Sampling method parameters are unclear and it crashes Google Colab

[sdv-dev]

Sampling method parameters are unclear and it crashes Google Colab

[csala]

@tirthajyoti you can find all the API documentation here: https://dai-lab.github.io/TGAN/api/tgan.model.html

In particular, the sample method is here: https://dai-lab.github.io/TGAN/api/tgan.model.html#tgan.model.TGANModel.sample

As you can see, there isn't much documentation about the sampling arguments because there is only one argument, which needs no documentation: the number of samples to generate.

Regarding the Google Colab and the memory consumption, we cannot tell you whether it is normal or not because we do not have any insight on your data. Also, we have never executed TGAN on Google Colab ourselves.

However, yes, TGAN is memory intensive, just like any other GAN or data synthesization tool, and yes, it's normal that the memory consumption increases during sampling, as you are generating and trying to allocate new data that didn't exist before you started sampling.

One option that you have, if you have limited resources and can fit but not sample, is to delete the data variables and collect garbage after fitting, before sampling, to make sure that you have enough space to allocate the new data as it is generated.

[csala]

Hi @qwerkkk I think that you are hitting a different issue. Please have a look at the issue #41 that I just opened.

As you can see there, there is a problem that makes TGAN go into an infinite loop if the number of samples is lower than the batch_size, which defaults to 200.

So, in you case, the snippet of code that you pasted will never end. However, if you change SAMPLES to 200 or higher, the fit process will take a couple of minutes and then the sampling will be almost immediate.