C5 W1 E3 - Jazz - Music Inference Model Error: Graph Disconnected

Course Q&A Deep Learning Specialization Sequence Models
1

Hi,

I am stuck on this problem for quite some time and I didn’t know how to address it. I’ve checked the dimensions for x through the function suggested by mentors and it is correct, but I encounter this error:

Graph disconnected: cannot obtain value for tensor Tensor("input_5:0", shape=(None, 1, 90), dtype=float32) at layer "lstm_4". The following previous layers were accessed without issue: []

While restarting the kernel or rerunning the block, I’ve found that the error happens in different layer each time such as “lstm_4”, “lstm_3” …

It also gives a funny warning:

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

In the error message, the graph disconnected error is pointed to the model line.

ValueError                                Traceback (most recent call last)
<ipython-input-26-c55ce93f25e1> in <module>
      1 LSTM_cell = LSTM(n_a, return_state = True)
----> 2 inference_model = music_inference_model(LSTM_cell, densor, Ty = 50)

<ipython-input-25-a67ee3af6354> 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, a0, c0], outputs=outputs)
     59 
     60     ### END CODE HERE ###

I cannot identify the error with my limited knowledge, can anyone explain this problem?

Best regards,
Thank you!

2

The issue is that in Step 3, ‘x’ is not the correct variable to use in the “inputs” tuple.

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