change NORM_EACH_CHANNEL back to False

GestaltCogTeam · Oct 25, 2023 · cf598ac · cf598ac
1 parent 2ae8908
commit cf598ac
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diff --git a/scripts/data_preparation/Electricity/generate_training_data.py b/scripts/data_preparation/Electricity/generate_training_data.py
@@ -131,7 +131,7 @@ def generate_data(args: argparse.Namespace):
     # Thus, because larger values of the loss function will be obtained when the magnitudes of different variables differ significantly,
     # the model will be trained to focus on the variable with the largest magnitude. Then, the loss is more likely to be reduced.
     # If downstream tasks have other requirements, you can set norm_each_channel to according to your needs.
-    NORM_EACH_CHANNEL = True   # if normalize each channel of data separately.
+    NORM_EACH_CHANNEL = False   # if normalize each channel of data separately.
 
     OUTPUT_DIR = "datasets/" + DATASET_NAME
     DATA_FILE_PATH = "datasets/raw_data/{0}/{0}.csv".format(DATASET_NAME)

diff --git a/scripts/data_preparation/Illness/generate_training_data.py b/scripts/data_preparation/Illness/generate_training_data.py
@@ -132,7 +132,7 @@ def generate_data(args: argparse.Namespace):
     # Thus, because larger values of the loss function will be obtained when the magnitudes of different variables differ significantly,
     # the model will be trained to focus on the variable with the largest magnitude. Then, the loss is more likely to be reduced.
     # If downstream tasks have other requirements, you can set norm_each_channel to according to your needs.
-    NORM_EACH_CHANNEL = True   # if normalize each channel of data separately.
+    NORM_EACH_CHANNEL = False   # if normalize each channel of data separately.
 
     OUTPUT_DIR = "datasets/" + DATASET_NAME
     DATA_FILE_PATH = "datasets/raw_data/{0}/{0}.csv".format(DATASET_NAME)

diff --git a/scripts/data_preparation/Traffic/generate_training_data.py b/scripts/data_preparation/Traffic/generate_training_data.py
@@ -138,7 +138,7 @@ def generate_data(args: argparse.Namespace):
     # Thus, because larger values of the loss function will be obtained when the magnitudes of different variables differ significantly,
     # the model will be trained to focus on the variable with the largest magnitude. Then, the loss is more likely to be reduced.
     # If downstream tasks have other requirements, you can set norm_each_channel to according to your needs.
-    NORM_EACH_CHANNEL = True   # if normalize each channel of data separately.
+    NORM_EACH_CHANNEL = False   # if normalize each channel of data separately.
 
     OUTPUT_DIR = "datasets/" + DATASET_NAME
     DATA_FILE_PATH = "datasets/raw_data/{0}/{0}.csv".format(DATASET_NAME)