ValueError: Output tensors to a Model must be the output of a TensorFlow `Layer` (thus holding past layer metadata)

Encountering an error using the functional API of keras from within TensorFlow. The layers compile fine until I attempt to initiate the Model object (tf.keras.Model) at which point I receive the below error and traceback.

The last layer wrapper is below:

def dense(self,kwargs):
    print('simple old Dense layer')
    self.layer_outputs[kwargs['LayerID']] = tf.keras.layers.Lambda(tf.layers.Dense(name=self._namer(kwargs['LayerID']), **kwargs['LayerKwargs']))(self.layer_outputs[kwargs['LayerInput']])
    if kwargs['args'].setdefault('norm',True):
        self.layer_outputs[kwargs['LayerID']] = self.batchnorm_relu(self.layer_outputs[kwargs['LayerID']],kwargs['LayerID'])
    return self.layer_outputs[kwargs['LayerID']]

I've reviewed other questions regarding similar errors, here, here and here. All of these issues were resolved either by correcting the input or wrapping the output in a keras.Lambda layer wrapper, neither of which seem to be working for me.

My input is below:

self.input_proxy = tf.keras.layers.Input(shape=self.batch_input_shape[1:],dtype=tf.float32)

One answer which I haven't yet tried is here, wherein I would assign the missing requisite meta_data manually. This may work, but seems awfully hacky and I'd like a more straightforward solution that works with the API if possible.

Why is this happening and how can I resolve it?

   C:\Users\asus\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\keras\engine\training.py in __init__(self, *args, **kwargs)
        115
        116   def __init__(self, *args, **kwargs):
    --> 117     super(Model, self).__init__(*args, **kwargs)
        118     # Create a cache for iterator get_next op.
        119     self._iterator_get_next = weakref.WeakKeyDictionary()

    C:\Users\asus\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\keras\engine\network.py in __init__(self, *args, **kwargs)
         78         'inputs' in kwargs and 'outputs' in kwargs):
         79       # Graph network
    ---> 80       self._init_graph_network(*args, **kwargs)
         81     else:
         82       # Subclassed network

    C:\Users\asus\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\training\checkpointable\base.py in _method_wrapper(self, *args, **kwargs)
        424     self._setattr_tracking = False  # pylint: disable=protected-access
        425     try:
    --> 426       method(self, *args, **kwargs)
        427     finally:
        428       self._setattr_tracking = previous_value  # pylint: disable=protected-access

    C:\Users\asus\AppData\Roaming\Python\Python36\site-packages\tensorflow\python\keras\engine\network.py in _init_graph_network(self, inputs, outputs, name)
        222         raise ValueError('Output tensors to a ' + cls_name + ' must be '
        223                          'the output of a TensorFlow `Layer` '
    --> 224                          '(thus holding past layer metadata). Found: ' + str(x))
        225
        226     self._base_init(name=name)

    ValueError: Output tensors to a Model must be the output of a TensorFlow `Layer` (thus holding past layer metadata). Found: Tensor("lambda/Last__0/BiasAdd:0",