Week 1 - Jazz, music_inference_model error

Course Q&A Deep Learning Specialization Sequence Models
1 
       x = tf.math.argmax(out, axis=-1)
        x = tf.one_hot(indices=x, depth=n_values) 
        # Step 2.E: 
        # Use RepeatVector(1) to convert x into a tensor with shape=(None, 1, 90)
        x = RepeatVector(1)(x)

above is my code, but I got error:



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_11" was not an Input tensor, it was generated by layer repeat_vector_505.
Note that input tensors are instantiated via `tensor = tf.keras.Input(shape)`.
The tensor that caused the issue was: repeat_vector_505/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_11" was not an Input tensor, it was generated by layer lstm.
Note that input tensors are instantiated via `tensor = tf.keras.Input(shape)`.
The tensor that caused the issue was: lstm/PartitionedCall_543:0
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_11" was not an Input tensor, it was generated by layer lstm.
Note that input tensors are instantiated via `tensor = tf.keras.Input(shape)`.
The tensor that caused the issue was: lstm/PartitionedCall_543:3
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-62-a33998d93c7b> in <module>
----> 1 inference_model = music_inference_model(LSTM_cell, densor, Ty = 50)

<ipython-input-61-9754ccc18a8b> in music_inference_model(LSTM_cell, densor, Ty)
     57 
     58     # Step 3: Create model instance with the correct "inputs" and "outputs" (≈1 line)
---> 59     inference_model = Model(inputs=[x, a, c], outputs=outputs)
     60 
     61 

/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:
2

Try restarting the kernel and run all the cells in the notebook again.

3

Hi, I got exactly the same errors, restarting the kernel does not help.

Any helps, Thanks.

4

There are lots of posts about the Jazz assignment on the forum. I recommend you search for “music_inference_model” as the topic.

5

For anyone interested, the line model = Model(inputs=[input_x, initial_hidden_state, initial_cell_state], outputs=the_outputs) of this post is wrong, the inputs should be the initial values of x, a, and c.

6

I think that’s exactly what the instructions say to do.