improve training speed and add speed constrain

communication/server.py

@@ -72,37 +72,37 @@ class Server:
         self.commit(msg)
         self.send()
 
-    def receive(self) -> None:
+    def receive(self):
-        """
+
-        Receive the next message from the TCP/IP socket and updates world
+        while True:
-        """
 
-        # Receive message length information
             if (
                     self.__socket.recv_into(
                         self.__rcv_buffer, nbytes=4, flags=socket.MSG_WAITALL
-            )
+                    ) != 4
-            != 4
             ):
                 raise ConnectionResetError
 
             msg_size = int.from_bytes(self.__rcv_buffer[:4], byteorder="big", signed=False)
 
-        # Ensure receive buffer is large enough to hold the message
             if msg_size > self.__rcv_buffer_size:
                 self.__rcv_buffer_size = msg_size
                 self.__rcv_buffer = bytearray(self.__rcv_buffer_size)
 
-        # Receive message with the specified length
             if (
                     self.__socket.recv_into(
                         self.__rcv_buffer, nbytes=msg_size, flags=socket.MSG_WAITALL
-            )
+                    ) != msg_size
-            != msg_size
             ):
                 raise ConnectionResetError
 
-        self.world_parser.parse(message=self.__rcv_buffer[:msg_size].decode())
+            self.world_parser.parse(
+                message=self.__rcv_buffer[:msg_size].decode()
+            )
+
+            # 如果socket没有更多数据就退出
+            if len(select([self.__socket], [], [], 0.0)[0]) == 0:
+                break
 
     def commit_beam(self, pos2d: list, rotation: float) -> None:
         assert len(pos2d) == 2

scripts/commons/Server.py

@@ -18,9 +18,18 @@ class Server():
         # makes it easier to kill test servers without affecting train servers
         cmd = "rcssservermj"
         for i in range(n_servers):
+            port = first_server_p + i
+            mport = first_monitor_p + i
+
+            server_cmd = f"{cmd} --aport {port} --mport {mport} --no-render  --no-realtime"
+
             self.rcss_processes.append(
-                subprocess.Popen((f"{cmd} --aport {first_server_p+i} --mport {first_monitor_p+i}").split(),
+                subprocess.Popen(
-                stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT, start_new_session=True)
+                    server_cmd.split(),
+                    stdout=subprocess.DEVNULL,
+                    stderr=subprocess.STDOUT,
+                    start_new_session=True
+                )
             )
 
     def check_running_servers(self, psutil, first_server_p, first_monitor_p, n_servers):

scripts/commons/Train_Base.py

@@ -46,7 +46,7 @@ class Train_Base():
     @staticmethod
     def prompt_user_for_model(self):
 
-        gyms_logs_path = "./mujococodebase/scripts/gyms/logs/"
+        gyms_logs_path = "./scripts/gyms/logs/"
         folders = [f for f in listdir(gyms_logs_path) if isdir(join(gyms_logs_path, f))]
         folders.sort(key=lambda f: os.path.getmtime(join(gyms_logs_path, f)), reverse=True) # sort by modification date
 

scripts/gyms/Walk.py

@@ -1,6 +1,7 @@
 import os
 import numpy as np
 import math
+import time
 from time import sleep 
 from random import random
 from random import uniform
@@ -55,6 +56,17 @@ class WalkEnv(gym.Env):
         self.auto_calibrate_train_sim_flip = True
         self.nominal_calibrated_once = False
         self.flip_calibrated_once = False
+        self._target_hz = 0.0
+        self._target_dt = 0.0
+        self._last_sync_time = None
+        target_hz_env = 24
+        if target_hz_env:
+            try:
+                self._target_hz = float(target_hz_env)
+            except ValueError:
+                self._target_hz = 0.0
+        if self._target_hz > 0.0:
+            self._target_dt = 1.0 / self._target_hz
 
 
         # State space
@@ -141,7 +153,7 @@ class WalkEnv(gym.Env):
         self.previous_action = np.zeros(len(self.Player.robot.ROBOT_MOTORS))
         self.previous_pos = np.array([0.0, 0.0])  # Track previous position
         self.Player.server.connect()
-        sleep(2.0)  # Longer wait for connection to establish completely
+        # sleep(2.0)  # Longer wait for connection to establish completely
         self.Player.server.send_immediate(
             f"(init {self.Player.robot.name} {self.Player.world.team_name} {self.Player.world.number})"
         )
@@ -260,6 +272,17 @@ class WalkEnv(gym.Env):
         self.Player.world.update()
         self.Player.robot.commit_motor_targets_pd()
         self.Player.server.send()
+        if self._target_dt > 0.0:
+            now = time.time()
+            if self._last_sync_time is None:
+                self._last_sync_time = now
+                return
+            elapsed = now - self._last_sync_time
+            remaining = self._target_dt - elapsed
+            if remaining > 0.0:
+                time.sleep(remaining)
+                now = time.time()
+            self._last_sync_time = now
 
     def debug_joint_status(self):
         robot = self.Player.robot
@@ -322,12 +345,12 @@ class WalkEnv(gym.Env):
 
         # 执行 Neutral 技能直到完成，给机器人足够时间在 beam 位置稳定站立
         finished_count = 0
-        for _ in range(20):
+        for _ in range(10):
             finished = self.Player.skills_manager.execute("Neutral")
             self.sync()
             if finished:
                 finished_count += 1
-                if finished_count >= 2:  # 假设需要连续2次完成才算成功
+                if finished_count >= 3:  # 假设需要连续3次完成才算成功
                     break
 
         # neutral_joint_positions = np.deg2rad(
@@ -493,8 +516,10 @@ class Train(Train_Base):
 
         #--------------------------------------- Learning parameters
         n_envs = 8 # Reduced from 8 to decrease CPU/network pressure during init
+        if n_envs < 1:
+            raise ValueError("GYM_CPU_N_ENVS must be >= 1")
         n_steps_per_env = 512  # RolloutBuffer is of size (n_steps_per_env * n_envs)
-        minibatch_size = 64    # should be a factor of (n_steps_per_env * n_envs)
+        minibatch_size = 128    # should be a factor of (n_steps_per_env * n_envs)
         total_steps = 30000000
         learning_rate = 3e-4
         folder_name = f'Walk_R{self.robot_type}'
@@ -509,6 +534,8 @@ class Train(Train_Base):
                 return WalkEnv( self.ip , self.server_p + i_env)
             return thunk
 
+        server_log_dir = os.path.join(model_path, "server_logs")
+        os.makedirs(server_log_dir, exist_ok=True)
         servers = Train_Server( self.server_p, self.monitor_p_1000, n_envs+1 ) #include 1 extra server for testing
         
         # Wait for servers to start
@@ -547,7 +574,7 @@ class Train(Train_Base):
                     gamma=0.99  # Discount factor
                 )
 
-            model_path = self.learn_model( model, total_steps, model_path, eval_env=eval_env, eval_freq=n_steps_per_env*20, save_freq=n_steps_per_env*20, backup_env_file=__file__ )
+            model_path = self.learn_model( model, total_steps, model_path, eval_env=eval_env, eval_freq=n_steps_per_env*10, save_freq=n_steps_per_env*10, backup_env_file=__file__ )
         except KeyboardInterrupt:
             sleep(1) # wait for child processes
             print("\nctrl+c pressed, aborting...\n")
@@ -562,7 +589,9 @@ class Train(Train_Base):
     def test(self, args):
 
         # Uses different server and monitor ports
-        server = Train_Server( self.server_p-1, self.monitor_p, 1 )
+        server_log_dir = os.path.join(args["folder_dir"], "server_logs")
+        os.makedirs(server_log_dir, exist_ok=True)
+        server = Train_Server( self.server_p-1, self.monitor_p, 1, log_dir=server_log_dir )
         env = WalkEnv( self.ip, self.server_p-1 )
         model = PPO.load( args["model_file"], env=env )
 
@@ -592,4 +621,4 @@ if __name__ == "__main__":
     )
     
     trainer = Train(script_args)
-    trainer.train({})
+    trainer.train({"model_file": "scripts/gyms/logs/Walk_R0_000/model_245760_steps.zip"})