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Merge pull request #8297 from Yinon-Polak/feat/add-pytorch-model-support

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Feat/add pytorch model support
This commit is contained in:
Robert Caulk
2023-04-11 15:40:12 +02:00
committed by GitHub
parent 476ed938f5 5404905d28
commit 4ab047dfa7
34 changed files with 1248 additions and 86 deletions
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17
tests/freqai/conftest.py
View File

@@ -1,5 +1,6 @@
from copy import deepcopy
from pathlib import Path
from typing import Any, Dict
from unittest.mock import MagicMock
import pytest
@@ -85,6 +86,22 @@ def make_rl_config(conf):
return conf
def mock_pytorch_mlp_model_training_parameters() -> Dict[str, Any]:
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):
dk = FreqaiDataKitchen(freqaiconf)
return dk

52
tests/freqai/test_freqai_interface.py
View File

@@ -15,7 +15,8 @@ from freqtrade.optimize.backtesting import Backtesting
from freqtrade.persistence import Trade
from freqtrade.plugins.pairlistmanager import PairListManager
from tests.conftest import EXMS, create_mock_trades, get_patched_exchange, log_has_re
from tests.freqai.conftest import get_patched_freqai_strategy, make_rl_config
from tests.freqai.conftest import (get_patched_freqai_strategy, make_rl_config,
mock_pytorch_mlp_model_training_parameters)
def is_py11() -> bool:
@@ -34,13 +35,14 @@ def is_mac() -> bool:
def can_run_model(model: str) -> None:
if (is_arm() or is_py11()) and "Catboost" in model:
pytest.skip("CatBoost is not supported on ARM")
pytest.skip("CatBoost is not supported on ARM.")
if is_mac() and not is_arm() and 'Reinforcement' in model:
pytest.skip("Reinforcement learning module not available on intel based Mac OS")
is_pytorch_model = 'Reinforcement' in model or 'PyTorch' in model
if is_pytorch_model and is_mac() and not is_arm():
pytest.skip("Reinforcement learning / PyTorch module not available on intel based Mac OS.")
if is_py11() and 'Reinforcement' in model:
pytest.skip("Reinforcement learning currently not available on python 3.11.")
if is_pytorch_model and is_py11():
pytest.skip("Reinforcement learning / PyTorch currently not available on python 3.11.")
@pytest.mark.parametrize('model, pca, dbscan, float32, can_short, shuffle, buffer', [
@@ -48,11 +50,12 @@ def can_run_model(model: str) -> None:
('XGBoostRegressor', False, True, False, True, False, 10),
('XGBoostRFRegressor', False, False, False, True, False, 0),
('CatboostRegressor', False, False, False, True, True, 0),
('PyTorchMLPRegressor', False, False, False, True, False, 0),
('ReinforcementLearner', False, True, False, True, False, 0),
('ReinforcementLearner_multiproc', False, False, False, True, False, 0),
('ReinforcementLearner_test_3ac', False, False, False, False, False, 0),
('ReinforcementLearner_test_3ac', False, False, False, True, False, 0),
('ReinforcementLearner_test_4ac', False, False, False, True, False, 0)
('ReinforcementLearner_test_4ac', False, False, False, True, False, 0),
])
def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
dbscan, float32, can_short, shuffle, buffer):
@@ -79,6 +82,11 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
freqai_conf["freqaimodel_path"] = str(Path(__file__).parents[1] / "freqai" / "test_models")
freqai_conf["freqai"]["rl_config"]["drop_ohlc_from_features"] = True
if 'PyTorchMLPRegressor' in model:
model_save_ext = 'zip'
pytorch_mlp_mtp = mock_pytorch_mlp_model_training_parameters()
freqai_conf['freqai']['model_training_parameters'].update(pytorch_mlp_mtp)
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
@@ -123,8 +131,7 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
('CatboostClassifierMultiTarget', "freqai_test_multimodel_classifier_strat")
])
def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, strat):
if (is_arm() or is_py11()) and 'Catboost' in model:
pytest.skip("CatBoost is not supported on ARM")
can_run_model(model)
freqai_conf.update({"timerange": "20180110-20180130"})
freqai_conf.update({"strategy": strat})
@@ -164,10 +171,10 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, s
'CatboostClassifier',
'XGBoostClassifier',
'XGBoostRFClassifier',
'PyTorchMLPClassifier',
])
def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
if (is_arm() or is_py11()) and model == 'CatboostClassifier':
pytest.skip("CatBoost is not supported on ARM")
can_run_model(model)
freqai_conf.update({"freqaimodel": model})
freqai_conf.update({"strategy": "freqai_test_classifier"})
@@ -193,7 +200,20 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
freqai.extract_data_and_train_model(new_timerange, "ADA/BTC",
strategy, freqai.dk, data_load_timerange)
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_model.joblib").exists()
if 'PyTorchMLPClassifier':
pytorch_mlp_mtp = mock_pytorch_mlp_model_training_parameters()
freqai_conf['freqai']['model_training_parameters'].update(pytorch_mlp_mtp)
if freqai.dd.model_type == 'joblib':
model_file_extension = ".joblib"
elif freqai.dd.model_type == "pytorch":
model_file_extension = ".zip"
else:
raise Exception(f"Unsupported model type: {freqai.dd.model_type},"
f" can't assign model_file_extension")
assert Path(freqai.dk.data_path /
f"{freqai.dk.model_filename}_model{model_file_extension}").exists()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_metadata.json").exists()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_trained_df.pkl").exists()
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}_svm_model.joblib").exists()
@@ -207,10 +227,12 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
("LightGBMRegressor", 2, "freqai_test_strat"),
("XGBoostRegressor", 2, "freqai_test_strat"),
("CatboostRegressor", 2, "freqai_test_strat"),
("PyTorchMLPRegressor", 2, "freqai_test_strat"),
("ReinforcementLearner", 3, "freqai_rl_test_strat"),
("XGBoostClassifier", 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):
@@ -231,6 +253,10 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog)
if 'test_4ac' in model:
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(
{"indicator_periods_candles": [2]})

2
tests/strategy/strats/freqai_test_classifier.py
View File

@@ -82,7 +82,7 @@ class freqai_test_classifier(IStrategy):
return dataframe
def set_freqai_targets(self, dataframe: DataFrame, metadata: Dict, **kwargs):
self.freqai.class_names = ["down", "up"]
dataframe['&s-up_or_down'] = np.where(dataframe["close"].shift(-100) >
dataframe["close"], 'up', 'down')