From 123909cdace327fd42d98ed886768a2411309299 Mon Sep 17 00:00:00 2001 From: Robert Caulk Date: Thu, 26 Sep 2024 16:31:43 +0200 Subject: [PATCH 1/2] fix: Update BasePyTorchRegressor.py --- freqtrade/freqai/base_models/BasePyTorchRegressor.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/freqtrade/freqai/base_models/BasePyTorchRegressor.py b/freqtrade/freqai/base_models/BasePyTorchRegressor.py index 9b429db23..5f53e7d07 100644 --- a/freqtrade/freqai/base_models/BasePyTorchRegressor.py +++ b/freqtrade/freqai/base_models/BasePyTorchRegressor.py @@ -86,9 +86,6 @@ class BasePyTorchRegressor(BasePyTorchModel): dk.feature_pipeline = self.define_data_pipeline(threads=dk.thread_count) dk.label_pipeline = self.define_label_pipeline(threads=dk.thread_count) - dd["train_labels"], _, _ = dk.label_pipeline.fit_transform(dd["train_labels"]) - dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"]) - (dd["train_features"], dd["train_labels"], dd["train_weights"]) = ( dk.feature_pipeline.fit_transform( dd["train_features"], dd["train_labels"], dd["train_weights"] From d18d8cf0ea532fc95f838556f1fbd74f0aec30a2 Mon Sep 17 00:00:00 2001 From: Robert Caulk Date: Thu, 26 Sep 2024 17:54:14 +0200 Subject: [PATCH 2/2] freqai_info -> ft_params --- .../freqai/prediction_models/PyTorchTransformerRegressor.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py b/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py index 27b7de832..2d60d68cf 100644 --- a/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py +++ b/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py @@ -141,7 +141,7 @@ class PyTorchTransformerRegressor(BasePyTorchRegressor): pred_df = pd.DataFrame(yb.detach().numpy(), columns=dk.label_list) pred_df, _, _ = dk.label_pipeline.inverse_transform(pred_df) - if self.freqai_info.get("DI_threshold", 0) > 0: + if self.ft_params.get("DI_threshold", 0) > 0: dk.DI_values = dk.feature_pipeline["di"].di_values else: dk.DI_values = np.zeros(outliers.shape[0])