When I create a model like this, there is a bug at runtime

[avan-debug]

state_input = Input(shape=(84, 84, 4), name='state_input', dtype='uint8')
advantage = Input(shape=(1,), name="adv")
state_input_1 = Lambda(layer_function)(state_input)
convlayer = Conv2D(32, (8, 8), strides=(4, 4), activation='relu', padding='valid')(state_input_1)
convlayer = Conv2D(64, (4, 4), strides=(2, 2), activation='relu', padding='valid')(convlayer)
convlayer = Conv2D(64, (3, 3), strides=(1, 1), activation='relu', padding='valid')(convlayer)
flattenlayer = Flatten()(convlayer)
denselayer = Dense(256, activation='relu')(flattenlayer)

out_actions = Dense(4, activation='softmax', name='output_actions')(denselayer)
out_value = Dense(1, name='output_value')(denselayer)
model = Model(inputs=[state_input, advantage], outputs=[out_actions, out_value])

pruned_model = pruning.factor_pruning(model, dense_prune_rate, conv_prune_rate, 'L2', num_classes=10)

Traceback (most recent call last):
File "/home/xys/primary_xingtian/xingtian-pruning/xt/structured_pruning/src/test/pruning_function_test.py", line 86, in
pruned_model = pruning.factor_pruning(model, dense_prune_rate, conv_prune_rate, 'L2', num_classes=10)
File "/home/xys/primary_xingtian/xingtian-pruning/xt/structured_pruning/src/pruning.py", line 77, in factor_pruning
num_new_neurons, num_new_filters, comp)
File "/home/xys/primary_xingtian/xingtian-pruning/xt/structured_pruning/src/pruning_helper_functions.py", line 259, in build_pruned_model
pruned_model.layers[i].set_weights(new_model_param[i])
File "/home/tank/miniconda3/envs/openmmlab/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1826, in set_weights
'shape %s' % (ref_shape, weight.shape))
ValueError: Layer weight shape (1911, 180) not compatible with provided weight shape (1886, 180)