add deco package

cli.py

@@ -1,4 +1,5 @@
 import numpy as np
+from deco import concurrent
 
 from lib.RLTrader import RLTrader
 from lib.cli.RLTraderCLI import RLTraderCLI
@@ -8,16 +9,26 @@
 trader_cli = RLTraderCLI()
 args = trader_cli.get_args()
 
+
+@concurrent(processes=args.proc_number)
+def run_concurrent_optimize(trader: RLTrader, args):
+    trader.optimize(args.trials, args.trials, args.parallel_jobs)
+
+
 if __name__ == '__main__':
     logger = init_logger(__name__, show_debug=args.debug)
     trader = RLTrader(**vars(args), logger=logger)
 
     if args.command == 'optimize':
-        trader.optimize(n_trials=args.trials, n_parallel_jobs=args.parallel_jobs)
+        run_concurrent_optimize(trader, args)
     elif args.command == 'train':
         trader.train(n_epochs=args.epochs)
     elif args.command == 'test':
         trader.test(model_epoch=args.model_epoch, should_render=args.no_render)
     elif args.command == 'opt-train-test':
-        trader.optimize(args.trials, args.parallel_jobs)
-        trader.train(n_epochs=args.train_epochs, test_trained_model=args.no_test, render_trained_model=args.no_render)
+        run_concurrent_optimize(trader, args)
+        trader.train(
+            n_epochs=args.train_epochs,
+            test_trained_model=args.no_test,
+            render_trained_model=args.no_render
+        )

lib/RLTrader.py

@@ -4,6 +4,8 @@
 
 from os import path
 from typing import Dict
+
+from deco import concurrent
 from stable_baselines.common.base_class import BaseRLModel
 from stable_baselines.common.policies import BasePolicy, MlpPolicy
 from stable_baselines.common.vec_env import DummyVecEnv, SubprocVecEnv
@@ -160,6 +162,7 @@ def optimize_params(self, trial, n_prune_evals_per_trial: int = 2, n_tests_per_e
 
         return -1 * last_reward
 
+    @concurrent
     def optimize(self, n_trials: int = 100, n_parallel_jobs: int = 1, *optimize_params):
         try:
             self.optuna_study.optimize(

lib/cli/RLTraderCLI.py

@@ -1,6 +1,6 @@
 import argparse
 import os
-
+import multiprocessing
 
 class RLTraderCLI:
     def __init__(self):
@@ -32,10 +32,12 @@ def __init__(self):
         opt_train_test_parser.add_argument('--train-epochs', type=int, default=10, help='Train for how many epochs')
         opt_train_test_parser.add_argument('--no-render', action='store_false', help='Should render the model')
         opt_train_test_parser.add_argument('--no-test', action='store_false', help='Should test the model')
+        opt_train_test_parser.add_argument('--proc-number', type=int, default=multiprocessing.cpu_count(), help='How many processes to spawn')
 
         optimize_parser = subparsers.add_parser('optimize', description='Optimize model parameters')
         optimize_parser.add_argument('--trials', type=int, default=1, help='Number of trials')
         optimize_parser.add_argument('--parallel-jobs', type=int, default=1, help='How many jobs in parallel')
+        optimize_parser.add_argument('--proc-number', type=int, default=multiprocessing.cpu_count(), help='How many processes to spawn')
 
         optimize_parser.add_argument('--verbose-model', type=int, default=1, help='Verbose model', dest='model_verbose')
 

requirements.no-gpu.txt

@@ -9,4 +9,5 @@ ta
 statsmodels==0.10.0rc2
 empyrical
 tensorflow
-ccxt
+ccxt
+deco

requirements.tests.txt

@@ -1,2 +1,3 @@
 -r requirements.no-gpu.txt
-pytest
+pytest
+deco

requirements.txt

@@ -10,4 +10,5 @@ statsmodels==0.10.0rc2
 empyrical
 tensorflow-gpu
 ccxt
-psycopg2
+psycopg2
+deco