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Merge pull request #7860 from freqtrade/update-freqai-tf-handling

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Ensure base tf to be include_timeframes
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Robert Caulk 2022-12-11 12:50:07 +01:00 committed by GitHub
commit 0f75ec9c97
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6 changed files with 21 additions and 15 deletions
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4
config_examples/config_freqai.example.json
View File

@ -79,9 +79,7 @@
"test_size": 0.33,
"random_state": 1
},
"model_training_parameters": {
"n_estimators": 1000
}
"model_training_parameters": {}
},
"bot_name": "",
"force_entry_enable": true,

5
docs/freqai-configuration.md
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@ -26,10 +26,7 @@ FreqAI is configured through the typical [Freqtrade config file](configuration.m
},
"data_split_parameters" : {
"test_size": 0.25
},
"model_training_parameters" : {
"n_estimators": 100
},
}
}
```

7
freqtrade/configuration/config_validation.py
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@ -355,6 +355,13 @@ def _validate_freqai_include_timeframes(conf: Dict[str, Any]) -> None:
f"Main timeframe of {main_tf} must be smaller or equal to FreqAI "
f"`include_timeframes`.Offending include-timeframes: {', '.join(offending_lines)}")
# Ensure that the base timeframe is included in the include_timeframes list
if main_tf not in freqai_include_timeframes:
feature_parameters = conf.get('freqai', {}).get('feature_parameters', {})
include_timeframes = [main_tf] + freqai_include_timeframes
conf.get('freqai', {}).get('feature_parameters', {}) \
.update({**feature_parameters, 'include_timeframes': include_timeframes})
def _validate_freqai_backtest(conf: Dict[str, Any]) -> None:
if conf.get('runmode', RunMode.OTHER) == RunMode.BACKTEST:

5
freqtrade/constants.py
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@ -608,9 +608,8 @@ CONF_SCHEMA = {
"backtest_period_days",
"identifier",
"feature_parameters",
"data_split_parameters",
"model_training_parameters"
]
"data_split_parameters"
]
},
},
}

2
freqtrade/freqai/prediction_models/ReinforcementLearner.py
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@ -61,7 +61,7 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
model = self.MODELCLASS(self.policy_type, self.train_env, policy_kwargs=policy_kwargs,
tensorboard_log=Path(
dk.full_path / "tensorboard" / dk.pair.split('/')[0]),
**self.freqai_info['model_training_parameters']
**self.freqai_info.get('model_training_parameters', {})
)
else:
logger.info('Continual training activated - starting training from previously '

7
tests/test_configuration.py
View File

@ -1046,8 +1046,13 @@ def test__validate_freqai_include_timeframes(default_conf, caplog) -> None:
# Validation pass
conf.update({'timeframe': '1m'})
validate_config_consistency(conf)
conf.update({'analyze_per_epoch': True})
# Ensure base timeframe is in include_timeframes
conf['freqai']['feature_parameters']['include_timeframes'] = ["5m", "15m"]
validate_config_consistency(conf)
assert conf['freqai']['feature_parameters']['include_timeframes'] == ["1m", "5m", "15m"]
conf.update({'analyze_per_epoch': True})
with pytest.raises(OperationalException,
match=r"Using analyze-per-epoch .* not supported with a FreqAI strategy."):
validate_config_consistency(conf)