Well, try it with bicubic on your system first, your numbers (that I presume are with bilinear scaling) are already higher than mine.
If you want to get that exact accuracy in test, hunt through past PyTorch versions and their associated libraries… I doubt it’s worth it for .34%. I think I did the 77.29 test around PyTorch 0.2.0 w/ CUDA 7.5 or 8 and CUDNN 6
Edit: Before you actually spend time doing that, just switch to dpn68b and be done with it  It’s a punchy little model w/ pretrained weights that’ll give you slightly higher accuracy than densenet-201… with 7.4m less parameters.