.white);//垂直向上的向量
|
||||
//Debug.DrawRay(thisEnemyPosition, LHorizontal, Color.red);// 垂直于Vc与Vertical向量所组成的面的，且指向<-左侧的小向量<- Enemy
|
||||
//Debug.DrawRay(thisEnemyPosition, RHorizontal, Color.green);// 垂直于Vc与Vertical向量所组成的面的，且指向->右侧的小向量Enemy ->
|
||||
//Debug.DrawRay(MyselfPosition, LMetoEnemy, Color.red);//自机与左侧边界连线<- Enemy
|
||||
//Debug.DrawRay(MyselfPosition, RMetoEnemy, Color.green);//自机与右侧边界连线Enemy ->
|
||||
//Debug.Log("EnemyObj" + EnemyIndex + "Position:" + thisEnemyPosition);
|
||||
|
||||
|
||||
//左侧于可见范围内--<--<--<--<--<--<--<--<--<--<--<--<--<--<
|
||||
if (LEnemyInView.x >= (thisEnemyWidth - attentionRange / 2) && LEnemyInView.x <= (thisEnemyWidth + attentionRange / 2) && LEnemyInView.z > 0)
|
||||
{
|
||||
//射出Raycast
|
||||
Ray LRay = new Ray(MyselfPosition, LMetoEnemy);
|
||||
RaycastHit LHit;
|
||||
if (showEnemySensor)
|
||||
{
|
||||
Debug.DrawRay(LRay.origin, LRay.direction * LMetoEnemyDist, Color.white);//自机与左侧边界连线<- Enemy
|
||||
}
|
||||
//Ray Hit Something
|
||||
if (Physics.Raycast(MyselfPosition, LMetoEnemy, out LHit, LMetoEnemyDist))
|
||||
{
|
||||
//Ray Hit Enemy
|
||||
//并且当射线射到的Enemy的距离与当前判断Enemy的距离差小于该Enemy半径时
|
||||
//既该射线所射到的Enemy为当前Enemy而不是别的时
|
||||
if (LHit.collider.tag == EnemyTagName && System.Math.Abs(LHit.distance - thisEnemyDistance) <= thisEnemyWidth)
|
||||
{
|
||||
if (showEnemySensor)
|
||||
{
|
||||
Debug.DrawRay(LRay.origin, LRay.direction * LHit.distance, Color.red);//自机与所击中物体的连线
|
||||
}
|
||||
thisLDistanceList.Add(LHit.distance);
|
||||
//Debug.Log("Hit Tag = " + LHit.collider.tag);
|
||||
//Debug.Log(LDistance[EnemyIndex-1]);
|
||||
//Debug.Log("ADD_LIST_ENEMYL");
|
||||
}
|
||||
//当射线所hit的不是enemy或hit的enemy不是当前所判断的enemy
|
||||
else
|
||||
{
|
||||
if (showEnemySensor)
|
||||
{
|
||||
Debug.DrawRay(LRay.origin, LRay.direction * LHit.distance, Color.cyan);//自机与所击中物体的连线
|
||||
}
|
||||
thisLDistanceList.Add(MaxDistance);
|
||||
//Debug.LogWarning("Hit Tag = " + LHit.collider.tag);
|
||||
//Debug.LogWarning(LDistance[EnemyIndex-1]);
|
||||
//Debug.Log("ADD_LIST_ENEMYL");
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
thisLDistanceList.Add(MaxDistance);
|
||||
Debug.LogError("LRAY HIT NOTHING, Check Code!");
|
||||
}
|
||||
}
|
||||
//左侧不在可见范围内时--<--<--<--<--<--<--<--<--<--<--<--<--<--<
|
||||
else
|
||||
{
|
||||
thisLDistanceList.Add(MaxDistance);
|
||||
//Debug.LogError("NoVisual");
|
||||
//Debug.LogError(LDistance[EnemyIndex-1]);
|
||||
//Debug.Log("ADD_LIST_ENEMYL_ELSE");
|
||||
}
|
||||
|
||||
//右侧于可见范围内-->-->-->-->-->-->-->-->-->-->-->-->-->-->
|
||||
if (REnemyInView.x >= (thisEnemyWidth - attentionRange / 2) && REnemyInView.x <= (thisEnemyWidth + attentionRange / 2) && REnemyInView.z > 0)
|
||||
{
|
||||
//射出Raycast
|
||||
Ray RRay = new Ray(MyselfPosition, RMetoEnemy);
|
||||
RaycastHit RHit;
|
||||
if (showEnemySensor)
|
||||
{
|
||||
Debug.DrawRay(RRay.origin, RRay.direction * RMetoEnemyDist, Color.white);//自机与左侧边界连线<- Enemy
|
||||
}
|
||||
//Ray Hit Something
|
||||
if (Physics.Raycast(MyselfPosition, RMetoEnemy, out RHit, RMetoEnemyDist))
|
||||
{
|
||||
//Ray Hit Enemy
|
||||
//并且当射线射到的Enemy的距离与当前判断Enemy的距离差小于该Enemy半径时
|
||||
//既该射线所射到的Enemy为当前Enemy而不是别的时
|
||||
if (RHit.collider.tag == EnemyTagName && System.Math.Abs(RHit.distance - thisEnemyDistance) <= thisEnemyWidth)
|
||||
{
|
||||
if (showEnemySensor)
|
||||
{
|
||||
Debug.DrawRay(RRay.origin, RRay.direction * RHit.distance, Color.red);//自机与所击中物体的连线
|
||||
}
|
||||
thisRDistanceList.Add(RHit.distance);
|
||||
//Debug.Log("Hit Tag = " + LHit.collider.tag);
|
||||
//Debug.Log(LDistance[EnemyIndex-1]);
|
||||
//Debug.Log("ADD_LIST_ENEMYR");
|
||||
}
|
||||
//当射线所hit的不是enemy或hit的enemy不是当前所判断的enemy
|
||||
else
|
||||
{
|
||||
if (showEnemySensor)
|
||||
{
|
||||
Debug.DrawRay(RRay.origin, RRay.direction * RHit.distance, Color.cyan);//自机与所击中物体的连线
|
||||
}
|
||||
thisRDistanceList.Add(MaxDistance);
|
||||
//Debug.LogWarning("Hit Tag = " + LHit.collider.tag);
|
||||
//Debug.LogWarning(LDistance[EnemyIndex-1]);
|
||||
//Debug.Log("ADD_LIST_ENEMYR");
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
thisLDistanceList.Add(MaxDistance);
|
||||
Debug.LogError("RRAY HIT NOTHING, Check Code!");
|
||||
}
|
||||
}
|
||||
//右侧不在可见范围内时-->-->-->-->-->-->-->-->-->-->-->-->-->-->
|
||||
else
|
||||
{
|
||||
thisRDistanceList.Add(MaxDistance);
|
||||
//Debug.LogError("NoVisual");
|
||||
//Debug.LogError(LDistance[EnemyIndex-1]);
|
||||
//Debug.Log("ADD_LIST_ENEMYR_ELSE");
|
||||
}
|
||||
}
|
||||
//Debug.LogWarning("EnemyIndex" + EnemyIndex);
|
||||
//Debug.LogWarning(thisLDistanceList.Count);
|
||||
//Debug.LogWarning(MinEnemyIndex);
|
||||
//Debug.Log("thisLDistanceList" + thisLDistanceList.Count);
|
||||
//Debug.Log("thisRDistanceList" + thisRDistanceList.Count);
|
||||
|
||||
//检查最近Enemy
|
||||
if (System.Math.Min(thisLDistanceList[EnemyIndex], thisRDistanceList[EnemyIndex]) < MinEnemyDis)
|
||||
{
|
||||
//Debug.Log("EnemyIndex" + EnemyIndex);
|
||||
MinEnemyDis = System.Math.Min(thisLDistanceList[EnemyIndex], thisRDistanceList[EnemyIndex]);
|
||||
MinEnemyIndex = EnemyIndex;
|
||||
case 1:// Wall
|
||||
rayColor = Color.white;
|
||||
break;
|
||||
case 2: // Enemy
|
||||
rayColor = Color.red;
|
||||
break;
|
||||
case -1: // Hit Nothing
|
||||
rayColor = Color.gray;
|
||||
break;
|
||||
default: // default,got wrong
|
||||
rayColor = Color.cyan;
|
||||
break;
|
||||
}
|
||||
}
|
||||
// 获取最近敌人的准确位置信息
|
||||
MinEnemyInfo[0] = (float)MinEnemyIndex;
|
||||
if(MinEnemyInfo[0] <= 0)
|
||||
else // 若在viewDistance范围无碰撞
|
||||
{
|
||||
MinEnemyInfo[1] = MaxDistance;
|
||||
MinEnemyInfo[2] = MaxDistance;
|
||||
rayTagResult = -1f;
|
||||
rayDisResult = -1f;
|
||||
//输出log
|
||||
//Debug.Log(0);
|
||||
//Debug.Log(0);
|
||||
}
|
||||
rayInfoPosition = ray.origin + (ray.direction * lineLength);
|
||||
if (showInGameRay)
|
||||
{
|
||||
drawLine(ray, lineLength, thisLineRenderer, rayColor);
|
||||
}
|
||||
else
|
||||
{
|
||||
MinEnemyInfo[1] = EnemyGameObjs[MinEnemyIndex].transform.position.x;
|
||||
MinEnemyInfo[2] = EnemyGameObjs[MinEnemyIndex].transform.position.z;
|
||||
turnOffLine(thisLineRenderer, rayColor);
|
||||
}
|
||||
return (EnemyIndex, thisLDistanceList, thisRDistanceList,MinEnemyInfo);
|
||||
// drawRay in game
|
||||
if (showInGameRayInfo) thisRayInfoUI.updateInfo(rayInfoText, rayInfoPosition, rayColor);
|
||||
// Show log
|
||||
if (showDebugRay) Debug.DrawRay(ray.origin, ray.direction * viewDistance, rayColor); // drawRay in debug
|
||||
// Debug.Log(ray.origin + ray.direction);
|
||||
// Debug.Log(rayTagResult);
|
||||
// Debug.Log(tagToInt(thisHit.collider.tag));
|
||||
}
|
||||
|
||||
|
||||
// 全局Ray探测处理
|
||||
(float[], float[]) eyeSensorRay(int rayNum, Camera agentCam, float viewDistance)
|
||||
private void drawLine(Ray ray,float lineLength, LineRenderer thisLineRenderer, Color lineColor)
|
||||
{
|
||||
//初始化result Array
|
||||
float[] thisRayTagResult = new float[rayNum];
|
||||
float[] thisRayDisResult = new float[rayNum];
|
||||
|
||||
//于视角范围内一帧射出rayNum条射线
|
||||
for (int a = 0; a <= rayNum - 1; a = a + 1)
|
||||
{
|
||||
//射线射出
|
||||
Vector3 point = new Vector3(a * agentCam.pixelWidth / (rayNum - 1), agentCam.pixelHeight / 2, 0);//发射位置
|
||||
Ray ray = agentCam.ScreenPointToRay(point);
|
||||
RaycastHit hit;
|
||||
if (showEyeSensor)
|
||||
{
|
||||
Debug.DrawRay(ray.origin, ray.direction * viewDistance, Color.black);
|
||||
}
|
||||
//若在viewDistance范围内有碰撞
|
||||
if (Physics.Raycast(ray, out hit, viewDistance))
|
||||
{
|
||||
thisRayTagResult[a] = tagToInt(hit.collider.tag);
|
||||
thisRayDisResult[a] = hit.distance;
|
||||
if (showEyeSensor)
|
||||
{
|
||||
Debug.DrawRay(ray.origin, ray.direction * hit.distance, Color.yellow);
|
||||
}
|
||||
//输出log
|
||||
//Debug.Log(rayTagResult[a]);
|
||||
//Debug.Log(tagToInt(hit.collider.tag));
|
||||
|
||||
}
|
||||
//若在viewDistance范围无碰撞
|
||||
else
|
||||
{
|
||||
thisRayTagResult[a] = -1f;
|
||||
thisRayDisResult[a] = -1f;
|
||||
//输出log
|
||||
//Debug.Log(0);
|
||||
//Debug.Log(0);
|
||||
}
|
||||
}
|
||||
return (thisRayTagResult, thisRayDisResult);
|
||||
thisLineRenderer.startColor = lineColor;
|
||||
thisLineRenderer.endColor = lineColor;
|
||||
thisLineRenderer.startWidth = lineWidth;
|
||||
thisLineRenderer.endWidth = lineWidth;
|
||||
thisLineRenderer.SetPosition(0, ray.origin);
|
||||
thisLineRenderer.SetPosition(1, ray.origin + (ray.direction * lineLength));
|
||||
}
|
||||
|
||||
void Start()
|
||||
private void turnOffLine(LineRenderer thisLineRenderer, Color lineColor)
|
||||
{
|
||||
rayTagResult = new float[rayNum];
|
||||
rayDisResult = new float[rayNum];
|
||||
thisLineRenderer.startColor = lineColor;
|
||||
thisLineRenderer.endColor = lineColor;
|
||||
thisLineRenderer.startWidth = 0f;
|
||||
thisLineRenderer.endWidth = 0f;
|
||||
thisLineRenderer.SetPosition(0, new Vector3(0, 0, 0));
|
||||
thisLineRenderer.SetPosition(1, new Vector3(0, 0, 0));
|
||||
}
|
||||
|
||||
|
||||
|
||||
void Update()
|
||||
public void updateRayInfo()
|
||||
{
|
||||
(rayTagResult, rayDisResult) = eyeSensorRay(rayNum, agentCam, viewDistance);
|
||||
(allEnemyNum, enemyLDisList, enemyRDisList, focusEnemyInfo) = enemySensorRay(myself, agentCam, attentionRange);
|
||||
transform.gameObject.GetComponent<UIController>().updateRemainEnemy(allEnemyNum);
|
||||
/*
|
||||
Debug.LogWarning("rayNum :" + rayNum);
|
||||
for (int i =0;i < rayNum; i++)
|
||||
float focusLEdge = agentCam.pixelWidth * (1 - focusRange) / 2;
|
||||
float focusREdge = agentCam.pixelWidth * (1 + focusRange) / 2;
|
||||
float thisCamPixelHeight = agentCam.pixelHeight;
|
||||
|
||||
for (int i = 0; i < halfOuterRayNum; i++) // create left outside rays; 0 ~ focusLeftEdge
|
||||
{
|
||||
Debug.Log("rayTagResult" + rayTagResult[i] + "rayDisResult"+ rayDisResult[i]);
|
||||
Vector3 point = new Vector3(i * focusLEdge / (halfOuterRayNum - 1), thisCamPixelHeight / 2, 0);
|
||||
Ray thisRay = agentCam.ScreenPointToRay(point);
|
||||
singleRaycastUpdate(thisRay,lineRenderers[i], rayInfoUIs[i] , out rayTagResult[i], out rayDisResult[i]);
|
||||
}
|
||||
Debug.LogWarning("EnemyNum Include Me:" + allEnemyNum);
|
||||
for(int i = 0; i < allEnemyNum; i++)
|
||||
for (int i = 0; i < halfOuterRayNum; i++) // create right outside rays; focusRightEdge ~ MaxPixelHeight
|
||||
{
|
||||
Debug.Log("enemyLDisList" + enemyLDisList[i] + "enemyRDisList" + enemyRDisList[i]);
|
||||
Vector3 point = new Vector3(focusREdge + (i * focusLEdge / (halfOuterRayNum - 1)), thisCamPixelHeight / 2, 0);
|
||||
Ray thisRay = agentCam.ScreenPointToRay(point);
|
||||
singleRaycastUpdate(thisRay, lineRenderers[halfOuterRayNum + i], rayInfoUIs[halfOuterRayNum + i], out rayTagResult[halfOuterRayNum + i], out rayDisResult[halfOuterRayNum + i]);
|
||||
}
|
||||
for (int i = 0; i < focusRayNum; i++) // create center focus rays; focusLeftEdge ~ focusLeftEdge
|
||||
{
|
||||
Vector3 point = new Vector3(focusLEdge + ((i + 1) * (focusREdge - focusLEdge) / (focusRayNum + 1)), thisCamPixelHeight / 2, 0);
|
||||
Ray thisRay = agentCam.ScreenPointToRay(point);
|
||||
singleRaycastUpdate(thisRay, lineRenderers[halfOuterRayNum * 2 + i], rayInfoUIs[halfOuterRayNum * 2 + i], out rayTagResult[halfOuterRayNum*2 + i], out rayDisResult[halfOuterRayNum*2 + i]);
|
||||
}
|
||||
*/
|
||||
}
|
||||
}
|
||||
|
||||
25
Aimbot-PPO-MultiScene/Assets/Script/InGame/rayInfoUI.cs
Normal file
25
Aimbot-PPO-MultiScene/Assets/Script/InGame/rayInfoUI.cs
Normal file
@ -0,0 +1,25 @@
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
using TMPro;
|
||||
|
||||
public class rayInfoUI : MonoBehaviour
|
||||
{
|
||||
TextMeshProUGUI infoText;
|
||||
|
||||
// Start is called before the first frame update
|
||||
void Start()
|
||||
{
|
||||
infoText = transform.GetChild(0).gameObject.GetComponent<TextMeshProUGUI>();
|
||||
}
|
||||
|
||||
public void updateInfo(string info,Vector3 infoPosition, Color infoColor)
|
||||
{
|
||||
infoText.text = info;
|
||||
infoText.color = infoColor;
|
||||
transform.position = infoPosition;
|
||||
Vector3 v = Camera.main.transform.position - infoPosition;
|
||||
v.x = v.z = 0.0f;
|
||||
transform.LookAt(Camera.main.transform.position - v);
|
||||
transform.Rotate(0, 180, 0);
|
||||
}
|
||||
}
|
||||
@ -1,5 +1,5 @@
|
||||
fileFormatVersion: 2
|
||||
guid: cce4f6a22ca8eba4b94c1bfc6ac08072
|
||||
guid: 812dfed7ee1d09c4fa7c3ed8372f54ae
|
||||
MonoImporter:
|
||||
externalObjects: {}
|
||||
serializedVersion: 2
|
||||
@ -1,22 +0,0 @@
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
|
||||
public class DecisionPeriodChanger : MonoBehaviour
|
||||
{
|
||||
public GameObject DataTransfer;
|
||||
public Slider DecisionPeriodSlide;
|
||||
public Text DecisionPeriodDataText;
|
||||
public Toggle TakeActionsBetweenDecisionsToggle;
|
||||
|
||||
public void onSlideValueChanged()
|
||||
{
|
||||
DataTransfer.GetComponent<StartSeneData>().DecisionPeriod = (int)(DecisionPeriodSlide.GetComponent<Slider>().value);
|
||||
DecisionPeriodDataText.text = DataTransfer.GetComponent<StartSeneData>().DecisionPeriod.ToString();
|
||||
}
|
||||
public void onToggleChanged()
|
||||
{
|
||||
DataTransfer.GetComponent<StartSeneData>().ActionsBetweenDecisions = TakeActionsBetweenDecisionsToggle.isOn;
|
||||
}
|
||||
}
|
||||
@ -1,11 +0,0 @@
|
||||
fileFormatVersion: 2
|
||||
guid: 0d097ecbef2d7b843b772144dd301b2b
|
||||
MonoImporter:
|
||||
externalObjects: {}
|
||||
serializedVersion: 2
|
||||
defaultReferences: []
|
||||
executionOrder: 0
|
||||
icon: {instanceID: 0}
|
||||
userData:
|
||||
assetBundleName:
|
||||
assetBundleVariant:
|
||||
62
Aimbot-PPO-MultiScene/Assets/Script/Start/EnvArgsChanger.cs
Normal file
62
Aimbot-PPO-MultiScene/Assets/Script/Start/EnvArgsChanger.cs
Normal file
@ -0,0 +1,62 @@
|
||||
using System;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
|
||||
public class EnvArgsChanger : MonoBehaviour
|
||||
{
|
||||
public GameObject DataTransfer;
|
||||
|
||||
[Header("EnemyNum")]
|
||||
public Text EnemyNumText;
|
||||
public InputField EnemyNumInput;
|
||||
|
||||
[Header("TimeLimit")]
|
||||
public Text TimeLimText;
|
||||
public InputField TimelimInput;
|
||||
|
||||
[Header("Decision Period")]
|
||||
public Slider DecisionPeriodSlide;
|
||||
public Text DecisionPeriodDataText;
|
||||
public Toggle TakeActionsBetweenDecisionsToggle;
|
||||
|
||||
|
||||
public void onEnemynumValueChanged()
|
||||
{
|
||||
// enemy total num value control
|
||||
if (EnemyNumInput.GetComponent<InputField>().text == "" || EnemyNumInput.GetComponent<InputField>().text.Contains("-"))
|
||||
{
|
||||
EnemyNumText.color = Color.gray;
|
||||
}
|
||||
else
|
||||
{
|
||||
EnemyNumText.color = Color.yellow;
|
||||
DataTransfer.GetComponent<StartSeneData>().EnemyNum = Math.Abs(int.Parse(EnemyNumInput.GetComponent<InputField>().text));
|
||||
}
|
||||
}
|
||||
|
||||
public void onTimeValueChanged()
|
||||
{
|
||||
// time limit value control
|
||||
if (TimelimInput.GetComponent<InputField>().text == "" || TimelimInput.GetComponent<InputField>().text.Contains("-"))
|
||||
{
|
||||
TimeLimText.color = Color.gray;
|
||||
}
|
||||
else
|
||||
{
|
||||
TimeLimText.color = Color.yellow;
|
||||
DataTransfer.GetComponent<StartSeneData>().Timelim = Math.Abs(int.Parse(TimelimInput.GetComponent<InputField>().text));
|
||||
}
|
||||
}
|
||||
|
||||
public void onDPSlideValueChanged()
|
||||
{
|
||||
// DecisionPeriod(DP) value Control
|
||||
DataTransfer.GetComponent<StartSeneData>().DecisionPeriod = (int)(DecisionPeriodSlide.GetComponent<Slider>().value);
|
||||
DecisionPeriodDataText.text = DataTransfer.GetComponent<StartSeneData>().DecisionPeriod.ToString();
|
||||
}
|
||||
public void onABDToggleChanged()
|
||||
{
|
||||
// Actions Between Decisions(ABD) Toggle Control
|
||||
DataTransfer.GetComponent<StartSeneData>().ActionsBetweenDecisions = TakeActionsBetweenDecisionsToggle.isOn;
|
||||
}
|
||||
}
|
||||
@ -1,5 +1,5 @@
|
||||
fileFormatVersion: 2
|
||||
guid: 7ab8f48d4eac07f44b093f714ede051c
|
||||
guid: ccfe892ab0f980343b6df0fafaec38e2
|
||||
MonoImporter:
|
||||
externalObjects: {}
|
||||
serializedVersion: 2
|
||||
@ -3,19 +3,15 @@ using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
|
||||
public class LoadDirToggle : MonoBehaviour
|
||||
public class LoadDirChanger : MonoBehaviour
|
||||
{
|
||||
public InputField LoadDirDateTextBox;
|
||||
public InputField LoadDirTimeTextBox;
|
||||
public Toggle Toggle;
|
||||
public GameObject DataTransfer;
|
||||
// Start is called before the first frame update
|
||||
void Start()
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
public void OnToggleChanged()
|
||||
|
||||
public void OnDirToggleChanged()
|
||||
{
|
||||
// if loadDirToggle is on then turn off the input text boxs.
|
||||
LoadDirDateTextBox.interactable = Toggle.isOn;
|
||||
@ -27,4 +23,15 @@ public class LoadDirToggle : MonoBehaviour
|
||||
DataTransfer.GetComponent<StartSeneData>().LoadDirTime = "0";
|
||||
}
|
||||
}
|
||||
|
||||
public void OnDateValueChanged()
|
||||
{
|
||||
string input = LoadDirDateTextBox.GetComponent<InputField>().text;
|
||||
DataTransfer.GetComponent<StartSeneData>().LoadDirDate = input;
|
||||
}
|
||||
public void OnTimeValueChanged()
|
||||
{
|
||||
string input = LoadDirTimeTextBox.GetComponent<InputField>().text;
|
||||
DataTransfer.GetComponent<StartSeneData>().LoadDirTime = input;
|
||||
}
|
||||
}
|
||||
@ -1,5 +1,5 @@
|
||||
fileFormatVersion: 2
|
||||
guid: 8396a1a162e012447a0e4f7626e70dc7
|
||||
guid: 664e98da80fb4d842b0c3aff09fd4dc9
|
||||
MonoImporter:
|
||||
externalObjects: {}
|
||||
serializedVersion: 2
|
||||
@ -1,14 +0,0 @@
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
|
||||
public class LoadDirDateTextChange : MonoBehaviour
|
||||
{
|
||||
public GameObject DataTransfer;
|
||||
public void OnValueChanged()
|
||||
{
|
||||
string input = this.GetComponent<InputField>().text;
|
||||
DataTransfer.GetComponent<StartSeneData>().LoadDirDate = input;
|
||||
}
|
||||
}
|
||||
@ -1,14 +0,0 @@
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
|
||||
public class LoadDirTimeTextChange : MonoBehaviour
|
||||
{
|
||||
public GameObject DataTransfer;
|
||||
public void OnValueChanged()
|
||||
{
|
||||
string input = this.GetComponent<InputField>().text;
|
||||
DataTransfer.GetComponent<StartSeneData>().LoadDirTime = input;
|
||||
}
|
||||
}
|
||||
@ -1,11 +0,0 @@
|
||||
fileFormatVersion: 2
|
||||
guid: e18f417f93a39c74481660da3236c133
|
||||
MonoImporter:
|
||||
externalObjects: {}
|
||||
serializedVersion: 2
|
||||
defaultReferences: []
|
||||
executionOrder: 0
|
||||
icon: {instanceID: 0}
|
||||
userData:
|
||||
assetBundleName:
|
||||
assetBundleVariant:
|
||||
@ -1,5 +1,3 @@
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
using UnityEngine.SceneManagement;
|
||||
|
||||
@ -1,25 +0,0 @@
|
||||
using System;
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
|
||||
public class StartSceneEnemyNumChanger : MonoBehaviour
|
||||
{
|
||||
public GameObject DataTransfer;
|
||||
public InputField EnemyNumInput;
|
||||
public Text EnemyNumText;
|
||||
|
||||
public void onValueChanged()
|
||||
{
|
||||
if (EnemyNumInput.GetComponent<InputField>().text == "" || EnemyNumInput.GetComponent<InputField>().text.Contains("-"))
|
||||
{
|
||||
EnemyNumText.color = Color.gray;
|
||||
}
|
||||
else
|
||||
{
|
||||
EnemyNumText.color = Color.yellow;
|
||||
DataTransfer.GetComponent<StartSeneData>().EnemyNum = Math.Abs(int.Parse(EnemyNumInput.GetComponent<InputField>().text));
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,11 +0,0 @@
|
||||
fileFormatVersion: 2
|
||||
guid: 64d0bcf55e4db0c488996ba1051c279f
|
||||
MonoImporter:
|
||||
externalObjects: {}
|
||||
serializedVersion: 2
|
||||
defaultReferences: []
|
||||
executionOrder: 0
|
||||
icon: {instanceID: 0}
|
||||
userData:
|
||||
assetBundleName:
|
||||
assetBundleVariant:
|
||||
@ -1,25 +0,0 @@
|
||||
using System;
|
||||
using System.Collections;
|
||||
using System.Collections.Generic;
|
||||
using UnityEngine;
|
||||
using UnityEngine.UI;
|
||||
|
||||
public class StartSceneTimeLimChanger : MonoBehaviour
|
||||
{
|
||||
public GameObject DataTransfer;
|
||||
public Text TimeLimText;
|
||||
public InputField TimelimInput;
|
||||
|
||||
public void onValueTimeChanged()
|
||||
{
|
||||
if (TimelimInput.GetComponent<InputField>().text == "" || TimelimInput.GetComponent<InputField>().text.Contains("-"))
|
||||
{
|
||||
TimeLimText.color = Color.gray;
|
||||
}
|
||||
else
|
||||
{
|
||||
TimeLimText.color = Color.yellow;
|
||||
DataTransfer.GetComponent<StartSeneData>().Timelim = Math.Abs(int.Parse(TimelimInput.GetComponent<InputField>().text));
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,11 +0,0 @@
|
||||
fileFormatVersion: 2
|
||||
guid: 7857e2b2e5caf6b4686c4a7d87fa998e
|
||||
MonoImporter:
|
||||
externalObjects: {}
|
||||
serializedVersion: 2
|
||||
defaultReferences: []
|
||||
executionOrder: 0
|
||||
icon: {instanceID: 0}
|
||||
userData:
|
||||
assetBundleName:
|
||||
assetBundleVariant:
|
||||
@ -4,9 +4,16 @@ from mlagents_envs.environment import UnityEnvironment
|
||||
|
||||
import numpy as np
|
||||
|
||||
|
||||
class makeEnv(object):
|
||||
def __init__(self,envPath,workerID,basePort):
|
||||
self.env = UnityEnvironment(file_name=envPath,seed = 1,side_channels=[],worker_id = workerID,base_port=basePort)
|
||||
def __init__(self, envPath, workerID, basePort):
|
||||
self.env = UnityEnvironment(
|
||||
file_name=envPath,
|
||||
seed=1,
|
||||
side_channels=[],
|
||||
worker_id=workerID,
|
||||
base_port=basePort,
|
||||
)
|
||||
self.env.reset()
|
||||
|
||||
# get enviroment specs
|
||||
@ -15,73 +22,97 @@ class makeEnv(object):
|
||||
self.BEHA_SPECS = self.env.behavior_specs
|
||||
self.BEHA_NAME = list(self.BEHA_SPECS)[0]
|
||||
self.SPEC = self.BEHA_SPECS[self.BEHA_NAME]
|
||||
self.OBSERVATION_SPECS = self.SPEC.observation_specs[0] # observation spec
|
||||
self.OBSERVATION_SPECS = self.SPEC.observation_specs[
|
||||
0
|
||||
] # observation spec
|
||||
self.ACTION_SPEC = self.SPEC.action_spec # action specs
|
||||
|
||||
self.DISCRETE_SIZE = self.ACTION_SPEC.discrete_size# 連続的な動作のSize
|
||||
self.CONTINUOUS_SIZE = self.ACTION_SPEC.continuous_size# 離散的な動作のSize
|
||||
self.STATE_SIZE = self.OBSERVATION_SPECS.shape[0] - self.LOAD_DIR_SIZE_IN_STATE# 環境観測データ数
|
||||
|
||||
self.DISCRETE_SIZE = self.ACTION_SPEC.discrete_size # 連続的な動作のSize
|
||||
self.CONTINUOUS_SIZE = self.ACTION_SPEC.continuous_size # 離散的な動作のSize
|
||||
self.STATE_SIZE = (
|
||||
self.OBSERVATION_SPECS.shape[0] - self.LOAD_DIR_SIZE_IN_STATE
|
||||
) # 環境観測データ数
|
||||
print("√√√√√Enviroment Initialized Success√√√√√")
|
||||
|
||||
def step(self,discreteActions = None,continuousActions = None,behaviorName = None,trackedAgent = None):
|
||||
|
||||
def step(
|
||||
self,
|
||||
discreteActions=None,
|
||||
continuousActions=None,
|
||||
behaviorName=None,
|
||||
trackedAgent=None,
|
||||
):
|
||||
# take action to enviroment
|
||||
# return mextState,reward,done
|
||||
|
||||
|
||||
# check if arg is include None or IS None
|
||||
try:
|
||||
isDisNone = discreteActions.any() == None
|
||||
if discreteActions.all() == None:
|
||||
isDisNone = discreteActions.any() is None
|
||||
if discreteActions.all() is None:
|
||||
print("step() Error!:discreteActions include None")
|
||||
except:
|
||||
isDisNone = True
|
||||
try:
|
||||
isConNone = continuousActions.any() == None
|
||||
if continuousActions.all() == None:
|
||||
isConNone = continuousActions.any() is None
|
||||
if continuousActions.all() is None:
|
||||
print("step() Error!:continuousActions include None")
|
||||
except:
|
||||
isConNone = True
|
||||
|
||||
|
||||
if isDisNone:
|
||||
# if discreteActions is enpty just give nothing[[0]] to Enviroment
|
||||
discreteActions = np.array([[0]], dtype=np.int)
|
||||
if isConNone:
|
||||
# if continuousActions is enpty just give nothing[[0]] to Enviroment
|
||||
continuousActions = np.array([[0]], dtype=np.float)
|
||||
if behaviorName == None:
|
||||
if behaviorName is None:
|
||||
behaviorName = self.BEHA_NAME
|
||||
if trackedAgent == None:
|
||||
if trackedAgent is None:
|
||||
trackedAgent = self.TRACKED_AGENT
|
||||
|
||||
#create actionTuple
|
||||
thisActionTuple = ActionTuple(continuous=continuousActions,discrete=discreteActions)
|
||||
|
||||
# create actionTuple
|
||||
thisActionTuple = ActionTuple(
|
||||
continuous=continuousActions, discrete=discreteActions
|
||||
)
|
||||
# take action to env
|
||||
self.env.set_actions(behavior_name=behaviorName,action=thisActionTuple)
|
||||
self.env.set_actions(
|
||||
behavior_name=behaviorName, action=thisActionTuple
|
||||
)
|
||||
self.env.step()
|
||||
# get nextState & reward & done after this action
|
||||
nextState,reward,done,loadDir, saveNow = self.getSteps(behaviorName,trackedAgent)
|
||||
return nextState,reward,done,loadDir, saveNow
|
||||
nextState, reward, done, loadDir, saveNow = self.getSteps(
|
||||
behaviorName, trackedAgent
|
||||
)
|
||||
return nextState, reward, done, loadDir, saveNow
|
||||
|
||||
def getSteps(self,behaviorName = None,trackedAgent = None):
|
||||
def getSteps(self, behaviorName=None, trackedAgent=None):
|
||||
# get nextState & reward & done
|
||||
if behaviorName == None:
|
||||
if behaviorName is None:
|
||||
behaviorName = self.BEHA_NAME
|
||||
decisionSteps,terminalSteps = self.env.get_steps(behaviorName)
|
||||
decisionSteps, terminalSteps = self.env.get_steps(behaviorName)
|
||||
if self.TRACKED_AGENT == -1 and len(decisionSteps) >= 1:
|
||||
self.TRACKED_AGENT = decisionSteps.agent_id[0]
|
||||
if trackedAgent == None:
|
||||
if trackedAgent is None:
|
||||
trackedAgent = self.TRACKED_AGENT
|
||||
|
||||
if trackedAgent in decisionSteps: # ゲーム終了していない場合、環境状態がdecision_stepsに保存される
|
||||
|
||||
if (
|
||||
trackedAgent in decisionSteps
|
||||
): # ゲーム終了していない場合、環境状態がdecision_stepsに保存される
|
||||
nextState = decisionSteps[trackedAgent].obs[0]
|
||||
nextState = np.reshape(nextState,[1,self.STATE_SIZE+self.LOAD_DIR_SIZE_IN_STATE])
|
||||
nextState = np.reshape(
|
||||
nextState, [1, self.STATE_SIZE + self.LOAD_DIR_SIZE_IN_STATE]
|
||||
)
|
||||
saveNow = nextState[0][-1]
|
||||
loadDir = nextState[0][-3:-1]
|
||||
nextState = nextState[0][:-3]
|
||||
reward = decisionSteps[trackedAgent].reward
|
||||
done = False
|
||||
if trackedAgent in terminalSteps: # ゲーム終了した場合、環境状態がterminal_stepsに保存される
|
||||
if (
|
||||
trackedAgent in terminalSteps
|
||||
): # ゲーム終了した場合、環境状態がterminal_stepsに保存される
|
||||
nextState = terminalSteps[trackedAgent].obs[0]
|
||||
nextState = np.reshape(nextState,[1,self.STATE_SIZE+self.LOAD_DIR_SIZE_IN_STATE])
|
||||
nextState = np.reshape(
|
||||
nextState, [1, self.STATE_SIZE + self.LOAD_DIR_SIZE_IN_STATE]
|
||||
)
|
||||
saveNow = nextState[0][-1]
|
||||
loadDir = nextState[0][-3:-1]
|
||||
nextState = nextState[0][:-3]
|
||||
@ -91,8 +122,8 @@ class makeEnv(object):
|
||||
|
||||
def reset(self):
|
||||
self.env.reset()
|
||||
nextState,reward,done,loadDir,saveNow = self.getSteps()
|
||||
return nextState,reward,done,loadDir,saveNow
|
||||
nextState, reward, done, loadDir, saveNow = self.getSteps()
|
||||
return nextState, reward, done, loadDir, saveNow
|
||||
|
||||
def render(self):
|
||||
self.env.render()
|
||||
self.env.render()
|
||||
|
||||
@ -24,7 +24,9 @@
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": []
|
||||
"source": [
|
||||
"a=1"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
|
||||
@ -13,7 +13,7 @@
|
||||
"\n",
|
||||
"import tensorflow as tf\n",
|
||||
"import time\n",
|
||||
"import datetime"
|
||||
"import datetime\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -33,28 +33,29 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"ENV_PATH = './Build-MultiScene-WithLoad/Aimbot-PPO'\n",
|
||||
"# Env\n",
|
||||
"ENV_PATH = \"./Build-CloseEnemyCut/Aimbot-PPO\"\n",
|
||||
"WORKER_ID = 1\n",
|
||||
"BASE_PORT = 200\n",
|
||||
"\n",
|
||||
"MAX_EP = 1000\n",
|
||||
"EP_LENGTH = 100000\n",
|
||||
"GAMMA = 0.99 # discount future reward (UP?)\n",
|
||||
"EPSILON = 0.2 # clip Ratio range[1-EPSILON,1+EPSILON]\n",
|
||||
"ACTOR_LR = 1e-5 # LR\n",
|
||||
"CRITIC_LR = 2e-5 # LR\n",
|
||||
"BATCH = 512 # learning step\n",
|
||||
"ACTOR_EPOCH = 15 # epoch\n",
|
||||
"CRITIC_EPOCH = 15 # epoch\n",
|
||||
"ENTROPY_WHEIGHT = 0.01 # sigma's entropy in Actor loss\n",
|
||||
"ACTION_INTERVAL = 1 # take action every ACTION_INTERVAL steps\n",
|
||||
"GAMMA = 0.99 # discount future reward (UP?)\n",
|
||||
"EPSILON = 0.2 # clip Ratio range[1-EPSILON,1+EPSILON]\n",
|
||||
"ACTOR_LR = 1e-5 # LR\n",
|
||||
"CRITIC_LR = 2e-5 # LR\n",
|
||||
"BATCH = 256 # learning step\n",
|
||||
"ACTOR_EPOCH = 15 # epoch\n",
|
||||
"CRITIC_EPOCH = 15 # epoch\n",
|
||||
"ENTROPY_WHEIGHT = 0.001 # sigma's entropy in Actor loss\n",
|
||||
"ACTION_INTERVAL = 1 # take action every ACTION_INTERVAL steps\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"TRAIN = True\n",
|
||||
"SAVE_DIR = \"PPO-Model/\"+datetime.datetime.now().strftime(\"%m%d%H%M\")+\"/\"\n",
|
||||
"SAVE_DIR = \"PPO-Model/\" + datetime.datetime.now().strftime(\"%m%d%H%M\") + \"/\"\n",
|
||||
"LOAD_DIR = None\n",
|
||||
"\n",
|
||||
"CTN_ACTION_RANGE = 10"
|
||||
"CTN_ACTION_RANGE = 10\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -68,28 +69,27 @@
|
||||
"text": [
|
||||
"√√√√√Enviroment Initialized Success√√√√√\n",
|
||||
"√√√√√Buffer Initialized Success√√√√√\n",
|
||||
"Load Model:\n",
|
||||
"PPO-Model/09051841/190108\n",
|
||||
"No loadDir specified,Create a New Model\n",
|
||||
"CONTINUOUS_SIZE 1\n",
|
||||
"DISCRETE_SIZE 5\n",
|
||||
"STATE_SIZE 29\n"
|
||||
"STATE_SIZE 30\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# initialize enviroment & buffer class\n",
|
||||
"env = aimBotEnv.makeEnv(envPath = ENV_PATH,\n",
|
||||
" workerID = WORKER_ID,\n",
|
||||
" basePort = BASE_PORT)\n",
|
||||
"env = aimBotEnv.makeEnv(\n",
|
||||
" envPath=ENV_PATH, workerID=WORKER_ID, basePort=BASE_PORT\n",
|
||||
")\n",
|
||||
"epBuffer = buffer.buffer()\n",
|
||||
"\n",
|
||||
"STATE_SIZE = env.STATE_SIZE\n",
|
||||
"CONTINUOUS_SIZE = env.CONTINUOUS_SIZE\n",
|
||||
"DISCRETE_SIZE = env.DISCRETE_SIZE\n",
|
||||
"_,_,_,loadDir,_ = env.getSteps()\n",
|
||||
"_, _, _, loadDir, _ = env.getSteps()\n",
|
||||
"\n",
|
||||
"# check load model or not\n",
|
||||
"if(np.any(loadDir == 0)):\n",
|
||||
"if np.any(loadDir == 0):\n",
|
||||
" # create a new model\n",
|
||||
" print(\"No loadDir specified,Create a New Model\")\n",
|
||||
" LOAD_DIR = None\n",
|
||||
@ -97,23 +97,23 @@
|
||||
" # load model\n",
|
||||
" loadDirDateSTR = str(int(loadDir[0]))\n",
|
||||
" loadDirTimeSTR = str(int(loadDir[1]))\n",
|
||||
" if len(loadDirDateSTR)!=8:\n",
|
||||
" if len(loadDirDateSTR) != 8:\n",
|
||||
" # fill lost 0 while converse float to string\n",
|
||||
" for _ in range(8 - len(loadDirDateSTR)):\n",
|
||||
" loadDirDateSTR = \"0\" + loadDirDateSTR\n",
|
||||
" if len(loadDirTimeSTR)!=6:\n",
|
||||
" if len(loadDirTimeSTR) != 6:\n",
|
||||
" # fill lost 0 while converse float to string\n",
|
||||
" for _ in range(6 - len(loadDirTimeSTR)):\n",
|
||||
" loadDirTimeSTR = \"0\" + loadDirTimeSTR\n",
|
||||
" LOAD_DIR = \"PPO-Model/\"+loadDirDateSTR+\"/\"+loadDirTimeSTR\n",
|
||||
" LOAD_DIR = \"PPO-Model/\" + loadDirDateSTR + \"/\" + loadDirTimeSTR\n",
|
||||
" print(\"Load Model:\")\n",
|
||||
" print(LOAD_DIR)\n",
|
||||
"\n",
|
||||
"print(\"CONTINUOUS_SIZE\",CONTINUOUS_SIZE)\n",
|
||||
"print(\"DISCRETE_SIZE\",DISCRETE_SIZE)\n",
|
||||
"print(\"STATE_SIZE\",STATE_SIZE)\n",
|
||||
"print(\"CONTINUOUS_SIZE\", CONTINUOUS_SIZE)\n",
|
||||
"print(\"DISCRETE_SIZE\", DISCRETE_SIZE)\n",
|
||||
"print(\"STATE_SIZE\", STATE_SIZE)\n",
|
||||
"\n",
|
||||
"disActShape = [3,3,2]"
|
||||
"disActShape = [3, 3, 2]\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -160,11 +160,7 @@
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"EP 0 START\n",
|
||||
"√√√√√Buffer Initialized Success√√√√√\n",
|
||||
"++++++++++++++++++++++++++++++++++++\n",
|
||||
"++++++++++++Model Loaded++++++++++++\n",
|
||||
"PPO-Model/09051841/190108\n",
|
||||
"++++++++++++++++++++++++++++++++++++\n"
|
||||
"√√√√√Buffer Initialized Success√√√√√\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -181,603 +177,16 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"A_Loss: 128583691.2 C_Loss: 812.6740254720052\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 18745178.266666666 C_Loss: 154.92835998535156\n",
|
||||
"Model's Weights Saved\n",
|
||||
"New Record! Save NN -38.23000041767955\n",
|
||||
"EP 1 START\n",
|
||||
"A_Loss: 563364718.9333333 C_Loss: 813.9496988932292\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 2345777356.8 C_Loss: 1002.7922281901042\n",
|
||||
"Model's Weights Saved\n",
|
||||
"New Record! Save NN 6.009999185800552\n",
|
||||
"EP 2 START\n",
|
||||
"A_Loss: 135096590.93333334 C_Loss: 289.0239980061849\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -1.0771097699801127 C_Loss: 94.56021474202474\n",
|
||||
"EP 3 START\n",
|
||||
"A_Loss: 188551280.0 C_Loss: 178.76077473958333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -0.7733836094538371 C_Loss: 24.582142766316732\n",
|
||||
"EP 4 START\n",
|
||||
"A_Loss: 1542771293.8666666 C_Loss: 2540.582096354167\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 17443229.466666665 C_Loss: 403.4093978881836\n",
|
||||
"EP 5 START\n",
|
||||
"A_Loss: 0.9811522722244262 C_Loss: 173.3322311401367\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 0.062289920759697755 C_Loss: 83.96865743001302\n",
|
||||
"EP 6 START\n",
|
||||
"A_Loss: 207701843.2 C_Loss: 508.06519571940106\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 198849240.53333333 C_Loss: 318.39104512532555\n",
|
||||
"EP 7 START\n",
|
||||
"A_Loss: 227911159.46666667 C_Loss: 280.90660603841144\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 138269843.73333332 C_Loss: 530.1331217447917\n",
|
||||
"EP 8 START\n",
|
||||
"A_Loss: 944055261.8666667 C_Loss: 24907129397945.176\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -4141405.066666667 C_Loss: 49846409529480.53\n",
|
||||
"Model's Weights Saved\n",
|
||||
"New Record! Save NN 32.569999642670155\n",
|
||||
"EP 9 START\n",
|
||||
"A_Loss: 13671169501.866667 C_Loss: 44895753103.339066\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 43214365218.13333 C_Loss: 37662.319010416664\n",
|
||||
"EP 10 START\n",
|
||||
"A_Loss: 29955732002.133335 C_Loss: 68502.11927083334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 20331074764.8 C_Loss: 38761.32864583333\n",
|
||||
"EP 11 START\n",
|
||||
"A_Loss: 17149350843.733334 C_Loss: 41642.053385416664\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 16021737676.8 C_Loss: 24600.219270833335\n",
|
||||
"EP 12 START\n",
|
||||
"A_Loss: 20431896029.866665 C_Loss: 82939.88125\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 12221524718.933332 C_Loss: 41908.44921875\n",
|
||||
"EP 13 START\n",
|
||||
"A_Loss: 23195075515.733334 C_Loss: 72094.946875\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 30219999095.466667 C_Loss: 25428.986588541666\n",
|
||||
"EP 14 START\n",
|
||||
"A_Loss: 27674789614.933334 C_Loss: 77286.32708333334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 14385042363.733334 C_Loss: 44674.395833333336\n",
|
||||
"EP 15 START\n",
|
||||
"A_Loss: 6491561813.333333 C_Loss: 57468.32369791667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 14895148373.333334 C_Loss: 27674.523567708333\n",
|
||||
"EP 16 START\n",
|
||||
"A_Loss: 23592904157.866665 C_Loss: 54008.02786458333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 28394169002.666668 C_Loss: 35594.001302083336\n",
|
||||
"EP 17 START\n",
|
||||
"A_Loss: 31493442082.133335 C_Loss: 43341.80390625\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 15182564420.266666 C_Loss: 13120.031575520834\n",
|
||||
"EP 18 START\n",
|
||||
"A_Loss: 15298737561.6 C_Loss: 31930.973177083335\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 18384228215.466667 C_Loss: 20152.706770833334\n",
|
||||
"EP 19 START\n",
|
||||
"A_Loss: 19412337732.266666 C_Loss: 13991118556664.594\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 10120899857.066668 C_Loss: 39128662677.066666\n",
|
||||
"EP 20 START\n",
|
||||
"A_Loss: 19142413516.8 C_Loss: 129969.633203125\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 5016769467.733334 C_Loss: 9036.797916666666\n",
|
||||
"EP 21 START\n",
|
||||
"A_Loss: 18806764066.133335 C_Loss: 14859.599609375\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 8090647210.666667 C_Loss: 6834.12041015625\n",
|
||||
"EP 22 START\n",
|
||||
"A_Loss: 18050034210.133335 C_Loss: 15550.104427083334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 84.65721384684245 C_Loss: 9692.593880208333\n",
|
||||
"EP 23 START\n",
|
||||
"A_Loss: 11287560055.466667 C_Loss: 10906.8736328125\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 9644667630.933332 C_Loss: 8087.964127604167\n",
|
||||
"EP 24 START\n",
|
||||
"A_Loss: 3744549939.2 C_Loss: 5294.3908203125\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 263749590.4 C_Loss: 1567.651505533854\n",
|
||||
"EP 25 START\n",
|
||||
"A_Loss: 5730180334.933333 C_Loss: 3254.1029459635415\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 4258283246.9333334 C_Loss: 1893.0966227213542\n",
|
||||
"EP 26 START\n",
|
||||
"A_Loss: 2880076526.9333334 C_Loss: 1959.542569986979\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 3309443618.133333 C_Loss: 816.9943277994792\n",
|
||||
"EP 27 START\n",
|
||||
"A_Loss: 1501129864.5333333 C_Loss: 750.1781555175781\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 1310018705.0666666 C_Loss: 259.69133911132815\n",
|
||||
"EP 28 START\n",
|
||||
"A_Loss: 587718690.1333333 C_Loss: 433.7637430826823\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 532166058.6666667 C_Loss: 279.7773742675781\n",
|
||||
"EP 29 START\n",
|
||||
"A_Loss: 70524670.93333334 C_Loss: 65.66910146077474\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 73527637.06666666 C_Loss: 89.10262959798177\n",
|
||||
"EP 30 START\n",
|
||||
"A_Loss: 144336381.86666667 C_Loss: 11965969993490.188\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 1655646916881.0667 C_Loss: 10321726704401.066\n",
|
||||
"EP 31 START\n",
|
||||
"A_Loss: 41522109.46666667 C_Loss: 2869060630042.067\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -64.74283854166667 C_Loss: 16231.0900390625\n",
|
||||
"EP 32 START\n",
|
||||
"A_Loss: 3817272.5 C_Loss: 25434.281510416666\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 279540269.8666667 C_Loss: 10897.152734375\n",
|
||||
"EP 33 START\n",
|
||||
"A_Loss: -88.46073099772136 C_Loss: 19774.261588541667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 400722821.04817367 C_Loss: 7724.169270833333\n",
|
||||
"EP 34 START\n",
|
||||
"A_Loss: 1930250.1738263448 C_Loss: 12444.766927083334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 37003849.2 C_Loss: 8640.598307291666\n",
|
||||
"EP 35 START\n",
|
||||
"A_Loss: 55674022.4 C_Loss: 14830.487825520833\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 78330882.4 C_Loss: 7793.051595052083\n",
|
||||
"EP 36 START\n",
|
||||
"A_Loss: 10209805.2 C_Loss: 11949599399.99375\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 48724937985574.92 C_Loss: 17860793484356.266\n",
|
||||
"EP 37 START\n",
|
||||
"A_Loss: 4330507.568489583 C_Loss: 223605282927.2875\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 7667.229915364584 C_Loss: 57925.12994791667\n",
|
||||
"EP 38 START\n",
|
||||
"A_Loss: 184.12769877115886 C_Loss: 7122.831803385417\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 15510.455403645834 C_Loss: 52148.67734375\n",
|
||||
"EP 39 START\n",
|
||||
"A_Loss: 5272.286588541667 C_Loss: 286373.10833333334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 2.6445246855417888 C_Loss: 4984.467862955729\n",
|
||||
"EP 40 START\n",
|
||||
"A_Loss: 5228.9494140625 C_Loss: 366411.77291666664\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -288.28272705078126 C_Loss: 12667.800716145834\n",
|
||||
"EP 41 START\n",
|
||||
"A_Loss: 19474.684244791668 C_Loss: 45928038184215.41\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 2104.5810709635416 C_Loss: 276810.7479166667\n",
|
||||
"EP 42 START\n",
|
||||
"A_Loss: 61.346117909749346 C_Loss: 24438.237760416665\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 14208.790559895833 C_Loss: 220833.20625\n",
|
||||
"EP 43 START\n",
|
||||
"A_Loss: 5357.714680989583 C_Loss: 332224.36041666666\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 85.4434425354004 C_Loss: 6307.7271484375\n",
|
||||
"EP 44 START\n",
|
||||
"A_Loss: 122.99782867431641 C_Loss: 19919.213411458335\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 15087.8431640625 C_Loss: 161420.19166666668\n",
|
||||
"EP 45 START\n",
|
||||
"A_Loss: 1674.8425455729166 C_Loss: 309222.24166666664\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 1518.2337646484375 C_Loss: 349629.71041666664\n",
|
||||
"EP 46 START\n",
|
||||
"A_Loss: 2379.195491536458 C_Loss: 364705.35833333334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 209796462.2 C_Loss: 13010572456.520052\n",
|
||||
"EP 47 START\n",
|
||||
"A_Loss: -2574.44921875 C_Loss: 39260709.6\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -255952.503125 C_Loss: 1636249529955.0833\n",
|
||||
"EP 48 START\n",
|
||||
"A_Loss: 607266.8805664063 C_Loss: 40067520562.25208\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 2080.8306803385417 C_Loss: 175271.12291666667\n",
|
||||
"EP 49 START\n",
|
||||
"A_Loss: 592.0791585286458 C_Loss: 303988.81666666665\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 6402.670670572917 C_Loss: 52915.89296875\n",
|
||||
"EP 50 START\n",
|
||||
"A_Loss: 1395209.9906412761 C_Loss: 47937.68541666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 5355160.362174479 C_Loss: 46913.726822916666\n",
|
||||
"EP 51 START\n",
|
||||
"A_Loss: 131.98586934407552 C_Loss: 131763.49583333332\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 545.0480163574218 C_Loss: 177076.325\n",
|
||||
"EP 52 START\n",
|
||||
"A_Loss: -295055.39791666664 C_Loss: 21676655815489.375\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 96046800076.8 C_Loss: 2559427411968.0\n",
|
||||
"EP 53 START\n",
|
||||
"A_Loss: 23993694.0 C_Loss: 400391016517.3333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 93352.0390625 C_Loss: 619253805875.2\n",
|
||||
"EP 54 START\n",
|
||||
"A_Loss: 2732956.3833333333 C_Loss: 46527696896.0\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 39510.85885416667 C_Loss: 28781911654.4\n",
|
||||
"EP 55 START\n",
|
||||
"A_Loss: -29427.872395833332 C_Loss: 5438102272.0\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 90085.98177083333 C_Loss: 3624150245.866667\n",
|
||||
"EP 56 START\n",
|
||||
"A_Loss: -498753.30625 C_Loss: 823590289405.8667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 10569771.733333332 C_Loss: 2970159109461.3335\n",
|
||||
"EP 57 START\n",
|
||||
"A_Loss: -50644.94348958333 C_Loss: 646384501282.1333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 23941.277994791668 C_Loss: 53731624072.53333\n",
|
||||
"EP 58 START\n",
|
||||
"A_Loss: -199527.115625 C_Loss: 2830466387626.6665\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 5080.106127929687 C_Loss: 1123213416857.6\n",
|
||||
"EP 59 START\n",
|
||||
"A_Loss: 854754.9208333333 C_Loss: 89255951291.73334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -6642.098014322916 C_Loss: 2435903428.266667\n",
|
||||
"EP 60 START\n",
|
||||
"A_Loss: 21668.172135416666 C_Loss: 4344311575859.2\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -2874.193896484375 C_Loss: 1691038327.4666667\n",
|
||||
"EP 61 START\n",
|
||||
"A_Loss: 46610.647135416664 C_Loss: 355761074.1333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 174212.034375 C_Loss: 49708919.233333334\n",
|
||||
"EP 62 START\n",
|
||||
"A_Loss: 135704.40625 C_Loss: 47006909.06666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 10387.477018229167 C_Loss: 51938460.8\n",
|
||||
"EP 63 START\n",
|
||||
"A_Loss: 594.3608805338541 C_Loss: 16747537224969.105\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 109.09736455281576 C_Loss: 4015293.466666667\n",
|
||||
"EP 64 START\n",
|
||||
"A_Loss: 2528.45546875 C_Loss: 5244184.566666666\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 228.57803039550782 C_Loss: 4565261.5\n",
|
||||
"EP 65 START\n",
|
||||
"A_Loss: 576.867138671875 C_Loss: 690111.6791666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 2555.884700520833 C_Loss: 1223311.4583333333\n",
|
||||
"EP 66 START\n",
|
||||
"A_Loss: 1392.1302897135417 C_Loss: 4376503.633333334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 3898.088427734375 C_Loss: 2490652.9833333334\n",
|
||||
"EP 67 START\n",
|
||||
"A_Loss: 456.2262491861979 C_Loss: 1098666.3\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -223.93345540364584 C_Loss: 2048068.5666666667\n",
|
||||
"EP 68 START\n",
|
||||
"A_Loss: -439.01691080729165 C_Loss: 2945374.433333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -24.373832575480144 C_Loss: 343411.81875\n",
|
||||
"EP 69 START\n",
|
||||
"A_Loss: 5111.536979166666 C_Loss: 10348606653210.434\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -38.84524319966634 C_Loss: 1990322.725\n",
|
||||
"EP 70 START\n",
|
||||
"A_Loss: 951.8831461588542 C_Loss: 223227.01875\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 172.96959330240887 C_Loss: 1922374.9416666667\n",
|
||||
"EP 71 START\n",
|
||||
"A_Loss: 39.82610600789388 C_Loss: 533955.7208333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 620.001796468099 C_Loss: 282419.71979166666\n",
|
||||
"EP 72 START\n",
|
||||
"A_Loss: 10333.698046875 C_Loss: 2511066.466666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -83.75911153157553 C_Loss: 1593542.8833333333\n",
|
||||
"EP 73 START\n",
|
||||
"A_Loss: 1590.978955078125 C_Loss: 931809.2333333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 189.47867533365886 C_Loss: 1312441.1333333333\n",
|
||||
"EP 74 START\n",
|
||||
"A_Loss: -4686.18564453125 C_Loss: 8461484.133333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 152230.85208333333 C_Loss: 26483003486139.734\n",
|
||||
"EP 75 START\n",
|
||||
"A_Loss: 543.5623474121094 C_Loss: 676008774.1916667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 72.8592913309733 C_Loss: 646183.675\n",
|
||||
"EP 76 START\n",
|
||||
"A_Loss: -111.36540323893229 C_Loss: 1268551.3833333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -86.98175252278646 C_Loss: 1884845.4166666667\n",
|
||||
"EP 77 START\n",
|
||||
"A_Loss: 9.363872464497884 C_Loss: 574981.4\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 10.75021572113037 C_Loss: 1757512.1051269532\n",
|
||||
"EP 78 START\n",
|
||||
"A_Loss: -91.82536315917969 C_Loss: 1116194.3125\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -2419.4617513020835 C_Loss: 9647680415.9\n",
|
||||
"EP 79 START\n",
|
||||
"A_Loss: 12534.184114583333 C_Loss: 125233972.73333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -12864.7326171875 C_Loss: 32251742043101.867\n",
|
||||
"EP 80 START\n",
|
||||
"A_Loss: 69521.21354166667 C_Loss: 239759950.93333334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 1941.87587890625 C_Loss: 3182419.7\n",
|
||||
"EP 81 START\n",
|
||||
"A_Loss: 48.873761876424155 C_Loss: 2138957.5\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -172.59212137858074 C_Loss: 1479709.7\n",
|
||||
"EP 82 START\n",
|
||||
"A_Loss: -217.69344889322917 C_Loss: 1724748.0333333334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 8.864885139465333 C_Loss: 2801.1948404947916\n",
|
||||
"EP 83 START\n",
|
||||
"A_Loss: -23.036806042989095 C_Loss: 487250.31875\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -85.1435302734375 C_Loss: 459072.14375\n",
|
||||
"EP 84 START\n",
|
||||
"A_Loss: -159.0248555501302 C_Loss: 704506.4\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 391660.59375 C_Loss: 185407429.55\n",
|
||||
"EP 85 START\n",
|
||||
"A_Loss: 11304412.4 C_Loss: 436438987025.06665\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -508119.4666666667 C_Loss: 27526751540565.332\n",
|
||||
"EP 86 START\n",
|
||||
"A_Loss: 8.469103686014812 C_Loss: 35030720904.04556\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 79.07336120605468 C_Loss: 2628.575537109375\n",
|
||||
"EP 87 START\n",
|
||||
"A_Loss: 87.94131622314453 C_Loss: 3291.388395182292\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 63.07492167154948 C_Loss: 3989.5349609375\n",
|
||||
"EP 88 START\n",
|
||||
"A_Loss: 9.08399314880371 C_Loss: 3549.7614908854166\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 47.93385569254557 C_Loss: 1957.0295735677084\n",
|
||||
"EP 89 START\n",
|
||||
"A_Loss: 76.6830576578776 C_Loss: 4872.250081380208\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 77.35536549886068 C_Loss: 1778.1133951822917\n",
|
||||
"EP 90 START\n",
|
||||
"A_Loss: 26.445547739664715 C_Loss: 1201.9427978515625\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 37.380027770996094 C_Loss: 2120.48583984375\n",
|
||||
"EP 91 START\n",
|
||||
"A_Loss: 62.73122533162435 C_Loss: 1910.77255859375\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 7.070840994517009 C_Loss: 2663.728580729167\n",
|
||||
"Model's Weights Saved\n",
|
||||
"New Record! Save NN 36.159999914467335\n",
|
||||
"EP 92 START\n",
|
||||
"A_Loss: 83.22457122802734 C_Loss: 4142.598046875\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -2965967.5 C_Loss: 89986176198316.5\n",
|
||||
"EP 93 START\n",
|
||||
"A_Loss: 5039913.333333333 C_Loss: 11098771021277.867\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 15480.3697265625 C_Loss: 119004974489.6\n",
|
||||
"EP 94 START\n",
|
||||
"A_Loss: -16268.488020833332 C_Loss: 2171354205.866667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 25105.733463541666 C_Loss: 180378952.53333333\n",
|
||||
"EP 95 START\n",
|
||||
"A_Loss: -356.90814819335935 C_Loss: 4823839.716666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -103.6774673461914 C_Loss: 1091913.1416666666\n",
|
||||
"EP 96 START\n",
|
||||
"A_Loss: 132.41912180582682 C_Loss: 3535627.6166666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -250.67224629720053 C_Loss: 2047510.1\n",
|
||||
"EP 97 START\n",
|
||||
"A_Loss: 191.60374145507814 C_Loss: 2080957.1833333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 317.184033203125 C_Loss: 1221589.425\n",
|
||||
"EP 98 START\n",
|
||||
"A_Loss: -39.01324615478516 C_Loss: 998958.2208333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -190.1520253499349 C_Loss: 1742518.1\n",
|
||||
"EP 99 START\n",
|
||||
"A_Loss: 311.61248372395835 C_Loss: 620184.1416666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -264.8520751953125 C_Loss: 1779512.7666666666\n",
|
||||
"EP 100 START\n",
|
||||
"A_Loss: -94.42798614501953 C_Loss: 1547244.1833333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -153766.15104166666 C_Loss: 33501732032887.137\n",
|
||||
"EP 101 START\n",
|
||||
"A_Loss: 60208.17265625 C_Loss: 27465943313.066666\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 17862.422265625 C_Loss: 988074240.0\n",
|
||||
"EP 102 START\n",
|
||||
"A_Loss: 28635.012890625 C_Loss: 144180219.2\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 265.3567850748698 C_Loss: 2369780.45\n",
|
||||
"EP 103 START\n",
|
||||
"A_Loss: -17.382435480753582 C_Loss: 726623.9833333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 16.159270922342937 C_Loss: 124937.20364583333\n",
|
||||
"EP 104 START\n",
|
||||
"A_Loss: 180.78487548828124 C_Loss: 2608104.4\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -472.0964823404948 C_Loss: 3132594.6666666665\n",
|
||||
"EP 105 START\n",
|
||||
"A_Loss: -245.632177734375 C_Loss: 1839736.6333333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -84.94388631184896 C_Loss: 788294.0833333334\n",
|
||||
"EP 106 START\n",
|
||||
"A_Loss: -344.7350769042969 C_Loss: 2457982.183333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 247.77904154459637 C_Loss: 191985.88020833334\n",
|
||||
"EP 107 START\n",
|
||||
"A_Loss: -93.01107330322266 C_Loss: 1014136.5958333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -301.968603515625 C_Loss: 2097648.5416666665\n",
|
||||
"EP 108 START\n",
|
||||
"A_Loss: -355.8355692545573 C_Loss: 2356025.3333333335\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -176.879106648763 C_Loss: 905950.4666666667\n",
|
||||
"EP 109 START\n",
|
||||
"A_Loss: 2279212.8916666666 C_Loss: 5355236439927.467\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 230154.93229166666 C_Loss: 21897054401331.2\n",
|
||||
"EP 110 START\n",
|
||||
"A_Loss: 204.3412821451823 C_Loss: 11179356820.975\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -44.459004465738936 C_Loss: 606090.0875\n",
|
||||
"EP 111 START\n",
|
||||
"A_Loss: -55.804770151774086 C_Loss: 453019.00625\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 437.7322265625 C_Loss: 531331.7\n",
|
||||
"EP 112 START\n",
|
||||
"A_Loss: -176.73267822265626 C_Loss: 1254341.2416666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -9.164166609446207 C_Loss: 116005.52552083334\n",
|
||||
"EP 113 START\n",
|
||||
"A_Loss: 57.09782918294271 C_Loss: 590456.1916666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -28.08950449625651 C_Loss: 368954.27291666664\n",
|
||||
"EP 114 START\n",
|
||||
"A_Loss: -141.4985616048177 C_Loss: 545265.2583333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 196.88966267903646 C_Loss: 262787.0489583333\n",
|
||||
"EP 115 START\n",
|
||||
"A_Loss: 9875956.133333333 C_Loss: 3146464274264.442\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 74947.0171875 C_Loss: 1476110921523.2\n",
|
||||
"EP 116 START\n",
|
||||
"A_Loss: -147298.26770833333 C_Loss: 7414750106920.533\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -61223.323958333334 C_Loss: 166082947754.66666\n",
|
||||
"EP 117 START\n",
|
||||
"A_Loss: 155204.75208333333 C_Loss: 54631106969.6\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -5608.896809895833 C_Loss: 239498007.5\n",
|
||||
"EP 118 START\n",
|
||||
"A_Loss: 64438.151041666664 C_Loss: 1624584972.8\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 2922.034130859375 C_Loss: 6422857095816.533\n",
|
||||
"EP 119 START\n",
|
||||
"A_Loss: 4014.168212890625 C_Loss: 72697799.46666667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 1831.806486002604 C_Loss: 35837436.0\n",
|
||||
"EP 120 START\n",
|
||||
"A_Loss: 10667.054622395834 C_Loss: 26391209.166666668\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 127434.12447916667 C_Loss: 182761787114.13333\n",
|
||||
"EP 121 START\n",
|
||||
"A_Loss: 143913.98645833333 C_Loss: 1208985656729.6\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 16578.108658854166 C_Loss: 1837287090.1333334\n",
|
||||
"EP 122 START\n",
|
||||
"A_Loss: -117467.396875 C_Loss: 1478863227690.6667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -70148.46614583333 C_Loss: 5382309429111.467\n",
|
||||
"EP 123 START\n",
|
||||
"A_Loss: -49.01672922770182 C_Loss: 3541015449.633333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -40.59830932617187 C_Loss: 352259.06875\n",
|
||||
"EP 124 START\n",
|
||||
"A_Loss: -95.25742848714192 C_Loss: 858177.2\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -52.94597473144531 C_Loss: 293412.5625\n",
|
||||
"EP 125 START\n",
|
||||
"A_Loss: -225.69961649576823 C_Loss: 748738.2375\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -4.78879960378011 C_Loss: 123586.36875\n",
|
||||
"EP 126 START\n",
|
||||
"A_Loss: -201.62482401529948 C_Loss: 720683.4833333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -21.21190528869629 C_Loss: 35503.817057291664\n",
|
||||
"EP 127 START\n",
|
||||
"A_Loss: 152.8080861409505 C_Loss: 41394907675409.0\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 3.5420272588729858 C_Loss: 95929.18802083333\n",
|
||||
"EP 128 START\n",
|
||||
"A_Loss: -2.3434098323186237 C_Loss: 43473.105729166666\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -31.295360438028972 C_Loss: 90783.04791666666\n",
|
||||
"EP 129 START\n",
|
||||
"A_Loss: 361140.66041666665 C_Loss: 72744.59609375\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 2418.9001627604166 C_Loss: 3928226928.5666666\n",
|
||||
"EP 130 START\n",
|
||||
"A_Loss: 11.188031895955403 C_Loss: 146395.30833333332\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -288.8839884440104 C_Loss: 726967.2367838542\n",
|
||||
"EP 131 START\n",
|
||||
"A_Loss: 228.3966074625651 C_Loss: 1645105.6708333334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 56.98198420206706 C_Loss: 80022.94166666667\n",
|
||||
"EP 132 START\n",
|
||||
"A_Loss: 32.61619491577149 C_Loss: 13436.4310546875\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -3.019519786039988 C_Loss: 26069.423307291665\n",
|
||||
"EP 133 START\n",
|
||||
"A_Loss: 5.228196366628011 C_Loss: 25157.172005208333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 13.022575950622558 C_Loss: 3747.759977213542\n",
|
||||
"EP 134 START\n",
|
||||
"A_Loss: -80517.8953125 C_Loss: 15650603660651.291\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 16014.4521484375 C_Loss: 9164626090.666666\n",
|
||||
"EP 135 START\n",
|
||||
"A_Loss: 117133.68125 C_Loss: 87002011844.26666\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 15981.832682291666 C_Loss: 47913645943.46667\n",
|
||||
"EP 136 START\n",
|
||||
"A_Loss: 19723.941666666666 C_Loss: 610387874.1333333\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -6.982747983932495 C_Loss: 42435512.56666667\n",
|
||||
"EP 137 START\n",
|
||||
"A_Loss: -177.51118876139324 C_Loss: 1209231.775\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -18.883594957987466 C_Loss: 646092.9708333333\n",
|
||||
"EP 138 START\n",
|
||||
"A_Loss: 152.13518269856772 C_Loss: 282594.4010416667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 18.2394229888916 C_Loss: 124778.96979166666\n",
|
||||
"EP 139 START\n",
|
||||
"A_Loss: 165.62351684570314 C_Loss: 132396.28125\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -245.43899637858073 C_Loss: 928183.8291666667\n",
|
||||
"EP 140 START\n",
|
||||
"A_Loss: -104456.69375 C_Loss: 1376307509015.4375\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 9644.121158854166 C_Loss: 66630244983.46667\n",
|
||||
"EP 141 START\n",
|
||||
"A_Loss: -92.3751708984375 C_Loss: 142594040.71354166\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 29.573409907023112 C_Loss: 46747.54921875\n",
|
||||
"EP 142 START\n",
|
||||
"A_Loss: 1008713.7708333334 C_Loss: 20930468997730.31\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: -80090.73802083333 C_Loss: 1022462403106.1333\n",
|
||||
"EP 143 START\n",
|
||||
"A_Loss: -23560.799739583334 C_Loss: 32153040110.933334\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 3245.091129557292 C_Loss: 950403610.1333333\n",
|
||||
"EP 144 START\n",
|
||||
"A_Loss: 184.1011952718099 C_Loss: 1113755.1979166667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 963.6497111002604 C_Loss: 1592140.8416666666\n",
|
||||
"EP 145 START\n",
|
||||
"A_Loss: 315.7770711263021 C_Loss: 494445.6979166667\n",
|
||||
"EP OVER!\n",
|
||||
"A_Loss: 440.2256103515625 C_Loss: 490657.3229166667\n",
|
||||
"EP 146 START\n"
|
||||
"A_Loss: 0.4477495511372884 C_Loss: 3.155759557088216\n",
|
||||
"A_Loss: 0.14549287557601928 C_Loss: 0.5123071213563283\n",
|
||||
"A_Loss: 0.055241942902406055 C_Loss: 0.13002794484297434\n",
|
||||
"A_Loss: 0.057325509190559384 C_Loss: 0.11068039039770762\n",
|
||||
"A_Loss: 0.04376962607105573 C_Loss: 0.03923700377345085\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"bestScore = 200.\n",
|
||||
"bestScore = 200.0\n",
|
||||
"stopTrainCounter = 0\n",
|
||||
"\n",
|
||||
"totalRewardHis = []\n",
|
||||
@ -787,60 +196,79 @@
|
||||
"maxTotalReward = -99999999999\n",
|
||||
"\n",
|
||||
"for ep in range(MAX_EP):\n",
|
||||
" print(\"EP \",ep,\" START\")\n",
|
||||
" print(\"EP \", ep, \" START\")\n",
|
||||
" # first time run game\n",
|
||||
" s,_,_,_,_ = env.reset()\n",
|
||||
" if (ep == 0):\n",
|
||||
" s, _, _, _, _ = env.reset()\n",
|
||||
" if ep == 0:\n",
|
||||
" epBuffer = buffer.buffer()\n",
|
||||
" s = s.reshape([STATE_SIZE])\n",
|
||||
" agent = PPO.PPO(stateSize=STATE_SIZE,\n",
|
||||
" disActShape=disActShape,\n",
|
||||
" conActSize=1,\n",
|
||||
" conActRange=CTN_ACTION_RANGE,\n",
|
||||
" criticLR=CRITIC_LR,\n",
|
||||
" actorLR=ACTOR_LR,\n",
|
||||
" gamma=GAMMA,\n",
|
||||
" epsilon=EPSILON,\n",
|
||||
" entropyWeight=ENTROPY_WHEIGHT,\n",
|
||||
" saveDir=SAVE_DIR,\n",
|
||||
" loadModelDir=LOAD_DIR)\n",
|
||||
" agent = PPO.PPO(\n",
|
||||
" stateSize=STATE_SIZE,\n",
|
||||
" disActShape=disActShape,\n",
|
||||
" conActSize=1,\n",
|
||||
" conActRange=CTN_ACTION_RANGE,\n",
|
||||
" criticLR=CRITIC_LR,\n",
|
||||
" actorLR=ACTOR_LR,\n",
|
||||
" gamma=GAMMA,\n",
|
||||
" epsilon=EPSILON,\n",
|
||||
" entropyWeight=ENTROPY_WHEIGHT,\n",
|
||||
" saveDir=SAVE_DIR,\n",
|
||||
" loadModelDir=LOAD_DIR,\n",
|
||||
" )\n",
|
||||
" step = 0\n",
|
||||
" done = False\n",
|
||||
" stopTrainCounter -= 1\n",
|
||||
" epHis.append(ep)\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" # reset total reward\n",
|
||||
" epTotalReward = 0\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" # Recorder list\n",
|
||||
" epStepHis = []\n",
|
||||
" epRewardHis = []\n",
|
||||
" epActorLossHis = []\n",
|
||||
" epCriticLossHis = []\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" # save weight immediately?\n",
|
||||
" saveNow = 0;\n",
|
||||
" saveNow = 0\n",
|
||||
"\n",
|
||||
" while not done:\n",
|
||||
" step += 1\n",
|
||||
" if step % ACTION_INTERVAL == 0: # take action every ACTION_INTERVAL steps\n",
|
||||
" if (\n",
|
||||
" step % ACTION_INTERVAL == 0\n",
|
||||
" ): # take action every ACTION_INTERVAL steps\n",
|
||||
" epStepHis.append(step)\n",
|
||||
" disAct1,disAct2,disAct3,conAct,predictResult = agent.chooseAction(s)\n",
|
||||
" kW, kS, kA, kD, mouseShoot, mouseMove = actToKey(disAct1,disAct2,disAct3,conAct)\n",
|
||||
" \n",
|
||||
" nextState,thisReward,done,_,saveNow = env.step(discreteActions=np.array([[kW, kS, kA, kD, mouseShoot]]),continuousActions=np.array([[mouseMove]]))\n",
|
||||
" (\n",
|
||||
" disAct1,\n",
|
||||
" disAct2,\n",
|
||||
" disAct3,\n",
|
||||
" conAct,\n",
|
||||
" predictResult,\n",
|
||||
" ) = agent.chooseAction(s)\n",
|
||||
" kW, kS, kA, kD, mouseShoot, mouseMove = actToKey(\n",
|
||||
" disAct1, disAct2, disAct3, conAct\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" nextState, thisReward, done, _, saveNow = env.step(\n",
|
||||
" discreteActions=np.array([[kW, kS, kA, kD, mouseShoot]]),\n",
|
||||
" continuousActions=np.array([[mouseMove]]),\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" epTotalReward += thisReward\n",
|
||||
" epBuffer.saveBuffers(s,[disAct1,disAct2,disAct3,conAct],thisReward)\n",
|
||||
" epBuffer.saveBuffers(\n",
|
||||
" s, [disAct1, disAct2, disAct3, conAct], thisReward\n",
|
||||
" )\n",
|
||||
" else:\n",
|
||||
" disActs = np.array([[0,0,0,0,0]])\n",
|
||||
" disActs = np.array([[0, 0, 0, 0, 0]])\n",
|
||||
" conActs = np.array([[0]])\n",
|
||||
"\n",
|
||||
" nextState,thisReward,done,_,saveNow = env.step(discreteActions=disActs,continuousActions=conActs)\n",
|
||||
" nextState, thisReward, done, _, saveNow = env.step(\n",
|
||||
" discreteActions=disActs, continuousActions=conActs\n",
|
||||
" )\n",
|
||||
" epTotalReward += thisReward\n",
|
||||
" nextState = nextState.reshape([STATE_SIZE])\n",
|
||||
" s = nextState\n",
|
||||
" \n",
|
||||
"\n",
|
||||
" if done:\n",
|
||||
" print(\"EP OVER!\")\n",
|
||||
" if saveNow != 0:\n",
|
||||
@ -848,25 +276,26 @@
|
||||
" saveNow = 0\n",
|
||||
" agent.saveWeights()\n",
|
||||
" # update PPO after Batch step or GameOver\n",
|
||||
" if (step+1)%BATCH == 0 or done:\n",
|
||||
" if (step + 1) % BATCH == 0 or done:\n",
|
||||
" bs = epBuffer.getStates()\n",
|
||||
" ba = epBuffer.getActions()\n",
|
||||
" br = epBuffer.getRewards()\n",
|
||||
" epBuffer.clearBuffer()\n",
|
||||
" if TRAIN:\n",
|
||||
" epActorLoss,epCriticLoss = agent.trainCritcActor(bs,ba,br,s,CRITIC_EPOCH,ACTOR_EPOCH)\n",
|
||||
" epActorLoss, epCriticLoss = agent.trainCritcActor(\n",
|
||||
" bs, ba, br, s, CRITIC_EPOCH, ACTOR_EPOCH\n",
|
||||
" )\n",
|
||||
" epActorLossHis.append(epActorLoss)\n",
|
||||
" epCriticLossHis.append(epCriticLoss)\n",
|
||||
" # update History Recorder\n",
|
||||
" totalActorLossHis.append(np.mean(epActorLossHis))\n",
|
||||
" totalCriticLossHis.append(np.mean(epCriticLossHis))\n",
|
||||
" totalRewardHis.append(epTotalReward)\n",
|
||||
" \n",
|
||||
" if (epTotalReward > maxTotalReward and epTotalReward != 0):\n",
|
||||
"\n",
|
||||
" if epTotalReward > maxTotalReward and epTotalReward != 0:\n",
|
||||
" maxTotalReward = epTotalReward\n",
|
||||
" agent.saveWeights(epTotalReward)\n",
|
||||
" print(\"New Record! Save NN\",epTotalReward)\n",
|
||||
" "
|
||||
" print(\"New Record! Save NN\", epTotalReward)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -1,7 +1,17 @@
|
||||
import numpy as np
|
||||
|
||||
|
||||
class rewardAI(object):
|
||||
def __init__(self,nonReward, shootReward, shootWithoutReadyReward, hitReward, winReward, loseReward, killReward):
|
||||
def __init__(
|
||||
self,
|
||||
nonReward,
|
||||
shootReward,
|
||||
shootWithoutReadyReward,
|
||||
hitReward,
|
||||
winReward,
|
||||
loseReward,
|
||||
killReward,
|
||||
):
|
||||
self.nonReward = nonReward
|
||||
self.shootReward = shootReward
|
||||
self.shootWithoutReadyReward = shootWithoutReadyReward
|
||||
@ -9,8 +19,8 @@ class rewardAI(object):
|
||||
self.winReward = winReward
|
||||
self.loseReward = loseReward
|
||||
self.killReward = killReward
|
||||
|
||||
def getRewards(self,remainTime):
|
||||
|
||||
def getRewards(self, remainTime):
|
||||
nonR = self.getnonReward()
|
||||
shootR = self.getshootReward()
|
||||
shootWithoutReadyR = self.getshootWithoutReadyReward()
|
||||
@ -18,27 +28,30 @@ class rewardAI(object):
|
||||
winR = self.getwinReward(remainTime)
|
||||
loseR = self.getloseReward()
|
||||
killR = self.getkillReward(remainTime)
|
||||
|
||||
rewards = np.array([[nonR,
|
||||
shootR,
|
||||
shootWithoutReadyR,
|
||||
hitR,
|
||||
winR,
|
||||
loseR,
|
||||
killR]], dtype=np.float)
|
||||
|
||||
rewards = np.array(
|
||||
[[nonR, shootR, shootWithoutReadyR, hitR, winR, loseR, killR]],
|
||||
dtype=np.float,
|
||||
)
|
||||
return rewards
|
||||
|
||||
def getnonReward (self):
|
||||
|
||||
def getnonReward(self):
|
||||
return self.nonReward
|
||||
|
||||
def getshootReward(self):
|
||||
return self.shootReward
|
||||
|
||||
def getshootWithoutReadyReward(self):
|
||||
return self.shootWithoutReadyReward
|
||||
|
||||
def gethitReward(self):
|
||||
return self.hitReward
|
||||
def getwinReward(self,time):
|
||||
return (self.winReward + time)
|
||||
|
||||
def getwinReward(self, time):
|
||||
return self.winReward + time
|
||||
|
||||
def getloseReward(self):
|
||||
return self.loseReward
|
||||
def getkillReward(self,time):
|
||||
return (self.killReward + time)
|
||||
|
||||
def getkillReward(self, time):
|
||||
return self.killReward + time
|
||||
|
||||
@ -19,12 +19,12 @@
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"state = np.array([[1,2,3],[1,2,3]])\n",
|
||||
"state = np.array([[1, 2, 3], [1, 2, 3]])\n",
|
||||
"aaa = np.array([[123]])\n",
|
||||
"\n",
|
||||
"state[:,-1]\n",
|
||||
"state[:, -1]\n",
|
||||
"\n",
|
||||
"np.append([[1, 2, 3]], [[7, 8, 9, 10]], axis=1)"
|
||||
"np.append([[1, 2, 3]], [[7, 8, 9, 10]], axis=1)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -36,22 +36,22 @@
|
||||
"import tensorflow as tf\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"aa = tf.constant([[1,2,3],[1,2,3],[1,2,3],[1,2,3]])\n",
|
||||
"bb = tf.constant([1,2,3,4])\n",
|
||||
"aa = tf.constant([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]])\n",
|
||||
"bb = tf.constant([1, 2, 3, 4])\n",
|
||||
"\n",
|
||||
"print(tf.expand_dims(bb,axis=1))\n",
|
||||
"print(tf.expand_dims(bb, axis=1))\n",
|
||||
"\n",
|
||||
"cc = tf.math.multiply(aa,tf.expand_dims(bb,axis = 1))\n",
|
||||
"cc = tf.math.multiply(aa, tf.expand_dims(bb, axis=1))\n",
|
||||
"\n",
|
||||
"print(cc)\n",
|
||||
"print(tf.shape(aa))\n",
|
||||
"\n",
|
||||
"print(aa[:,2:3])\n",
|
||||
"print(aa[:, 2:3])\n",
|
||||
"\n",
|
||||
"aa = tf.constant([1.0,2.0,3.0,np.nan])\n",
|
||||
"aa = tf.constant([1.0, 2.0, 3.0, np.nan])\n",
|
||||
"print(np.any(tf.math.is_nan(aa)))\n",
|
||||
"if np.any(tf.math.is_nan(aa)):\n",
|
||||
" print('true')"
|
||||
" print(\"true\")\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -62,11 +62,13 @@
|
||||
"source": [
|
||||
"import tensorflow as tf\n",
|
||||
"\n",
|
||||
"prob = tf.constant([0.3,0.3,0.])\n",
|
||||
"prob = tf.constant([0.3, 0.3, 0.0])\n",
|
||||
"\n",
|
||||
"entropy = tf.reduce_mean(tf.math.negative(tf.math.multiply(prob,tf.math.log(prob))))\n",
|
||||
"entropy = tf.reduce_mean(\n",
|
||||
" tf.math.negative(tf.math.multiply(prob, tf.math.log(prob)))\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"print(entropy)"
|
||||
"print(entropy)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -87,25 +89,31 @@
|
||||
],
|
||||
"source": [
|
||||
"from functools import singledispatchmethod\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"class person:\n",
|
||||
" @singledispatchmethod\n",
|
||||
" def age(self,arg):\n",
|
||||
" def age(self, arg):\n",
|
||||
" print(\"error\")\n",
|
||||
"\n",
|
||||
" @age.register(int)\n",
|
||||
" def _(self,arg:int):\n",
|
||||
" print(\"int\",arg)\n",
|
||||
" def _(self, arg: int):\n",
|
||||
" print(\"int\", arg)\n",
|
||||
"\n",
|
||||
" @age.register(str)\n",
|
||||
" def _(self,arg:str):\n",
|
||||
" print(\"str\",arg)\n",
|
||||
" def _(self, arg: str):\n",
|
||||
" print(\"str\", arg)\n",
|
||||
"\n",
|
||||
" @age.register(bool)\n",
|
||||
" def _(self,arg:bool):\n",
|
||||
" print(\"bool\",arg)\n",
|
||||
" def _(self, arg: bool):\n",
|
||||
" print(\"bool\", arg)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"p = person()\n",
|
||||
"p.age(23) # int\n",
|
||||
"p.age('twenty three') # str\n",
|
||||
"p.age(\"twenty three\") # str\n",
|
||||
"p.age(True) # bool\n",
|
||||
"p.age(['23']) # list\n"
|
||||
"p.age([\"23\"]) # list\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -117,6 +125,7 @@
|
||||
"import tensorflow as tf\n",
|
||||
"import tensorflow.keras.layers as layers\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def conv_bn_relu(inputs, chs, reps):\n",
|
||||
" x = inputs\n",
|
||||
" for i in range(reps):\n",
|
||||
@ -125,6 +134,7 @@
|
||||
" x = layers.ReLU()(x)\n",
|
||||
" return x\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def create_model():\n",
|
||||
" inputs = layers.Input((32, 32, 3))\n",
|
||||
" x = conv_bn_relu(inputs, 64, 3)\n",
|
||||
@ -136,27 +146,38 @@
|
||||
" x = layers.Dense(10, activation=\"softmax\")(x)\n",
|
||||
" return tf.keras.models.Model(inputs, x)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def perprocess(img, label):\n",
|
||||
" img = tf.cast(img, tf.float32) / 255.0\n",
|
||||
" label = tf.cast(label, tf.float32)\n",
|
||||
" return img, label\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def train():\n",
|
||||
" (X_train, y_train), (X_test, y_test) = tf.keras.datasets.cifar10.load_data()\n",
|
||||
" trainset = tf.data.Dataset.from_tensor_slices((X_train, y_train)\n",
|
||||
" ).map(perprocess).shuffle(4096).batch(128).repeat().prefetch(50)\n",
|
||||
" (X_train, y_train), (\n",
|
||||
" X_test,\n",
|
||||
" y_test,\n",
|
||||
" ) = tf.keras.datasets.cifar10.load_data()\n",
|
||||
" trainset = (\n",
|
||||
" tf.data.Dataset.from_tensor_slices((X_train, y_train))\n",
|
||||
" .map(perprocess)\n",
|
||||
" .shuffle(4096)\n",
|
||||
" .batch(128)\n",
|
||||
" .repeat()\n",
|
||||
" .prefetch(50)\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" model = create_model()\n",
|
||||
" model.compile(\"adam\", \"sparse_categorical_crossentropy\", [\"acc\"])\n",
|
||||
"\n",
|
||||
" model.fit(trainset, steps_per_epoch=50000//128, epochs=1) \n",
|
||||
" # 'Adam/conv2d/kernel/m:0' shape=(3, 3, 3, 64) \n",
|
||||
" print(model.optimizer.weights[1][0, 0, 0,:10])\n",
|
||||
" model.fit(trainset, steps_per_epoch=50000 // 128, epochs=1)\n",
|
||||
" # 'Adam/conv2d/kernel/m:0' shape=(3, 3, 3, 64)\n",
|
||||
" print(model.optimizer.weights[1][0, 0, 0, :10])\n",
|
||||
" # <tf.Variable 'conv2d/kernel:0' shape=(3, 3, 3, 64)\n",
|
||||
" print(model.weights[0][0, 0, 0,:10])\n",
|
||||
" print(model.weights[0][0, 0, 0, :10])\n",
|
||||
"\n",
|
||||
" model.save_weights(\"model_tf.ckpt\", save_format=\"tf\") # デフォルト\n",
|
||||
" model.save_weights(\"model_h5.h5\", save_format=\"h5\") "
|
||||
" model.save_weights(\"model_h5.h5\", save_format=\"h5\")\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -179,7 +200,7 @@
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"train()"
|
||||
"train()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -210,9 +231,11 @@
|
||||
"\n",
|
||||
" model.load_weights(\"model_tf.ckpt\")\n",
|
||||
" # これでようやくオプティマイザーの値も同一になる\n",
|
||||
" print(model.weights[0][0, 0, 0,:10])\n",
|
||||
" print(model.optimizer.weights[1][0, 0, 0,:10])\n",
|
||||
"load_tf_w_zero_grad()"
|
||||
" print(model.weights[0][0, 0, 0, :10])\n",
|
||||
" print(model.optimizer.weights[1][0, 0, 0, :10])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"load_tf_w_zero_grad()\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -234,14 +257,14 @@
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"a = np.array([10,20,30,0])\n",
|
||||
"a = np.array([10, 20, 30, 0])\n",
|
||||
"\n",
|
||||
"np.any(a == 0)"
|
||||
"np.any(a == 0)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 29,
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@ -250,7 +273,7 @@
|
||||
"4"
|
||||
]
|
||||
},
|
||||
"execution_count": 29,
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user