def main(args):
env = Market(args.codes)
algorithm = Algorithm(
tf.Session(config=config),
env,
env.trader.action_space,
env.data_dim,
**{
"mode":
args.mode,
# "mode": "test",
"episodes":
args.episode,
"save_path":
os.path.join(CHECKPOINTS_DIR, "RL", "DuelingDQN", "model"),
"summary_path":
os.path.join(CHECKPOINTS_DIR, "RL", "DuelingDQN", "summary"),
"enable_saver":
True,
"enable_summary_writer":
True
})
algorithm.run()
algorithm.eval_v2()
algorithm.plot()
def main(args):
env = Market(args.codes, **{"use_sequence": True})
algorithm = Algorithm(
tf.Session(config=config),
env,
env.seq_length,
env.data_dim,
env.code_count,
**{
"mode":
args.mode,
# "mode": "test",
"save_path":
os.path.join(CHECKPOINTS_DIR, "SL", "TreNet", "model"),
"summary_path":
os.path.join(CHECKPOINTS_DIR, "SL", "TreNet", "summary"),
"hidden_size":
5,
"enable_saver":
True,
"enable_summary_writer":
True
})
algorithm.run()
algorithm.eval_and_plot()
def main(args):
env = Market(args.codes)
algorithm = Algorithm(env, env.trader.action_space, env.data_dim, **{
# "mode": args.mode,
# "mode": "test",
"episodes": 10,
})
algorithm.run()
def main(args):
env = Market(args.codes, **{"use_sequence": True})
algorithm = Algorithm(tf.Session(config=config), env, env.seq_length, env.data_dim, env.code_count, **{
"mode": args.mode,
# "mode": "test",
"log_level": args.log_level,
"save_path": os.path.join(CHECKPOINTS_DIR, "SL", "DualAttnRNN", "model"),
"enable_saver": True,
})
algorithm.run()
algorithm.eval_and_plot()
def main(args):
env = Market(args.codes)
algorithm = Algorithm(
tf.Session(config=config),
env,
env.trader.action_space,
env.data_dim,
**{
"mode": args.mode,
# "mode": "test",
"episodes": 200,
"log_level": args.log_level,
"save_path": os.path.join(CHECKPOINTS_DIR, "RL", "DDPG", "model"),
"enable_saver": True,
})
algorithm.run()
algorithm.eval_v1()
algorithm.plot()
