ark626

@Teravus THANKS for that hint, the Librosa Cache is for me a HUGE improvement, since im learning on an Jetson AGX Xavier, where the CPU is a lot weaker it...

From my pov it is this call prediction = sess.run(outputs, feed_dict={samples: window})[0] It never returns anything after this in the generator.py. Currently im analyzing why

Would also love to see it running on aarch64 since torch is now running there already. #657 ive also already commented, seems like the installation of the prequisites is the...

Okay got it installed by working myself around. => Run the Script once until it fails Then alter the Parts like this (so libmad and lame are not overwritten) ```...

Yes i fit ist running. I will answere later in more Detail. In the meantime you Coupe Check the Guide in this ive written JetsonXavierAGX

Okay so in general the guide here referes to some of the usefull things ive used: https://github.com/ark626/JetsonXavierAGX If i recall it properly to run MelGAN-VC you needed to install torch...

I used: torch @ file:///media/ext/dataSets/MelGANVC/torch-1.6.0rc2-cp36-cp36m-linux_aarch64.whl # Editable install with no version control (torchaudio==0.7.0a0+102174e) -e /usr/local/lib/python3.6/dist-packages/torchaudio-0.7.0a0+102174e-py3.6-linux-aarch64.egg The torch is linked in my guide.(https://drive.google.com/drive/folders/1Ee9S9Ab892n_rONX4zqQdbjjt5rTnHwV?usp=sharing) For the torchaudio i sadly dont recall how...

I think the issue here was the tf version. Try installing tensorflow==1.15.4+nv20.11 Also it seems that that the memory is a little bit to small and ran out of memory...

to reduce the ram usage you can reduce the vec_len i.E. 64 or 32. The sampling rate sr should match the ones of your samples you use to train. Also...

I checked the stable diffusion. Most of the "Need" for python 3.10 stems from using things like the new Typing. This is easily exchangeable and gives downwards compatibility to 3.9....