__init__() got an unexpected keyword argument 'EPS'

[formidiable]

No description provided.

[MehranTaghian]

Hello Thank you for reaching out I have changed the code a little bit. So the main file to run would be main.py instead of main.ipynb. Also, try to set the transaction cost to zero. It hasn't been fully tested

…

On Sat, Dec 25, 2021 at 5:29 PM formidiable ***@***.***> wrote: ------------------------------ TypeError Traceback (most recent call last) in 1 hidden_size = 64 2 ----> 3 gru_agent = gru(data_loader, dataTrain_sequential, dataTest_sequential, DATASET_NAME, transaction_cost, hidden_size, 4 BATCH_SIZE=BATCH_SIZE, GAMMA=GAMMA, EPS=EPS, 5 ReplayMemorySize=ReplayMemorySize, TypeError: *init*() got an unexpected keyword argument 'EPS' I get this error and same for some other arguments. What should i do? And I get -%100 rate of return when i set transaction cost = 0.005, I try to set the EPS but i couldn't succeed yet. Do you have any advise? — Reply to this email directly, view it on GitHub <#1>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AGGUZYVCP5LXX5RFTJZRGJDUSZOVRANCNFSM5KYKAGDA> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>. You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[dekacypher]

Remove EPS and n_actions from the DeepRL constructor, because they don't match the parameteres of the constructor of DeepRL, and also set data_train to the correct type it should be DataAutoPatternExtractionAgent and not DataForPatternBasedAgent. And likewise for the test() method, the parametres used doesn't match the constructor of the test()-method.

Like this:

`
deepRLAgent = DeepRL(data_loader, dataTrain_autoPatternExtractionAgent_windowed, dataTest_autoPatternExtractionAgent_windowed, DATASET_NAME,
state_mode, window_size, transaction_cost,
BATCH_SIZE=BATCH_SIZE, GAMMA=GAMMA, ReplayMemorySize=ReplayMemorySize,
TARGET_UPDATE=TARGET_UPDATE, n_step=n_step)
#EPS=EPS,
#n_actions=n_actions,
deepRLAgent.train(n_episodes)
file_name = None

ev_deepRLAgent = deepRLAgent.test(
initial_investment=initial_investment, test_type='train')
#file_name=file_name, action_name=dataTrain_autoPatternExtractionAgent_windowed.action_name,
deepRLAgent_portfolio_train = ev_deepRLAgent.get_daily_portfolio_value()
ev_deepRLAgent = deepRLAgent.test(
initial_investment=initial_investment, test_type='test')
#file_name=file_name, action_name=dataTrain_autoPatternExtractionAgent_windowed.action_name,
deepRLAgent_portfolio_test = ev_deepRLAgent.get_daily_portfolio_value()

model_kind = 'DQN-pattern'

add_train_portfo(model_kind, deepRLAgent_portfolio_train)
add_test_portfo(model_kind, deepRLAgent_portfolio_test)
``