Music inference model tenserflow error

I keep receiving this error after I have run the following code -
inference_model = music_inference_model(LSTM_cell, densor, Ty = 50)

I tried adding this line before this code but it did not help. Can someone please help me?
LSTM_cell = LSTM(n_a, return_state = True)

the error is-

WARNING:tensorflow:Functional inputs must come from tf.keras.Input (thus holding past layer metadata), they cannot be the output of a previous non-Input layer. Here, a tensor specified as input to “functional_4” was not an Input tensor, it was generated by layer repeat_vector_149.
Note that input tensors are instantiated via tensor = tf.keras.Input(shape).
The tensor that caused the issue was: repeat_vector_149/Tile:0
WARNING:tensorflow:Functional inputs must come from tf.keras.Input (thus holding past layer metadata), they cannot be the output of a previous non-Input layer. Here, a tensor specified as input to “functional_4” was not an Input tensor, it was generated by layer lstm_2.
Note that input tensors are instantiated via tensor = tf.keras.Input(shape).
The tensor that caused the issue was: lstm_2/PartitionedCall_49:0
WARNING:tensorflow:Functional inputs must come from tf.keras.Input (thus holding past layer metadata), they cannot be the output of a previous non-Input layer. Here, a tensor specified as input to “functional_4” was not an Input tensor, it was generated by layer lstm_2.
Note that input tensors are instantiated via tensor = tf.keras.Input(shape).
The tensor that caused the issue was: lstm_2/PartitionedCall_49:3

AssertionError Traceback (most recent call last)
in
----> 1 inference_model = music_inference_model(LSTM_cell, densor, Ty = 50)

in music_inference_model(LSTM_cell, densor, Ty)
56
57 # Step 3: Create model instance with the correct “inputs” and “outputs” (≈1 line)
—> 58 inference_model = Model(inputs=[x, a, c], outputs=outputs)
59
60 ### END CODE HERE ###

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py in new(cls, *args, **kwargs)
240 # Functional model
241 from tensorflow.python.keras.engine import functional # pylint: disable=g-import-not-at-top
→ 242 return functional.Functional(*args, **kwargs)
243 else:
244 return super(Model, cls).new(cls, *args, **kwargs)

/opt/conda/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
456 try:
→ 457 result = method(self, *args, **kwargs)
458 finally:
459 self._self_setattr_tracking = previous_value # pylint: disable=protected-access

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/functional.py in init(self, inputs, outputs, name, trainable)
113 # ‘arguments during initialization. Got an unexpected argument:’)
114 super(Functional, self).init(name=name, trainable=trainable)
→ 115 self._init_graph_network(inputs, outputs)
116
117 @trackable.no_automatic_dependency_tracking

/opt/conda/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
456 try:
→ 457 result = method(self, *args, **kwargs)
458 finally:
459 self._self_setattr_tracking = previous_value # pylint: disable=protected-access

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/functional.py in _init_graph_network(self, inputs, outputs)
182 # It’s supposed to be an input layer, so only one node
183 # and one tensor output.
→ 184 assert node_index == 0
185 assert tensor_index == 0
186 self._input_layers.append(layer)

AssertionError:

There may be some other errors, but, the first thing to fix is this.
A model should be created with “input” and “output” for the network. But, your inputs are not initial inputs. This should be a problem in creating a model.

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