FutureWarning: This config doesn't use attention memories, a core feature of XLNet even though I'm using mem_len
So every time I try to run xl-net using the run_generation.py script, I get the warning : `FutureWarning: This config doesn't use attention memories, a core feature of XLNet. Consider setting mem_len to a non-zero value, for example xlnet = XLNetLMHeadModel.from_pretrained('xlnet-base-cased'', mem_len=1024), for accurate training performance as well as an order of magnitude faster inference.`

The issue is that I am using mem_len, I'm setting it to 384 (have tried other values as well) but I still get this warning.
Any solutions to this?

Thanks!<|||||>Hey, how are you setting `mem_len=384`? I am under the impression that the default `run_generation` script doesn't allow you to change the model from the default configuration, which would explain the warning.<|||||>Here is how I am setting it
`model = model_class.from_pretrained(args.model_name_or_path,cache_dir=args.cache_dir,mem_len=args.mem_len)`

<|||||>Ok, I've understood the issue - when using this call, the config first gets created with `mem_len=0` (hence the warning) then `mem_len` gets changed. I'll open a PR to move the warning to the `forward` call. In the meantime, you can suppress the warnings; memories are actually getting used.<|||||>Okay great! 
Thanks a lot. Closing the issue.