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5ffea26de7
Two fixes for single-GPU users on non-NVIDIA backends; multi-GPU
non-CUDA support is intentionally out of scope here (tracked separately).
1. get_all_torch_devices: add AMD/ROCm, MLU, and a generic fallback arm.
Previously the function only enumerated NVIDIA, Intel XPU, and Ascend
NPU when cpu_state==GPU; on AMD/ROCm (which exposes its GPU through
torch.cuda.*) and DirectML it fell through to an empty list. The
biggest user-visible regression: unload_all_models() iterates this
list, so it became a silent no-op on AMD/ROCm. /free, manager
unloads, and shutdown stopped releasing VRAM.
- is_amd() now shares the torch.cuda.* arm with is_nvidia(), since
ROCm reuses the CUDA API surface.
- is_mlu() gets its own arm using torch.mlu.device_count().
- A final fallback appends get_torch_device() for any GPU backend
the explicit arms miss (notably DirectML), so callers see at
least the current device and unload_all_models works.
MPS users are unaffected: cpu_state==MPS already routes to the
else branch which appends get_torch_device() returning mps.
2. main.py DynamicVRAM init: guard the comfy_aimdo branch with an
explicit is_nvidia() check.
The outer condition allows entering the DynamicVRAM init block when
the user passes --enable-dynamic-vram explicitly, bypassing the
implicit is_nvidia() gate. On non-NVIDIA backends this then runs
comfy_aimdo.control.init_devices(range(torch.cuda.device_count())),
which is comfy-aimdo-only territory and may crash at startup. Add a
leading is_nvidia() check that logs a clean warning and falls back
to the legacy ModelPatcher path.
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|---|---|---|
| .. | ||
| audio_encoders | ||
| background_removal | ||
| cldm | ||
| comfy_types | ||
| extra_samplers | ||
| image_encoders | ||
| k_diffusion | ||
| ldm | ||
| sd1_tokenizer | ||
| t2i_adapter | ||
| taesd | ||
| text_encoders | ||
| weight_adapter | ||
| bg_removal_model.py | ||
| cli_args.py | ||
| clip_config_bigg.json | ||
| clip_model.py | ||
| clip_vision_config_g.json | ||
| clip_vision_config_h.json | ||
| clip_vision_config_vitl_336_llava.json | ||
| clip_vision_config_vitl_336.json | ||
| clip_vision_config_vitl.json | ||
| clip_vision_siglip2_base_naflex.json | ||
| clip_vision_siglip_384.json | ||
| clip_vision_siglip_512.json | ||
| clip_vision.py | ||
| conds.py | ||
| context_windows.py | ||
| controlnet.py | ||
| deploy_environment.py | ||
| diffusers_convert.py | ||
| diffusers_load.py | ||
| float.py | ||
| gligen.py | ||
| hooks.py | ||
| latent_formats.py | ||
| lora_convert.py | ||
| lora.py | ||
| memory_management.py | ||
| model_base.py | ||
| model_detection.py | ||
| model_management.py | ||
| model_patcher.py | ||
| model_prefetch.py | ||
| model_sampling.py | ||
| multigpu.py | ||
| nested_tensor.py | ||
| ops.py | ||
| options.py | ||
| patcher_extension.py | ||
| pinned_memory.py | ||
| pixel_space_convert.py | ||
| quant_ops.py | ||
| rmsnorm.py | ||
| sample.py | ||
| sampler_helpers.py | ||
| samplers.py | ||
| sd1_clip_config.json | ||
| sd1_clip.py | ||
| sd.py | ||
| sdxl_clip.py | ||
| supported_models_base.py | ||
| supported_models.py | ||
| utils.py | ||