Fix model loading - Using tensorflow1.15@nv43

.gitattributes

@@ -25,4 +25,3 @@ models/segnet2.keras filter=lfs diff=lfs merge=lfs -text
 external/opencl/*.deb filter=lfs diff=lfs merge=lfs -text
 phonelibs/zmq/aarch64-linux/lib/libzmq.a filter=lfs diff=lfs merge=lfs -text
 external/azcopy/azcopy filter=lfs diff=lfs merge=lfs -text
-models/** filter=lfs diff=lfs merge=lfs -text

selfdrive/modeld/runners/keras_runner.py

@@ -42,15 +42,12 @@ def run_loop(m):
   if len(gpus) > 0:
     if os.path.splitext(os.path.basename(sys.argv[1]))[0]== "supercombo":
       tf.config.experimental.set_virtual_device_configuration(gpus[0], [tf.config.experimental.VirtualDeviceConfiguration(memory_limit=2548)])
-      with open(f"{os.path.splitext(sys.argv[1])[0]}.model.keras", "r") as json_file:
-        m = model_from_json(json_file.read())
-      m.load_weights(f"{os.path.splitext(sys.argv[1])[0]}.weights.keras")
     else:
       tf.config.experimental.set_virtual_device_configuration(gpus[0], [tf.config.experimental.VirtualDeviceConfiguration(memory_limit=256)])
-      m = load_model(sys.argv[1], compile=False)
-  else:
-    m = load_model(sys.argv[1], compile=False)
-      
+  with open(f"{os.path.splitext(sys.argv[1])[0]}.model.keras", "r") as json_file:
+    m = model_from_json(json_file.read())
+    m.load_weights(f"{os.path.splitext(sys.argv[1])[0]}.weights.keras")
+
   bs = [int(np.product(ii.shape[1:])) for ii in m.inputs]
   ri = keras.layers.Input((sum(bs),))
   tii = []