get unstable results when evaluate the model about pygoturn HOT 3 CLOSED

Hi, I am still working on the inference part from the model. test.py may need some revisions. As of now, train.py is ready, just need to train for enough iterations to get a good working model.

In the original source code, they are using the same model but they set do_train to false in the test code here. So, essentially they are disabling the dropouts while testing I believe, which is equivalent to pytorch model.eval().

from pygoturn.

sure, since set model.eval() is normal standard procedure in most case,but so far the result is totally wrong in evaluation phase,which make no sense,because the Dropout will handle the scale problem itself.

from pygoturn.

Hi, I have fixed all these issues now. Please have a look at the updated README.

from pygoturn.