How to set Keras layer to include `None` in return tuple - tensorflow

Question

I am trying to make a Keras layer that returns None in its tuple.
class transformer_IO(tf.keras.layers.Layer):
def call(self, input):
return (input, None, None, None)
However, when I try to compile with this error, I get
AttributeError: 'NoneType' object has no attribute 'shape'
Here is an example
!pip install transformers
from transformers import TFBertModel
import tensorflow as tf
from copy import deepcopy
class transformer_IO(tf.keras.layers.Layer):
def call(self, input):
return (input, None, None, None)
def get_functional_model_protoFix():
bioRoberta_f = TFBertModel.from_pretrained('bert-base-uncased', from_pt=True)
Q_Tlayer0_f = deepcopy(bioRoberta_f.layers[0].encoder.layer[8])
Q_Tlayer0_f._name = Q_Tlayer0_f._name + 'Query_f'
Q_Tlayer1_f = deepcopy(bioRoberta_f.layers[0].encoder.layer[9])
Q_Tlayer1_f._name = Q_Tlayer1_f._name + 'Query_f'
transIO = transformer_IO()
inputIds = tf.keras.Input(shape=(None,), dtype=tf.int32, name='input_Q')
Q_outputs = bioRoberta_f(inputIds)[0]
Q_outputs = transIO(Q_outputs)
Q_outputs = Q_Tlayer0_f(Q_outputs)[0]
Q_outputs = transIO(Q_outputs)
Q_outputs = Q_Tlayer1_f(Q_outputs)[0]
modelNew = tf.keras.Model(inputs=inputIds, outputs=Q_outputs)
return modelNew
model_functional = get_functional_model_protoFix()
model_functional.compile(loss=loss_fn,
optimizer=tfa.optimizers.AdamW(weight_decay=1e-4, learning_rate=1e-5,
epsilon=1e-06))
Full error message
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-35-a029c18cecf9> in <module>()
----> 1 model_functional_new = get_functional_model_protoFix()
2 model_functional_new.compile(loss=loss_fn,
3 optimizer=tfa.optimizers.AdamW(weight_decay=1e-4, learning_rate=1e-5,
4 epsilon=1e-06))
7 frames
<ipython-input-34-693ee085f848> in get_functional_model_protoFix()
13
14 Q_outputs = bioRoberta_f(inputIds)[0]
---> 15 Q_outputs = transIO(Q_outputs)
16 Q_outputs = Q_Tlayer0_f(Q_outputs)[0]
17 Q_outputs = transIO(Q_outputs)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
952 kwargs.pop('mask')
953 inputs, outputs = self._set_connectivity_metadata_(
--> 954 inputs, outputs, args, kwargs)
955 self._handle_activity_regularization(inputs, outputs)
956 self._set_mask_metadata(inputs, outputs, input_masks)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in _set_connectivity_metadata_(self, inputs, outputs, args, kwargs)
2312 # This updates the layer history of the output tensor(s).
2313 self._add_inbound_node(
-> 2314 input_tensors=inputs, output_tensors=outputs, arguments=arguments)
2315 return inputs, outputs
2316
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in _add_inbound_node(self, input_tensors, output_tensors, arguments)
2342 input_tensors=input_tensors,
2343 output_tensors=output_tensors,
-> 2344 arguments=arguments)
2345
2346 # Update tensor history metadata.
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/node.py in __init__(self, outbound_layer, inbound_layers, node_indices, tensor_indices, input_tensors, output_tensors, arguments)
108 self.input_shapes = nest.map_structure(backend.int_shape, input_tensors)
109 # Nested structure of shape tuples, shapes of output_tensors.
--> 110 self.output_shapes = nest.map_structure(backend.int_shape, output_tensors)
111
112 # Optional keyword arguments to layer's `call`.
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in map_structure(func, *structure, **kwargs)
615
616 return pack_sequence_as(
--> 617 structure[0], [func(*x) for x in entries],
618 expand_composites=expand_composites)
619
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in <listcomp>(.0)
615
616 return pack_sequence_as(
--> 617 structure[0], [func(*x) for x in entries],
618 expand_composites=expand_composites)
619
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/backend.py in int_shape(x)
1201 """
1202 try:
-> 1203 shape = x.shape
1204 if not isinstance(shape, tuple):
1205 shape = tuple(shape.as_list())
AttributeError: 'NoneType' object has no attribute 'shape'