Merge pull request #580 from nasa/hotfix/v1.5.2

Hotfix v1.5.2

setup.py

@@ -22,7 +22,7 @@
 
 setup(
     name='prog_models',
-    version='1.5.1',
+    version='1.5.2',
     description='The NASA Prognostic Model Package is a python modeling framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.',
     long_description=long_description,
     long_description_content_type='text/markdown',

src/prog_models/__init__.py

@@ -7,4 +7,4 @@
 from prog_models.composite_model import CompositeModel
 from prog_models.linear_model import LinearModel
 
-__version__ = '1.5.1'
+__version__ = '1.5.2'

src/prog_models/data_models/lstm_model.py

@@ -537,10 +537,7 @@ def from_data(cls, inputs, outputs, event_states=None, t_met=None, **kwargs):
         from tensorflow import keras
 
         # Build model
-        callbacks = [
-            keras.callbacks.ModelCheckpoint("best_model.keras", save_best_only=True)
-        ]
-
+        callbacks = []
         if params['early_stop']:
             callbacks.append(keras.callbacks.EarlyStopping(**params['early_stop.cfg']))
 
@@ -592,8 +589,6 @@ def from_data(cls, inputs, outputs, event_states=None, t_met=None, **kwargs):
             workers=params['workers'],
             use_multiprocessing=(params['workers'] > 1))
 
-        model = keras.models.load_model("best_model.keras")
-
         # Split model into separate models
         n_state_layers = params['layers'] + 1 + (params['dropout'] > 0) + (params['normalize'])
         output_layer_input = keras.layers.Input(model.layers[n_state_layers-1].output.shape[1:])