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add pytorch mlp models to test_start_backtesting

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This commit is contained in:
Yinon Polak 2023-03-21 16:20:35 +02:00
parent 83a7d888bc
commit 02bccd0097
2 changed files with 27 additions and 27 deletions
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16
tests/freqai/conftest.py
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@ -83,6 +83,22 @@ def make_rl_config(conf):
return conf return conf
def mock_pytorch_mlp_model_training_parameters(conf):
return {
"learning_rate": 3e-4,
"trainer_kwargs": {
"max_iters": 1,
"batch_size": 64,
"max_n_eval_batches": 1,
},
"model_kwargs": {
"hidden_dim": 32,
"dropout_percent": 0.2,
"n_layer": 1,
}
}
def get_patched_data_kitchen(mocker, freqaiconf): def get_patched_data_kitchen(mocker, freqaiconf):
dk = FreqaiDataKitchen(freqaiconf) dk = FreqaiDataKitchen(freqaiconf)
return dk return dk

38
tests/freqai/test_freqai_interface.py
View File

@ -89,19 +89,8 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
if 'PyTorchMLPRegressor' in model: if 'PyTorchMLPRegressor' in model:
model_save_ext = 'zip' model_save_ext = 'zip'
freqai_conf['freqai']['model_training_parameters'].update({ pytorch_mlp_mtp = mock_pytorch_mlp_model_training_parameters()
"learning_rate": 3e-4, freqai_conf['freqai']['model_training_parameters'].update(pytorch_mlp_mtp)
"trainer_kwargs": {
"max_iters": 1,
"batch_size": 64,
"max_n_eval_batches": 1,
},
"model_kwargs": {
"hidden_dim": 32,
"dropout_percent": 0.2,
"n_layer": 1,
}
})
strategy = get_patched_freqai_strategy(mocker, freqai_conf) strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf) exchange = get_patched_exchange(mocker, freqai_conf)
@ -214,19 +203,8 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
strategy, freqai.dk, data_load_timerange) strategy, freqai.dk, data_load_timerange)
if 'PyTorchMLPClassifier': if 'PyTorchMLPClassifier':
freqai_conf['freqai']['model_training_parameters'].update({ pytorch_mlp_mtp = mock_pytorch_mlp_model_training_parameters()
"learning_rate": 3e-4, freqai_conf['freqai']['model_training_parameters'].update(pytorch_mlp_mtp)
"trainer_kwargs": {
"max_iters": 1,
"batch_size": 64,
"max_n_eval_batches": 1,
},
"model_kwargs": {
"hidden_dim": 32,
"dropout_percent": 0.2,
"n_layer": 1,
}
})
if freqai.dd.model_type == 'joblib': if freqai.dd.model_type == 'joblib':
model_file_extension = ".joblib" model_file_extension = ".joblib"
@ -251,10 +229,12 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
("LightGBMRegressor", 2, "freqai_test_strat"), ("LightGBMRegressor", 2, "freqai_test_strat"),
("XGBoostRegressor", 2, "freqai_test_strat"), ("XGBoostRegressor", 2, "freqai_test_strat"),
("CatboostRegressor", 2, "freqai_test_strat"), ("CatboostRegressor", 2, "freqai_test_strat"),
("PyTorchMLPRegressor", 2, "freqai_test_strat"),
("ReinforcementLearner", 3, "freqai_rl_test_strat"), ("ReinforcementLearner", 3, "freqai_rl_test_strat"),
("XGBoostClassifier", 2, "freqai_test_classifier"), ("XGBoostClassifier", 2, "freqai_test_classifier"),
("LightGBMClassifier", 2, "freqai_test_classifier"), ("LightGBMClassifier", 2, "freqai_test_classifier"),
("CatboostClassifier", 2, "freqai_test_classifier") ("CatboostClassifier", 2, "freqai_test_classifier"),
("PyTorchMLPClassifier", 2, "freqai_test_classifier")
], ],
) )
def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog): def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog):
@ -275,6 +255,10 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog)
if 'test_4ac' in model: if 'test_4ac' in model:
freqai_conf["freqaimodel_path"] = str(Path(__file__).parents[1] / "freqai" / "test_models") freqai_conf["freqaimodel_path"] = str(Path(__file__).parents[1] / "freqai" / "test_models")
if 'PyTorchMLP' in model:
pytorch_mlp_mtp = mock_pytorch_mlp_model_training_parameters()
freqai_conf['freqai']['model_training_parameters'].update(pytorch_mlp_mtp)
freqai_conf.get("freqai", {}).get("feature_parameters", {}).update( freqai_conf.get("freqai", {}).get("feature_parameters", {}).update(
{"indicator_periods_candles": [2]}) {"indicator_periods_candles": [2]})