How to replace the input layer of a pre-trained tensorflow model with our own input layer...?

Question

I have a pre-trained model with input shape of shape=(None,4096, 12). I want to use this trained model with my own input layer having shape=(None, 1250, 5). i have tried the solution posted here. but i got error

enter ValueError                                Traceback (most recent call last)
/tmp/ipykernel_34/2421370102.py in <module>
2 weights = [layer.get_weights() for layer in mod.layers[1:]]
3 for layer, weight in zip(new_model.layers[1:], weights):
----> 4     layer.set_weights(weight)
/opt/conda/lib/python3.7/site-packages/keras/engine/base_layer.py in 
set_weights(self, weights)
1799           raise ValueError(
1800               'Layer weight shape %s not compatible with 
provided weight '
-> 1801               'shape %s' % (ref_shape, weight_shape))
1802         weight_value_tuples.append((param, weight))
1803         weight_index += 1

ValueError: Layer weight shape (16, 5, 64) not compatible with 
provided weight shape (16, 12, 64)