If this is not crashing then PyTorch is most likely running with your AMD graphics card and ROCm, if not see magic variables

debug_pytorch_rocm.py

import torch

print("pytorch version: " + torch.__version__)
print("CUDA available: " + str(torch.cuda.is_available()))
print("device count: " + str(torch.cuda.device_count()))
print("current device: " + str(torch.cuda.current_device()))
print("device name: " + torch.cuda.get_device_name(torch.cuda.current_device()))
print("backend:")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(device)

print("small matmul")
a = torch.rand(3, 3).to(device)
b = torch.rand(3, 3).to(device)
res = torch.matmul(a, b)
print(res)
print(res.size())
print("larger matmul")
a = torch.rand(1280, 1280).to(device)
b = torch.rand(1280, 1280).to(device)
res = torch.matmul(a, b)
print(res)
print(res.size())

magic_variables.sh

# first test if it works without hip
# hide all hip devices
HIP_VISIBLE_DEVICES=
python debug_pytorch_rocm.py

# some programs don't work with multi gpu setups, to hide all other than first card
HIP_VISIBLE_DEVICES=0
python debug_pytorch_rocm.py

# find out the architecture of your card
amdgpu-arch
# architecture of my card, 6600 M (same for XT) is gfx1032
#export PYTORCH_ROCM_ARCH="gfx1032"
#export HSA_OVERRIDE_GFX_VERSION=10.3.2

# pytorch was only compiled for certain supported archs though
# https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/3rd-party/pytorch-install.html
# so we tell it to use a compatible supported architecture
# PLEASE MAKE SURE TO CHOOSE A COMPATIBLE ARCH
export PYTORCH_ROCM_ARCH="gfx1030"
export HSA_OVERRIDE_GFX_VERSION=10.3.0

# NOT NEEDED set compiler target, HSA_OVERRIDE_GFX_VERSION should set that too
# export HCC_AMDGPU_TARGET=gfx1030
 
python debug_pytorch_rocm.py
# this should work now :D
# if not, increase log level from 1 to 3
AMD_LOG_LEVEL=3