adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge branch 'develop' into backtest_fitlivepredictions

Browse Source
This commit is contained in:
Wagner Costa
2022-11-29 09:39:15 -03:00
parent d09157efb8 066d040fd3
commit df979ece33
63 changed files with 3805 additions and 1804 deletions
Download Patch File Download Diff File Expand all files Collapse all files

33
freqtrade/freqai/data_drawer.py
View File

@@ -1,4 +1,5 @@
import collections
import importlib
import logging
import re
import shutil
@@ -99,6 +100,7 @@ class FreqaiDataDrawer:
self.empty_pair_dict: pair_info = {
"model_filename": "", "trained_timestamp": 0,
"data_path": "", "extras": {}}
self.model_type = self.freqai_info.get('model_save_type', 'joblib')
def update_metric_tracker(self, metric: str, value: float, pair: str) -> None:
"""
@@ -497,10 +499,12 @@ class FreqaiDataDrawer:
save_path = Path(dk.data_path)
# Save the trained model
if not dk.keras:
if self.model_type == 'joblib':
dump(model, save_path / f"{dk.model_filename}_model.joblib")
else:
elif self.model_type == 'keras':
model.save(save_path / f"{dk.model_filename}_model.h5")
elif 'stable_baselines' in self.model_type:
model.save(save_path / f"{dk.model_filename}_model.zip")
if dk.svm_model is not None:
dump(dk.svm_model, save_path / f"{dk.model_filename}_svm_model.joblib")
@@ -527,11 +531,10 @@ class FreqaiDataDrawer:
dk.pca, open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "wb")
)
# if self.live:
# store as much in ram as possible to increase performance
self.model_dictionary[coin] = model
self.pair_dict[coin]["model_filename"] = dk.model_filename
self.pair_dict[coin]["data_path"] = str(dk.data_path)
if coin not in self.meta_data_dictionary:
self.meta_data_dictionary[coin] = {}
self.meta_data_dictionary[coin]["train_df"] = dk.data_dictionary["train_features"]
@@ -563,14 +566,6 @@ class FreqaiDataDrawer:
if dk.live:
dk.model_filename = self.pair_dict[coin]["model_filename"]
dk.data_path = Path(self.pair_dict[coin]["data_path"])
if self.freqai_info.get("follow_mode", False):
# follower can be on a different system which is rsynced from the leader:
dk.data_path = Path(
self.config["user_data_dir"]
/ "models"
/ dk.data_path.parts[-2]
/ dk.data_path.parts[-1]
)
if coin in self.meta_data_dictionary:
dk.data = self.meta_data_dictionary[coin]["meta_data"]
@@ -589,12 +584,16 @@ class FreqaiDataDrawer:
# try to access model in memory instead of loading object from disk to save time
if dk.live and coin in self.model_dictionary:
model = self.model_dictionary[coin]
elif not dk.keras:
elif self.model_type == 'joblib':
model = load(dk.data_path / f"{dk.model_filename}_model.joblib")
else:
elif self.model_type == 'keras':
from tensorflow import keras
model = keras.models.load_model(dk.data_path / f"{dk.model_filename}_model.h5")
elif self.model_type == 'stable_baselines':
mod = importlib.import_module(
'stable_baselines3', self.freqai_info['rl_config']['model_type'])
MODELCLASS = getattr(mod, self.freqai_info['rl_config']['model_type'])
model = MODELCLASS.load(dk.data_path / f"{dk.model_filename}_model")
if Path(dk.data_path / f"{dk.model_filename}_svm_model.joblib").is_file():
dk.svm_model = load(dk.data_path / f"{dk.model_filename}_svm_model.joblib")
@@ -604,6 +603,10 @@ class FreqaiDataDrawer:
f"Unable to load model, ensure model exists at " f"{dk.data_path} "
)
# load it into ram if it was loaded from disk
if coin not in self.model_dictionary:
self.model_dictionary[coin] = model
if self.config["freqai"]["feature_parameters"]["principal_component_analysis"]:
dk.pca = cloudpickle.load(
open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "rb")