feat: closes #40

views/py/python_model_template.py

@@ -93,6 +93,10 @@ val_ds = list_ds.take(val_size)
 dataset = prepare_dataset(train_ds)
 dataset_validation   = prepare_dataset(val_ds)
 
+
+{{ if .LoadPrev }}
+model = tf.keras.saving.load_model('{{.LastModelRunPath}}')
+{{ else }}
 model = keras.Sequential([
     {{- range .Layers }}
     {{- if eq .LayerType 1}}
@@ -106,13 +110,14 @@ model = keras.Sequential([
     {{- end }}
     {{- end }}
 ])
+{{ end }}
 
 model.compile(
     loss=losses.SparseCategoricalCrossentropy(),
     optimizer=tf.keras.optimizers.Adam(),
     metrics=['accuracy'])
 
-his = model.fit(dataset, validation_data= dataset_validation, epochs=50, callbacks=[NotifyServerCallback()])
+his = model.fit(dataset, validation_data= dataset_validation, epochs={{.EPOCH_PER_RUN}}, callbacks=[NotifyServerCallback()])
 
 acc = his.history["accuracy"]
 
@@ -120,6 +125,6 @@ f = open("accuracy.val", "w")
 f.write(str(acc[-1]))
 f.close()
 
-tf.saved_model.save(model, "model")
 
-# model.save("model.keras", save_format="tf")
+tf.saved_model.save(model, "model")
+model.save("model.keras")