From 0bfb936ab46377d1d5faf8c46ff19d0c6f91a04e Mon Sep 17 00:00:00 2001 From: rattus <46076784+rattus128@users.noreply.github.com> Date: Sat, 21 Feb 2026 10:52:57 -0800 Subject: [PATCH] comfy-aimdo 0.2 - Improved pytorch allocator integration (#12557) Integrate comfy-aimdo 0.2 which takes a different approach to installing the memory allocator hook. Instead of using the complicated and buggy pytorch MemPool+CudaPluggableAlloctor, cuda is directly hooked making the process much more transparent to both comfy and pytorch. As far as pytorch knows, aimdo doesnt exist anymore, and just operates behind the scenes. Remove all the mempool setup stuff for dynamic_vram and bump the comfy-aimdo version. Remove the allocator object from memory_management and demote its use as an enablment check to a boolean flag. Comfy-aimdo 0.2 also support the pytorch cuda async allocator, so remove the dynamic_vram based force disablement of cuda_malloc and just go back to the old settings of allocators based on command line input. --- comfy/memory_management.py | 2 +- comfy/model_management.py | 3 +-- comfy/utils.py | 2 +- cuda_malloc.py | 8 +------- execution.py | 22 ++++++++-------------- main.py | 11 +++++------ requirements.txt | 2 +- 7 files changed, 18 insertions(+), 32 deletions(-) diff --git a/comfy/memory_management.py b/comfy/memory_management.py index 858bd4cc..0b7da285 100644 --- a/comfy/memory_management.py +++ b/comfy/memory_management.py @@ -78,4 +78,4 @@ def interpret_gathered_like(tensors, gathered): return dest_views -aimdo_allocator = None +aimdo_enabled = False diff --git a/comfy/model_management.py b/comfy/model_management.py index 38c3e482..1fe56a62 100644 --- a/comfy/model_management.py +++ b/comfy/model_management.py @@ -836,7 +836,7 @@ def unet_inital_load_device(parameters, dtype): mem_dev = get_free_memory(torch_dev) mem_cpu = get_free_memory(cpu_dev) - if mem_dev > mem_cpu and model_size < mem_dev and comfy.memory_management.aimdo_allocator is None: + if mem_dev > mem_cpu and model_size < mem_dev and comfy.memory_management.aimdo_enabled: return torch_dev else: return cpu_dev @@ -1121,7 +1121,6 @@ def get_cast_buffer(offload_stream, device, size, ref): synchronize() del STREAM_CAST_BUFFERS[offload_stream] del cast_buffer - #FIXME: This doesn't work in Aimdo because mempool cant clear cache soft_empty_cache() with wf_context: cast_buffer = torch.empty((size), dtype=torch.int8, device=device) diff --git a/comfy/utils.py b/comfy/utils.py index 17443b4c..5fe66ecd 100644 --- a/comfy/utils.py +++ b/comfy/utils.py @@ -1154,7 +1154,7 @@ def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, upscale_am return tiled_scale_multidim(samples, function, (tile_y, tile_x), overlap=overlap, upscale_amount=upscale_amount, out_channels=out_channels, output_device=output_device, pbar=pbar) def model_trange(*args, **kwargs): - if comfy.memory_management.aimdo_allocator is None: + if not comfy.memory_management.aimdo_enabled: return trange(*args, **kwargs) pbar = trange(*args, **kwargs, smoothing=1.0) diff --git a/cuda_malloc.py b/cuda_malloc.py index b2182df3..f7651981 100644 --- a/cuda_malloc.py +++ b/cuda_malloc.py @@ -1,10 +1,8 @@ import os import importlib.util -from comfy.cli_args import args, PerformanceFeature, enables_dynamic_vram +from comfy.cli_args import args, PerformanceFeature import subprocess -import comfy_aimdo.control - #Can't use pytorch to get the GPU names because the cuda malloc has to be set before the first import. def get_gpu_names(): if os.name == 'nt': @@ -87,10 +85,6 @@ if not args.cuda_malloc: except: pass -if enables_dynamic_vram() and comfy_aimdo.control.init(): - args.cuda_malloc = False - os.environ['PYTORCH_CUDA_ALLOC_CONF'] = "" - if args.disable_cuda_malloc: args.cuda_malloc = False diff --git a/execution.py b/execution.py index f549a2f0..75b02189 100644 --- a/execution.py +++ b/execution.py @@ -9,7 +9,6 @@ import traceback from enum import Enum from typing import List, Literal, NamedTuple, Optional, Union import asyncio -from contextlib import nullcontext import torch @@ -521,19 +520,14 @@ async def execute(server, dynprompt, caches, current_item, extra_data, executed, # TODO - How to handle this with async functions without contextvars (which requires Python 3.12)? GraphBuilder.set_default_prefix(unique_id, call_index, 0) - #Do comfy_aimdo mempool chunking here on the per-node level. Multi-model workflows - #will cause all sorts of incompatible memory shapes to fragment the pytorch alloc - #that we just want to cull out each model run. - allocator = comfy.memory_management.aimdo_allocator - with nullcontext() if allocator is None else torch.cuda.use_mem_pool(torch.cuda.MemPool(allocator.allocator())): - try: - output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data) - finally: - if allocator is not None: - if args.verbose == "DEBUG": - comfy_aimdo.model_vbar.vbars_analyze() - comfy.model_management.reset_cast_buffers() - comfy_aimdo.model_vbar.vbars_reset_watermark_limits() + try: + output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data) + finally: + if comfy.memory_management.aimdo_enabled: + if args.verbose == "DEBUG": + comfy_aimdo.control.analyze() + comfy.model_management.reset_cast_buffers() + comfy_aimdo.model_vbar.vbars_reset_watermark_limits() if has_pending_tasks: pending_async_nodes[unique_id] = output_data diff --git a/main.py b/main.py index 92d705b4..39e605de 100644 --- a/main.py +++ b/main.py @@ -173,6 +173,10 @@ import gc if 'torch' in sys.modules: logging.warning("WARNING: Potential Error in code: Torch already imported, torch should never be imported before this point.") +import comfy_aimdo.control + +if enables_dynamic_vram(): + comfy_aimdo.control.init() import comfy.utils @@ -188,13 +192,9 @@ import hook_breaker_ac10a0 import comfy.memory_management import comfy.model_patcher -import comfy_aimdo.control -import comfy_aimdo.torch - if enables_dynamic_vram(): if comfy.model_management.torch_version_numeric < (2, 8): logging.warning("Unsupported Pytorch detected. DynamicVRAM support requires Pytorch version 2.8 or later. Falling back to legacy ModelPatcher. VRAM estimates may be unreliable especially on Windows") - comfy.memory_management.aimdo_allocator = None elif comfy_aimdo.control.init_device(comfy.model_management.get_torch_device().index): if args.verbose == 'DEBUG': comfy_aimdo.control.set_log_debug() @@ -208,11 +208,10 @@ if enables_dynamic_vram(): comfy_aimdo.control.set_log_info() comfy.model_patcher.CoreModelPatcher = comfy.model_patcher.ModelPatcherDynamic - comfy.memory_management.aimdo_allocator = comfy_aimdo.torch.get_torch_allocator() + comfy.memory_management.aimdo_enabled = True logging.info("DynamicVRAM support detected and enabled") else: logging.warning("No working comfy-aimdo install detected. DynamicVRAM support disabled. Falling back to legacy ModelPatcher. VRAM estimates may be unreliable especially on Windows") - comfy.memory_management.aimdo_allocator = None def cuda_malloc_warning(): diff --git a/requirements.txt b/requirements.txt index 3a9bfde4..8fbb0dbd 100644 --- a/requirements.txt +++ b/requirements.txt @@ -22,7 +22,7 @@ alembic SQLAlchemy av>=14.2.0 comfy-kitchen>=0.2.7 -comfy-aimdo>=0.1.8 +comfy-aimdo>=0.2.0 requests #non essential dependencies: