Merge 69a5578b11 into 37ac9ff44f
This commit is contained in:
liminfei-amd
GitHub
commit
6f08c34836
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@ -433,6 +433,98 @@ def is_amd():
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return True
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return False
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def is_integrated_gpu(device=None):
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# AMD APUs / integrated GPUs expose host RAM (GTT/shared) as device memory
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# via mem_get_info(); torch flags these as integrated. See ComfyUI #14274.
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if cpu_state != CPUState.GPU:
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return False
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if not (is_nvidia() or is_amd()):
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return False
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try:
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if device is None:
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device = get_torch_device()
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return bool(getattr(torch.cuda.get_device_properties(device), "is_integrated", 0))
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except Exception:
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return False
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def _amd_vram_gtt_totals(device=None):
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# Best-effort (vram_total, gtt_total) in bytes from the amdgpu sysfs nodes
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# mem_info_vram_total / mem_info_gtt_total, or None when they cannot be read
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# (e.g. NVIDIA Tegra integrated parts that have no dedicated VRAM). #14274
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if not is_amd():
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return None
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try:
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drm_root = "/sys/class/drm"
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candidates = []
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for name in os.listdir(drm_root):
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if not (name.startswith("card") and name[len("card"):].isdigit()):
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continue
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dev_dir = os.path.join(drm_root, name, "device")
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vram_path = os.path.join(dev_dir, "mem_info_vram_total")
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gtt_path = os.path.join(dev_dir, "mem_info_gtt_total")
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if not (os.path.exists(vram_path) and os.path.exists(gtt_path)):
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continue
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try:
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with open(os.path.join(dev_dir, "vendor")) as vf:
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if vf.read().strip().lower() != "0x1002":
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continue
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except OSError:
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pass
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candidates.append((os.path.basename(os.path.realpath(dev_dir)), vram_path, gtt_path))
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if not candidates:
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return None
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chosen = None
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target_bdf = None
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try:
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if device is None:
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device = get_torch_device()
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props = torch.cuda.get_device_properties(device)
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# torch reports the PCI location as integers (pci_domain_id / pci_bus_id
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# / pci_device_id); amdgpu names its sysfs nodes as a hex
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# "domain:bus:device.function" BDF. Build the canonical hex BDF so the
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# two are comparable (the old str(pci_bus_id) compared a decimal bus
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# number against a hex BDF string and could never match). #14274
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target_bdf = "%04x:%02x:%02x" % (
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int(getattr(props, "pci_domain_id", 0) or 0),
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int(getattr(props, "pci_bus_id", 0) or 0),
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int(getattr(props, "pci_device_id", 0) or 0),
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)
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except Exception:
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target_bdf = None
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if target_bdf:
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for pci, vram_path, gtt_path in candidates:
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# candidates carry the realpath() leaf BDF (domain:bus:device.function),
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# so matching the domain:bus:device part works whether the GPU is
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# attached directly or sits behind a PCIe bridge (nested sysfs path). #14274
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if pci.lower().rsplit(".", 1)[0] == target_bdf:
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chosen = (vram_path, gtt_path)
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break
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if chosen is None and len(candidates) == 1:
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chosen = (candidates[0][1], candidates[0][2])
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if chosen is None:
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return None
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with open(chosen[0]) as f:
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vram_total = int(f.read().strip())
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with open(chosen[1]) as f:
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gtt_total = int(f.read().strip())
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return (vram_total, gtt_total)
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except Exception:
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return None
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def integrated_gpu_is_shared_heavy(device=None):
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# For an integrated GPU, decide whether its memory is dominated by the shared
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# GTT/host-RAM aperture (treat as UMA -> SHARED) or by a large dedicated VRAM
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# carveout (keep NORMAL/HIGH_VRAM). Keys on the amdgpu mem_info_vram_total vs
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# mem_info_gtt_total ratio (ComfyUI #14274). Defaults to True when the totals
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# are unavailable (e.g. NVIDIA Tegra parts that have no dedicated VRAM).
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totals = _amd_vram_gtt_totals(device)
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if totals is None:
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return True
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vram_total, gtt_total = totals
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if not vram_total or vram_total <= 0:
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return True
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return gtt_total >= vram_total
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def amd_min_version(device=None, min_rdna_version=0):
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if not is_amd():
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return False
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@ -578,6 +670,15 @@ if cpu_state != CPUState.GPU:
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if cpu_state == CPUState.MPS:
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vram_state = VRAMState.SHARED
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if vram_state == VRAMState.NORMAL_VRAM and is_integrated_gpu() and integrated_gpu_is_shared_heavy():
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# Integrated/UMA GPU whose shared GTT/host-RAM pool dominates the (small)
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# dedicated VRAM carveout: treat as UMA and use SHARED so the shared pool is
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# not double-counted as dedicated VRAM (#14274). Dedicated-heavy integrated
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# parts (large BIOS UMA carveout, e.g. Strix Halo) keep NORMAL_VRAM where
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# HIGH_VRAM is correct.
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vram_state = VRAMState.SHARED
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logging.info("Integrated GPU with shared-memory-dominant pool detected (UMA): using SHARED vram state to avoid double-counting GTT/shared memory as dedicated VRAM.")
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logging.info(f"Set vram state to: {vram_state.name}")
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DISABLE_SMART_MEMORY = args.disable_smart_memory
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@ -0,0 +1,241 @@
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import builtins
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import io
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from types import SimpleNamespace
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import pytest
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import torch
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from comfy.cli_args import args as cli_args
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original_cpu_arg = cli_args.cpu
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if not torch.cuda.is_available():
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cli_args.cpu = True
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import comfy.model_management as model_management # noqa: E402
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cli_args.cpu = original_cpu_arg
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MIXED_TOPOLOGY = {
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"card1": {
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"realpath": "/sys/devices/pci0000:00/0000:00:01.1/0000:01:00.0/0000:02:00.0/0000:03:00.0",
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"vram": 17163091968,
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"gtt": 16359088128,
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},
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"card2": {
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"realpath": "/sys/devices/pci0000:00/0000:00:01.2/0000:04:00.0/0000:05:00.0/0000:06:00.0",
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"vram": 17163091968,
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"gtt": 16359088128,
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},
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"card3": {
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"realpath": "/sys/devices/pci0000:00/0000:00:08.1/0000:1d:00.0",
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"vram": 536870912,
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"gtt": 16359088128,
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},
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}
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def install_fake_drm(monkeypatch, cards):
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files = {}
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realpaths = {}
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for card, values in cards.items():
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device_dir = model_management.os.path.join("/sys/class/drm", card, "device")
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files[model_management.os.path.join(device_dir, "vendor")] = values.get("vendor", "0x1002")
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files[model_management.os.path.join(device_dir, "mem_info_vram_total")] = str(values["vram"])
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files[model_management.os.path.join(device_dir, "mem_info_gtt_total")] = str(values["gtt"])
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realpaths[device_dir] = values["realpath"]
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monkeypatch.setattr(
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model_management.os,
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"listdir",
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lambda path: [*cards, "card1-DP-1"] if path == "/sys/class/drm" else [],
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)
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monkeypatch.setattr(model_management.os.path, "exists", lambda path: path in files)
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monkeypatch.setattr(model_management.os.path, "realpath", lambda path: realpaths.get(path, path))
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monkeypatch.setattr(
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builtins,
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"open",
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lambda path, *args, **kwargs: io.StringIO(files[str(path)]),
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)
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def properties(bus, *, integrated, domain=0, device=0):
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return SimpleNamespace(
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pci_domain_id=domain,
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pci_bus_id=bus,
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pci_device_id=device,
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is_integrated=int(integrated),
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)
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@pytest.fixture(autouse=True)
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def gpu_mode(monkeypatch):
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monkeypatch.setattr(model_management, "cpu_state", model_management.CPUState.GPU)
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monkeypatch.setattr(model_management, "is_amd", lambda: True)
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monkeypatch.setattr(model_management, "is_nvidia", lambda: False)
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def test_mixed_topology_maps_each_device_by_canonical_bdf(monkeypatch):
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install_fake_drm(monkeypatch, MIXED_TOPOLOGY)
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device_properties = {
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0: properties(3, integrated=False),
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1: properties(6, integrated=False),
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2: properties(29, integrated=True),
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}
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: device_properties[device.index],
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)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) == (
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17163091968,
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16359088128,
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)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 1)) == (
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17163091968,
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16359088128,
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)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 2)) == (
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536870912,
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16359088128,
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)
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assert model_management.is_integrated_gpu(torch.device("cuda", 0)) is False
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assert model_management.is_integrated_gpu(torch.device("cuda", 1)) is False
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assert model_management.is_integrated_gpu(torch.device("cuda", 2)) is True
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assert model_management.integrated_gpu_is_shared_heavy(torch.device("cuda", 0)) is False
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assert model_management.integrated_gpu_is_shared_heavy(torch.device("cuda", 1)) is False
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assert model_management.integrated_gpu_is_shared_heavy(torch.device("cuda", 2)) is True
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def test_dedicated_heavy_integrated_gpu_stays_non_shared(monkeypatch):
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install_fake_drm(monkeypatch, {"card1": MIXED_TOPOLOGY["card1"]})
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: properties(3, integrated=True),
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)
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device = torch.device("cuda", 0)
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assert model_management.is_integrated_gpu(device) is True
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assert model_management.integrated_gpu_is_shared_heavy(device) is False
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@pytest.mark.parametrize(
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("vram", "gtt", "expected"),
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[
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(1024, 1023, False),
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(1024, 1024, True),
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(1024, 1025, True),
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(0, 1024, True),
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],
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)
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def test_shared_heavy_threshold(monkeypatch, vram, gtt, expected):
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card = {**MIXED_TOPOLOGY["card3"], "vram": vram, "gtt": gtt}
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install_fake_drm(monkeypatch, {"card3": card})
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: properties(29, integrated=True),
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)
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assert model_management.integrated_gpu_is_shared_heavy(torch.device("cuda", 0)) is expected
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def test_full_domain_bus_device_bdf_is_matched(monkeypatch):
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card = {
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**MIXED_TOPOLOGY["card3"],
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"realpath": "/sys/devices/pci1234:00/1234:ab:1f.0",
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}
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install_fake_drm(monkeypatch, {"card3": card})
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: properties(0xAB, integrated=True, domain=0x1234, device=0x1F),
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)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) == (
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536870912,
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16359088128,
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)
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def test_multiple_candidates_without_bdf_match_do_not_fall_back(monkeypatch):
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install_fake_drm(monkeypatch, MIXED_TOPOLOGY)
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: properties(127, integrated=True),
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)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) is None
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def test_non_amd_drm_candidate_is_ignored(monkeypatch):
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cards = {
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"card1": MIXED_TOPOLOGY["card1"],
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"card2": {
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**MIXED_TOPOLOGY["card2"],
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"vendor": "0x10de",
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"vram": 1,
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"gtt": 2,
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},
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}
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install_fake_drm(monkeypatch, cards)
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: properties(6, integrated=False),
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)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) == (
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17163091968,
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16359088128,
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)
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def test_single_candidate_can_fall_back_when_pci_properties_are_unavailable(monkeypatch):
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install_fake_drm(monkeypatch, {"card3": MIXED_TOPOLOGY["card3"]})
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: (_ for _ in ()).throw(RuntimeError("properties unavailable")),
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)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) == (
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536870912,
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16359088128,
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)
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def test_unavailable_totals_default_integrated_gpu_to_shared(monkeypatch):
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install_fake_drm(monkeypatch, {})
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) is None
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assert model_management.integrated_gpu_is_shared_heavy(torch.device("cuda", 0)) is True
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def test_non_integer_totals_default_integrated_gpu_to_shared(monkeypatch):
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card = {**MIXED_TOPOLOGY["card3"], "vram": "invalid", "gtt": 16359088128}
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install_fake_drm(monkeypatch, {"card3": card})
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) is None
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assert model_management.integrated_gpu_is_shared_heavy(torch.device("cuda", 0)) is True
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def test_cpu_state_never_reports_integrated_gpu(monkeypatch):
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monkeypatch.setattr(model_management, "cpu_state", model_management.CPUState.CPU)
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monkeypatch.setattr(
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model_management.torch.cuda,
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"get_device_properties",
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lambda device: properties(29, integrated=True),
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)
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assert model_management.is_integrated_gpu(torch.device("cuda", 0)) is False
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def test_non_amd_backend_has_no_amd_totals(monkeypatch):
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install_fake_drm(monkeypatch, MIXED_TOPOLOGY)
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monkeypatch.setattr(model_management, "is_amd", lambda: False)
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assert model_management._amd_vram_gtt_totals(torch.device("cuda", 0)) is None
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