improve training speed and add speed constrain
This commit is contained in:
@@ -72,37 +72,37 @@ class Server:
|
||||
self.commit(msg)
|
||||
self.send()
|
||||
|
||||
def receive(self) -> None:
|
||||
"""
|
||||
Receive the next message from the TCP/IP socket and updates world
|
||||
"""
|
||||
def receive(self):
|
||||
|
||||
# Receive message length information
|
||||
if (
|
||||
self.__socket.recv_into(
|
||||
self.__rcv_buffer, nbytes=4, flags=socket.MSG_WAITALL
|
||||
while True:
|
||||
|
||||
if (
|
||||
self.__socket.recv_into(
|
||||
self.__rcv_buffer, nbytes=4, flags=socket.MSG_WAITALL
|
||||
) != 4
|
||||
):
|
||||
raise ConnectionResetError
|
||||
|
||||
msg_size = int.from_bytes(self.__rcv_buffer[:4], byteorder="big", signed=False)
|
||||
|
||||
if msg_size > self.__rcv_buffer_size:
|
||||
self.__rcv_buffer_size = msg_size
|
||||
self.__rcv_buffer = bytearray(self.__rcv_buffer_size)
|
||||
|
||||
if (
|
||||
self.__socket.recv_into(
|
||||
self.__rcv_buffer, nbytes=msg_size, flags=socket.MSG_WAITALL
|
||||
) != msg_size
|
||||
):
|
||||
raise ConnectionResetError
|
||||
|
||||
self.world_parser.parse(
|
||||
message=self.__rcv_buffer[:msg_size].decode()
|
||||
)
|
||||
!= 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
|
||||
):
|
||||
raise ConnectionResetError
|
||||
|
||||
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
|
||||
|
||||
@@ -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(),
|
||||
stdout=subprocess.DEVNULL, stderr=subprocess.STDOUT, start_new_session=True)
|
||||
subprocess.Popen(
|
||||
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):
|
||||
@@ -60,4 +69,4 @@ class Server():
|
||||
def kill(self):
|
||||
for p in self.rcss_processes:
|
||||
p.kill()
|
||||
print(f"Killed {self.n_servers} rcssservermj processes starting at {self.first_server_p}")
|
||||
print(f"Killed {self.n_servers} rcssservermj processes starting at {self.first_server_p}")
|
||||
|
||||
@@ -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
|
||||
|
||||
|
||||
@@ -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(
|
||||
@@ -492,9 +515,11 @@ class Train(Train_Base):
|
||||
def train(self, args):
|
||||
|
||||
#--------------------------------------- Learning parameters
|
||||
n_envs = 8 # Reduced from 8 to decrease CPU/network pressure during init
|
||||
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"})
|
||||
|
||||
Reference in New Issue
Block a user