Recibo un error al intentar guardar un modelo con capas de aumento de datos con Tensorflow versión 2.7.0.

Aquí está el código de aumento de datos:

 input_shape_rgb = (img_height, img_width, 3) data_augmentation_rgb = tf.keras.Sequential( [ layers.RandomFlip("horizontal"), layers.RandomFlip("vertical"), layers.RandomRotation(0.5), layers.RandomZoom(0.5), layers.RandomContrast(0.5), RandomColorDistortion(name='random_contrast_brightness/none'), ] )

Ahora construyo mi modelo así:

 # Build the model input_shape = (img_height, img_width, 3) model = Sequential([ layers.Input(input_shape), data_augmentation_rgb, layers.Rescaling((1./255)), layers.Conv2D(16, kernel_size, padding=padding, activation='relu', strides=1, data_format='channels_last'), layers.MaxPooling2D(), layers.BatchNormalization(), layers.Conv2D(32, kernel_size, padding=padding, activation='relu'), # best 4 layers.MaxPooling2D(), layers.BatchNormalization(), layers.Conv2D(64, kernel_size, padding=padding, activation='relu'), # best 3 layers.MaxPooling2D(), layers.BatchNormalization(), layers.Conv2D(128, kernel_size, padding=padding, activation='relu'), # best 3 layers.MaxPooling2D(), layers.BatchNormalization(), layers.Flatten(), layers.Dense(128, activation='relu'), # best 1 layers.Dropout(0.1), layers.Dense(128, activation='relu'), # best 1 layers.Dropout(0.1), layers.Dense(64, activation='relu'), # best 1 layers.Dropout(0.1), layers.Dense(num_classes, activation = 'softmax') ]) model.compile(loss='categorical_crossentropy', optimizer='adam',metrics=metrics) model.summary()

Luego, una vez que finaliza el entrenamiento, solo hago:

 model.save("./")

Y estoy recibiendo este error:

 --------------------------------------------------------------------------- KeyError Traceback (most recent call last) <ipython-input-84-87d3f09f8bee> in <module>() ----> 1 model.save("./") /usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs) 65 except Exception as e: # pylint: disable=broad-except 66 filtered_tb = _process_traceback_frames(e.__traceback__) ---> 67 raise e.with_traceback(filtered_tb) from None 68 finally: 69 del filtered_tb /usr/local/lib/python3.7/dist- packages/tensorflow/python/saved_model/function_serialization.py in serialize_concrete_function(concrete_function, node_ids, coder) 66 except KeyError: 67 raise KeyError( ---> 68 f"Failed to add concrete function '{concrete_function.name}' to object-" 69 f"based SavedModel as it captures tensor {capture!r} which is unsupported" 70 " or not reachable from root. " KeyError: "Failed to add concrete function 'b'__inference_sequential_46_layer_call_fn_662953'' to object-based SavedModel as it captures tensor <tf.Tensor: shape=(), dtype=resource, value=<Resource Tensor>> which is unsupported or not reachable from root. One reason could be that a stateful object or a variable that the function depends on is not assigned to an attribute of the serialized trackable object (see SaveTest.test_captures_unreachable_variable)."

Inspeccioné el motivo de recibir este error al cambiar la arquitectura de mi modelo y descubrí que el motivo provino de la capa data_augmentation ya que RandomFlip y RandomRotation y otros se cambiaron de layers.experimental.prepocessing.RandomFlip a layers.RandomFlip , pero aún así aparece el error.