I would suggest to double-check your PyTorch version on the laptop (by printing torch.__version__) to make sure that you got a very fresh relelease/nightly build. It seems really easy to have conda trick you into using an old version.
As explained by @ptrblck , here, there was a bug not too long ago:
  
    
    
    Mixed precision increases memory in meta-learning? mixed-precision
  
  
    Could you update to the latest stable release or the nightly and rerun the test? 
We hit a caching issue some time ago for linear layers (and fixed it). Based on the output you are seeing, I don’t think the problem is that AMP uses more memory in particular, but that the memory usage is clearly increasing/leaking.
  


Best regards
Thomas