UNQ_C1 : djmodel - Ex 2 in Week 1

Anantha · February 21, 2022, 1:00pm

UNQ_C1

GRADED FUNCTION: djmodel

After this function, which returns ‘model, the variable, ’model’ is assigned as :
model = djmodel(Tx=30, LSTM_cell=LSTM_cell, densor=densor, reshaper=reshaper)

Now, when the next unit, ‘#Unit Test’ is run, I get this in the output:

Test failed at index 1
Expected value

[‘TensorFlowOpLayer’, [(None, 90)], 0]

does not match the input value:

[‘Lambda’, (None, 90), 0]

AssertionError Traceback (most recent call last)
in
1 # UNIT TEST
2 output = summary(model)
----> 3 comparator(output, djmodel_out)

~/work/W1A3/test_utils.py in comparator(learner, instructor)
24 “\n\n does not match the input value: \n\n”,
25 colored(f"{b}", “red”))
—> 26 raise AssertionError(“Error in test”)
27 print(colored(“All tests passed!”, “green”))
28

AssertionError: Error in test

The next unit,
“# Check your model
model.summary()” , however, runs and gives an ‘expected’ output.
And the trouble is that after compiling and initialising the hidden state and cell state, the code for ‘training the model’:
history = model.fit([X, a0, c0], list(Y), epochs=100, verbose = 0),
Does not succeed, and ‘history’ is ‘not defined’.

QUESTION: Has djmodel been correctly done?

paulinpaloalto · February 21, 2022, 5:02pm

It sounds like something is wrong with your djmodel. I would start by investigating the first error about the unexpected Lambda function. For starters, are you sure you are running this on the course website and not in some local environment? If the latter, there are never any guarantees because of “versionitis” problems.

Also it might shed some light if you showed us the actual exception trace you get from running the model.fit cell.

Kic · February 21, 2022, 5:03pm

Hi @Anantha ,

There is problem with your djmodel() code. The assertion error is raised because the two arguments for comparator(), output and djmodel_out did not match during test. So, you need to check the ‘For’ loop within the djmodel() and make sure the correct parameters are passed.

Anantha · February 22, 2022, 5:26am

Dear Paul,
thanks for your reply. I started a new instance, and djmodel works- the unit test and model.summary, with no errors. Optimies, with Adam and model.compile, initialise, train and history - work fine, loss dropping from 29.xxx to 6.xxx, and the descending plot.
The problem is now with the ‘inference model’.
As parameters of LSTM_cell, I have used (x,[a,c]), ‘out’ comes from densor(a) and to ‘outputs’, i append ‘out’. ‘x’ is the maximum from ‘out’, using argmax and with tf.one_hot, I have tried with (x,n_values) as well as (x,90). And the parameter for RepeatVector(1) is x, it should convert x, which is (None,90) to (None,1,90).
However, there an error, which ends with:
" ValueError: Graph disconnected: cannot obtain value for tensor Tensor(“input_3:0”, shape=(None, 1, 90), dtype=float32) at layer “lstm”. The following previous layers were accessed without issue: "
While I am ‘following instructions’, the internals of what is going on is quite unclear!
Request help, and some resource to help me understand.
regards,
Anantha

Kic · February 22, 2022, 3:35pm

Hi @Anantha

When creating the inference_model instance, the inputs should be [x0,a0, c0].

Anantha · February 23, 2022, 5:47am

Thank you.
I had used [x0, a0,c0] as input, but, as it did not work, I shifted to [x,a0,c0] in view of the instruction:

model = Model(inputs=[input_x, initial_hidden_state, initial_cell_state], outputs=the_outputs)

Now, again with input as [x0,a0,co], i get this attribute error:

Kic · February 23, 2022, 11:50am

It should be c0, not co.

Anantha · February 23, 2022, 12:41pm

Yes, of course, sir, a typo in the mail. But c0 I the code

Anantha · February 23, 2022, 1:51pm

Sir,
No mistake in the code. It was c0. The mistake was in my mail.
Kindly respond to the question

Kic · February 23, 2022, 6:04pm

For creating the inference_model instance:
inteference_model = Model(inputs=[x0,a0,c0], outputs=outputs)

What attribute error did you get when your input is set to [x0,a0,c0]?

Anantha · February 24, 2022, 12:45am

inference_model=Model(inputs=[x0,a0,c0],outputs=outputs):

This is the attribute error:

Kic · February 24, 2022, 2:22pm

Hi @Anantha

Could you post the code for music_inference_model() in a direct message to me, I’ll have a look for you.

Anantha · February 24, 2022, 3:26pm

Where do I find your direct email, please?

Kic · February 24, 2022, 3:33pm

If you click on my icon, a dialogue box will appear, and you should find a blue ‘message’ box on the top right corner.

Anantha · February 25, 2022, 4:37pm

Dear Kin,
hope you received the direct message

Kic · February 25, 2022, 8:33pm