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andreskull committed Jul 17, 2019
1 parent cc9a0ed commit 242f5e8
Showing 1 changed file with 7 additions and 17 deletions.
24 changes: 7 additions & 17 deletions lib/RLTrader.py
Original file line number Diff line number Diff line change
Expand Up @@ -112,26 +112,20 @@ def get_model_params(self):
'cliprange': params['cliprange'],
'noptepochs': int(params['noptepochs']),
'lam': params['lam'],
'vf_coef': params['vf_coef'],
'max_grad_norm': params['max_grad_norm']
}

def optimize_agent_params(self, trial):
if self.Model != PPO2:
return {'learning_rate': trial.suggest_loguniform('learning_rate', 1e-5, 1.)}

return {
# PPO2 hyperparameter ranges
# https://medium.com/aureliantactics/ppo-hyperparameters-and-ranges-6fc2d29bccbe
'n_steps': int(trial.suggest_loguniform('n_steps', 32, 5000)),
'gamma': trial.suggest_uniform('gamma', 0.8, 0.9997),
'learning_rate': trial.suggest_loguniform('learning_rate', 5e-6, 0.003),
'ent_coef': trial.suggest_uniform('ent_coef', 0, 1e-2),
'cliprange': trial.suggest_uniform('cliprange', 0.1, 0.3),
'noptepochs': int(trial.suggest_uniform('noptepochs', 3, 30)),
'lam': trial.suggest_uniform('lam', 0.9, 1.),
'vf_coef': trial.suggest_uniform('vf_coef', 0.5, 1.),
'max_grad_norm': trial.suggest_uniform('max_grad_norm', 0.4, 0.6),
'n_steps': int(trial.suggest_loguniform('n_steps', 16, 2048)),
'gamma': trial.suggest_loguniform('gamma', 0.9, 0.9999),
'learning_rate': trial.suggest_loguniform('learning_rate', 1e-5, 1.),
'ent_coef': trial.suggest_loguniform('ent_coef', 1e-8, 1e-1),
'cliprange': trial.suggest_uniform('cliprange', 0.1, 0.4),
'noptepochs': int(trial.suggest_loguniform('noptepochs', 1, 48)),
'lam': trial.suggest_uniform('lam', 0.8, 1.)
}

def optimize_params(self, trial, n_prune_evals_per_trial: int = 2, n_tests_per_eval: int = 1):
Expand Down Expand Up @@ -295,11 +289,7 @@ def test(self, model_epoch: int = 0, render_env: bool = True, render_report: boo

if save_report:
reports_path = path.join('data', 'reports', f'{self.study_name}__{model_epoch}.html')
# try:
qs.reports.html(returns.Balance, file=reports_path)
# except Exception as err:
# print(err)
# pass

self.logger.info(
f'Finished testing model ({self.study_name}__{model_epoch}): ${"{:.2f}".format(np.sum(rewards))}')

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