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* Fix Hunyuan 3D 2.1 multi-GPU worksplit: use cond_or_uncond instead of hardcoded chunk(2) Amp-Thread-ID: https://ampcode.com/threads/T-019da964-2cc8-77f9-9aae-23f65da233db Co-authored-by: Amp <amp@ampcode.com> * Add GPU device selection to all loader nodes - Add get_gpu_device_options() and resolve_gpu_device_option() helpers in model_management.py for vendor-agnostic GPU device selection - Add device widget to CheckpointLoaderSimple, UNETLoader, VAELoader - Expand device options in CLIPLoader, DualCLIPLoader, LTXAVTextEncoderLoader from [default, cpu] to include gpu:0, gpu:1, etc. on multi-GPU systems - Wire load_diffusion_model_state_dict and load_state_dict_guess_config to respect model_options['load_device'] - Graceful fallback: unrecognized devices (e.g. gpu:1 on single-GPU) silently fall back to default Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Add VALIDATE_INPUTS to skip device combo validation for workflow portability When a workflow saved on a 2-GPU machine (with device=gpu:1) is loaded on a 1-GPU machine, the combo validation would reject the unknown value. VALIDATE_INPUTS with the device parameter bypasses combo validation for that input only, allowing resolve_gpu_device_option to handle the graceful fallback at runtime. Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Set CUDA device context in outer_sample to match model load_device Custom CUDA kernels (comfy_kitchen fp8 quantization) use torch.cuda.current_device() for DLPack tensor export. When a model is loaded on a non-default GPU (e.g. cuda:1), the CUDA context must match or the kernel fails with 'Can't export tensors on a different CUDA device index'. Save and restore the previous device around sampling. Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Fix code review bugs: negative index guard, CPU offload_device, checkpoint te_model_options - resolve_gpu_device_option: reject negative indices (gpu:-1) - UNETLoader: set offload_device when cpu is selected - CheckpointLoaderSimple: pass te_model_options for CLIP device, set offload_device for cpu, pass load_device to VAE - load_diffusion_model_state_dict: respect offload_device from model_options - load_state_dict_guess_config: respect offload_device, pass load_device to VAE Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Fix CUDA device context for CLIP encoding and VAE encode/decode Add torch.cuda.set_device() calls to match model's load device in: - CLIP.encode_from_tokens: fixes 'Can't export tensors on a different CUDA device index' when CLIP is loaded on a non-default GPU - CLIP.encode_from_tokens_scheduled: same fix for the hooks code path - CLIP.generate: same fix for text generation - VAE.decode: fixes VAE decoding on non-default GPU - VAE.encode: fixes VAE encoding on non-default GPU Same pattern as the existing outer_sample fix in samplers.py - saves and restores previous CUDA device in a try/finally block. Amp-Thread-ID: https://ampcode.com/threads/T-019dabdc-8feb-766f-b4dc-f46ef4d8ff57 Co-authored-by: Amp <amp@ampcode.com> * Extract cuda_device_context manager, fix tiled VAE methods Add model_management.cuda_device_context() — a context manager that saves/restores torch.cuda.current_device when operating on a non-default GPU. Replaces 6 copies of the manual save/set/restore boilerplate. Refactored call sites: - CLIP.encode_from_tokens - CLIP.encode_from_tokens_scheduled (hooks path) - CLIP.generate - VAE.decode - VAE.encode - samplers.outer_sample Bug fixes (newly wrapped): - VAE.decode_tiled: was missing device context entirely, would fail on non-default GPU when called from 'VAE Decode (Tiled)' node - VAE.encode_tiled: same issue for 'VAE Encode (Tiled)' node Amp-Thread-ID: https://ampcode.com/threads/T-019dabdc-8feb-766f-b4dc-f46ef4d8ff57 Co-authored-by: Amp <amp@ampcode.com> * Restore CheckpointLoaderSimple, add CheckpointLoaderDevice Revert CheckpointLoaderSimple to its original form (no device input) so it remains the simple default loader. Add new CheckpointLoaderDevice node (advanced/loaders) with separate model_device, clip_device, and vae_device inputs for per-component GPU placement in multi-GPU setups. Amp-Thread-ID: https://ampcode.com/threads/T-019dabdc-8feb-766f-b4dc-f46ef4d8ff57 Co-authored-by: Amp <amp@ampcode.com> --------- Co-authored-by: Amp <amp@ampcode.com> |
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| .. | ||
| audio_encoders | ||
| cldm | ||
| comfy_types | ||
| extra_samplers | ||
| image_encoders | ||
| k_diffusion | ||
| ldm | ||
| sd1_tokenizer | ||
| t2i_adapter | ||
| taesd | ||
| text_encoders | ||
| weight_adapter | ||
| 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 | ||
| 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_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 | ||
| windows.py | ||