diff --git a/plotting.py b/plotting.py
index 01061b211c060e6d91ffb2cfd61607f84efa0991..86e476ed9f6b3af809ff31c3bb10265a6232a60e 100644
--- a/plotting.py
+++ b/plotting.py
@@ -10,7 +10,7 @@ from mpl_toolkits.axes_grid1 import ImageGrid, make_axes_locatable
 import numpy as np
 
 from .keras_visualize_activations.read_activations import get_activations
-from .tfhelpers import get_grad_function, max_activation_wrt_input, create_random_event
+from .utils import get_grad_function, max_activation_wrt_input, create_random_event
 
 import logging
 logger = logging.getLogger(__name__)
@@ -328,10 +328,9 @@ if __name__ == "__main__":
 
     import logging
     logging.basicConfig()
-    logging.getLogger("tfhelpers").setLevel(logging.DEBUG)
-    logging.getLogger(__name__).setLevel(logging.DEBUG)
+    logging.getLogger().setLevel(logging.DEBUG)
 
-    from .tfhelpers import get_single_neuron_function, get_max_activation_events
+    from .utils import get_single_neuron_function, get_max_activation_events
 
     import meme
     # meme.setOptions(overrideCache="/scratch-local/nhartmann/meme_cache")
diff --git a/scripts/plot_NN_2D.py b/scripts/plot_NN_2D.py
index 59819d19dfe69ecfe0b5fd3bf9e0d01a548dd406..ab310d8a2520b0c3cd10fe5f860c2f3dd1a3e68c 100755
--- a/scripts/plot_NN_2D.py
+++ b/scripts/plot_NN_2D.py
@@ -15,7 +15,7 @@ from KerasROOTClassification.plotting import (
     plot_hist_2D_events,
     plot_cond_avg_actmax_2D
 )
-from KerasROOTClassification.tfhelpers import get_single_neuron_function, get_max_activation_events
+from KerasROOTClassification.utils import get_single_neuron_function, get_max_activation_events
 
 parser = argparse.ArgumentParser(description='Create various 2D plots for a single neuron')
 parser.add_argument("project_dir")
diff --git a/tfhelpers.py b/utils.py
similarity index 98%
rename from tfhelpers.py
rename to utils.py
index 8f3c7b49de0b89e4f8c68d08fc166f0137d8ea0a..4c6fe8a4f0c518ffb6630bb5b3ca6ea1249575ac 100644
--- a/tfhelpers.py
+++ b/utils.py
@@ -8,7 +8,7 @@ import keras.backend as K
 
 from meme import cache
 
-logger = logging.getLogger("tfhelpers")
+logger = logging.getLogger(__name__)
 logger.addHandler(logging.NullHandler())
 
 def get_single_neuron_function(model, layer, neuron, scaler=None):