RuntimeError: The layer has never been called and thus has no defined output shape. about importance-sampling HOT 6 OPEN

Hi, do you mind sharing the TF and keras versions that you are using? Also, you could try to use an older version from around the time that the library was released.

Cheers,
Angelos

from importance-sampling.

i use TF v2.3.1 and keras v2.4.3. could you share your version of these ?

from importance-sampling.

It has been a long time since I tested the code and in general tensorflow 2 is not supported. You can also see issue #25 for more details.

I would suggest TF 1.13.1 and keras 2.0.0 for testing purposes but you might even get it working with TF 2.1 and keras 2.3.1 .

from importance-sampling.

ok, thanks your answer and link. i tried to downgrade TF and others. i will reset all setting, restart on your suggestion version.
i will re-visit to write the result, soon.

from importance-sampling.

Hi, if useful, I got an mnist example to almost work with:
tensorflow==2.3.1
keras==2.3.1

Still get an error though:

score = model.evaluate(x_test, y_test, verbose=0)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'input_1' with dtype float and shape [?,10]

from importance-sampling.

Alright, I finally got it to work!
tensorflow==1.13.1
keras==2.2.4

Specifically, /examples/mnist_mlp.py with args.importance_training=True.

With tensorflow 1.3.1, was not able to install the above-suggested keras 2.0.0 since "seqeval 0.0.12 requires Keras>=2.2.4, but you have keras 2.0.0 which is incompatible."

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