LayerConvNeXtGamma: avoid adding an EagerTensor to config

Very weird how this is a problem when it wasn't before..

aimodel/src/lib/ai/components/LayerConvNeXtGamma.py

@@ -15,6 +15,5 @@ class LayerConvNeXtGamma(tf.keras.layers.Layer):
 	def get_config(self):
 		config = super(LayerConvNeXtGamma, self).get_config()
 		
-        config.update({ "const": self.const, "dim": self.dim })
-        
+		config.update({ "const": self.const.numpy(), "dim": self.dim })
 		return config

aimodel/src/lib/ai/helpers/make_callbacks.py

@@ -16,7 +16,7 @@ def make_callbacks(dirpath, model_predict):
 			model_to_checkpoint=model_predict,
 			filepath=os.path.join(
 				dirpath_checkpoints,
-				"checkpoint_weights_e{epoch:d}_loss{loss:.3f}.hdf5"
+				"checkpoint_e{epoch:d}_loss{loss:.3f}.hdf5"
 			),
 			monitor="loss"
 		),