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Merge branch 'master' into dr-support-pip-cm

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Dr.Lt.Data 2025-09-08 07:44:18 +09:00
commit 8a2f805233
2 changed files with 27 additions and 8 deletions
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2
comfy/cli_args.py
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@ -151,7 +151,7 @@ class PerformanceFeature(enum.Enum):
CublasOps = "cublas_ops"
AutoTune = "autotune"
parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: fp16_accumulation fp8_matrix_mult cublas_ops")
parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: {}".format(" ".join(map(lambda c: c.value, PerformanceFeature))))
parser.add_argument("--mmap-torch-files", action="store_true", help="Use mmap when loading ckpt/pt files.")
parser.add_argument("--disable-mmap", action="store_true", help="Don't use mmap when loading safetensors.")

33
comfy/model_management.py
View File

@ -22,6 +22,7 @@ from enum import Enum
from comfy.cli_args import args, PerformanceFeature
import torch
import sys
import importlib
import platform
import weakref
import gc
@ -289,6 +290,21 @@ def is_amd():
return True
return False
def amd_min_version(device=None, min_rdna_version=0):
if not is_amd():
return False
arch = torch.cuda.get_device_properties(device).gcnArchName
if arch.startswith('gfx') and len(arch) == 7:
try:
cmp_rdna_version = int(arch[4]) + 2
except:
cmp_rdna_version = 0
if cmp_rdna_version >= min_rdna_version:
return True
return False
MIN_WEIGHT_MEMORY_RATIO = 0.4
if is_nvidia():
MIN_WEIGHT_MEMORY_RATIO = 0.0
@ -321,12 +337,13 @@ try:
logging.info("AMD arch: {}".format(arch))
logging.info("ROCm version: {}".format(rocm_version))
if args.use_split_cross_attention == False and args.use_quad_cross_attention == False:
if torch_version_numeric >= (2, 7): # works on 2.6 but doesn't actually seem to improve much
if any((a in arch) for a in ["gfx90a", "gfx942", "gfx1100", "gfx1101", "gfx1151"]): # TODO: more arches, TODO: gfx950
ENABLE_PYTORCH_ATTENTION = True
# if torch_version_numeric >= (2, 8):
# if any((a in arch) for a in ["gfx1201"]):
# ENABLE_PYTORCH_ATTENTION = True
if importlib.util.find_spec('triton') is not None: # AMD efficient attention implementation depends on triton. TODO: better way of detecting if it's compiled in or not.
if torch_version_numeric >= (2, 7): # works on 2.6 but doesn't actually seem to improve much
if any((a in arch) for a in ["gfx90a", "gfx942", "gfx1100", "gfx1101", "gfx1151"]): # TODO: more arches, TODO: gfx950
ENABLE_PYTORCH_ATTENTION = True
# if torch_version_numeric >= (2, 8):
# if any((a in arch) for a in ["gfx1201"]):
# ENABLE_PYTORCH_ATTENTION = True
if torch_version_numeric >= (2, 7) and rocm_version >= (6, 4):
if any((a in arch) for a in ["gfx1201", "gfx942", "gfx950"]): # TODO: more arches
SUPPORT_FP8_OPS = True
@ -905,7 +922,9 @@ def vae_dtype(device=None, allowed_dtypes=[]):
# NOTE: bfloat16 seems to work on AMD for the VAE but is extremely slow in some cases compared to fp32
# slowness still a problem on pytorch nightly 2.9.0.dev20250720+rocm6.4 tested on RDNA3
if d == torch.bfloat16 and (not is_amd()) and should_use_bf16(device):
# also a problem on RDNA4 except fp32 is also slow there.
# This is due to large bf16 convolutions being extremely slow.
if d == torch.bfloat16 and ((not is_amd()) or amd_min_version(device, min_rdna_version=4)) and should_use_bf16(device):
return d
return torch.float32