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avoid using ram for unnecessary train_df, fix some deprecation warnings

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This commit is contained in:
robcaulk
2023-06-10 12:07:03 +02:00
parent e246259792
commit 4cdd6bc6c3
3 changed files with 3 additions and 10 deletions
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3
freqtrade/freqai/base_models/FreqaiMultiOutputClassifier.py
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@@ -1,9 +1,8 @@
import numpy as np
from joblib import Parallel
from sklearn.base import is_classifier
from sklearn.multioutput import MultiOutputClassifier, _fit_estimator
from sklearn.utils.fixes import delayed
from sklearn.utils.multiclass import check_classification_targets
from sklearn.utils.parallel import Parallel, delayed
from sklearn.utils.validation import has_fit_parameter
from freqtrade.exceptions import OperationalException

3
freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
View File

@@ -1,6 +1,5 @@
from joblib import Parallel
from sklearn.multioutput import MultiOutputRegressor, _fit_estimator
from sklearn.utils.fixes import delayed
from sklearn.utils.parallel import Parallel, delayed
from sklearn.utils.validation import has_fit_parameter

7
freqtrade/freqai/data_drawer.py
View File

@@ -469,7 +469,7 @@ class FreqaiDataDrawer:
with (save_path / f"{dk.model_filename}_{LABEL_PIPELINE}.pkl").open("wb") as fp:
cloudpickle.dump(dk.label_pipeline, fp)
# save the train data to file so we can check preds for area of applicability later
# save the train data to file for post processing if desired
dk.data_dictionary["train_features"].to_pickle(
save_path / f"{dk.model_filename}_{TRAINDF}.pkl"
)
@@ -484,7 +484,6 @@ class FreqaiDataDrawer:
if coin not in self.meta_data_dictionary:
self.meta_data_dictionary[coin] = {}
self.meta_data_dictionary[coin][TRAINDF] = dk.data_dictionary["train_features"]
self.meta_data_dictionary[coin][METADATA] = dk.data
self.meta_data_dictionary[coin][FEATURE_PIPELINE] = dk.feature_pipeline
self.meta_data_dictionary[coin][LABEL_PIPELINE] = dk.label_pipeline
@@ -518,16 +517,12 @@ class FreqaiDataDrawer:
if coin in self.meta_data_dictionary:
dk.data = self.meta_data_dictionary[coin][METADATA]
dk.data_dictionary["train_features"] = self.meta_data_dictionary[coin][TRAINDF]
dk.feature_pipeline = self.meta_data_dictionary[coin][FEATURE_PIPELINE]
dk.label_pipeline = self.meta_data_dictionary[coin][LABEL_PIPELINE]
else:
with (dk.data_path / f"{dk.model_filename}_{METADATA}.json").open("r") as fp:
dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
dk.data_dictionary["train_features"] = pd.read_pickle(
dk.data_path / f"{dk.model_filename}_{TRAINDF}.pkl"
)
with (dk.data_path / f"{dk.model_filename}_{FEATURE_PIPELINE}.pkl").open("rb") as fp:
dk.feature_pipeline = cloudpickle.load(fp)
with (dk.data_path / f"{dk.model_filename}_{LABEL_PIPELINE}.pkl").open("rb") as fp: