Refactor and improve model_management code related to free memory.
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parent
499641ebf1
commit
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@ -1,6 +1,7 @@
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import psutil
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from enum import Enum
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from comfy.cli_args import args
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import torch
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class VRAMState(Enum):
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CPU = 0
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@ -32,19 +33,60 @@ if args.directml is not None:
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# torch_directml.disable_tiled_resources(True)
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lowvram_available = False #TODO: need to find a way to get free memory in directml before this can be enabled by default.
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try:
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import torch
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if directml_enabled:
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pass #TODO
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else:
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try:
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import intel_extension_for_pytorch as ipex
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if torch.xpu.is_available():
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xpu_available = True
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total_vram = torch.xpu.get_device_properties(torch.xpu.current_device()).total_memory / (1024 * 1024)
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except:
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total_vram = torch.cuda.mem_get_info(torch.cuda.current_device())[1] / (1024 * 1024)
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pass
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def get_torch_device():
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global xpu_available
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global directml_enabled
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if directml_enabled:
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global directml_device
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return directml_device
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if vram_state == VRAMState.MPS:
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return torch.device("mps")
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if vram_state == VRAMState.CPU:
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return torch.device("cpu")
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else:
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if xpu_available:
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return torch.device("xpu")
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else:
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return torch.device(torch.cuda.current_device())
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def get_total_memory(dev=None, torch_total_too=False):
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global xpu_available
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global directml_enabled
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if dev is None:
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dev = get_torch_device()
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if hasattr(dev, 'type') and (dev.type == 'cpu' or dev.type == 'mps'):
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mem_total = psutil.virtual_memory().total
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mem_total_torch = mem_total
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else:
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if directml_enabled:
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mem_total = 1024 * 1024 * 1024 #TODO
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mem_total_torch = mem_total
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elif xpu_available:
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mem_total = torch.xpu.get_device_properties(dev).total_memory
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mem_total_torch = mem_total
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else:
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stats = torch.cuda.memory_stats(dev)
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mem_reserved = stats['reserved_bytes.all.current']
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_, mem_total_cuda = torch.cuda.mem_get_info(dev)
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mem_total_torch = mem_reserved
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mem_total = mem_total_cuda
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if torch_total_too:
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return (mem_total, mem_total_torch)
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else:
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return mem_total
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total_vram = get_total_memory(get_torch_device()) / (1024 * 1024)
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total_ram = psutil.virtual_memory().total / (1024 * 1024)
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print("Total VRAM {:0.0f} MB, total RAM {:0.0f} MB".format(total_vram, total_ram))
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if not args.normalvram and not args.cpu:
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if lowvram_available and total_vram <= 4096:
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print("Trying to enable lowvram mode because your GPU seems to have 4GB or less. If you don't want this use: --normalvram")
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@ -52,8 +94,6 @@ try:
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elif total_vram > total_ram * 1.1 and total_vram > 14336:
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print("Enabling highvram mode because your GPU has more vram than your computer has ram. If you don't want this use: --normalvram")
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vram_state = VRAMState.HIGH_VRAM
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except:
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pass
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try:
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OOM_EXCEPTION = torch.cuda.OutOfMemoryError
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@ -128,29 +168,17 @@ if args.cpu:
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print(f"Set vram state to: {vram_state.name}")
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def get_torch_device():
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global xpu_available
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global directml_enabled
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if directml_enabled:
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global directml_device
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return directml_device
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if vram_state == VRAMState.MPS:
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return torch.device("mps")
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if vram_state == VRAMState.CPU:
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return torch.device("cpu")
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else:
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if xpu_available:
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return torch.device("xpu")
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else:
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return torch.cuda.current_device()
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def get_torch_device_name(device):
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if hasattr(device, 'type'):
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if device.type == "cuda":
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return "{} {}".format(device, torch.cuda.get_device_name(device))
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else:
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return "{}".format(device.type)
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else:
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return "CUDA {}: {}".format(device, torch.cuda.get_device_name(device))
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try:
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print("Using device:", get_torch_device_name(get_torch_device()))
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print("Device:", get_torch_device_name(get_torch_device()))
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except:
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print("Could not pick default device.")
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@ -308,33 +336,6 @@ def pytorch_attention_flash_attention():
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return True
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return False
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def get_total_memory(dev=None, torch_total_too=False):
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global xpu_available
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global directml_enabled
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if dev is None:
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dev = get_torch_device()
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if hasattr(dev, 'type') and (dev.type == 'cpu' or dev.type == 'mps'):
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mem_total = psutil.virtual_memory().total
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else:
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if directml_enabled:
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mem_total = 1024 * 1024 * 1024 #TODO
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mem_total_torch = mem_total
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elif xpu_available:
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mem_total = torch.xpu.get_device_properties(dev).total_memory
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mem_total_torch = mem_total
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else:
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stats = torch.cuda.memory_stats(dev)
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mem_reserved = stats['reserved_bytes.all.current']
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_, mem_total_cuda = torch.cuda.mem_get_info(dev)
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mem_total_torch = mem_reserved
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mem_total = mem_total_cuda
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if torch_total_too:
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return (mem_total, mem_total_torch)
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else:
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return mem_total
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def get_free_memory(dev=None, torch_free_too=False):
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global xpu_available
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global directml_enabled
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@ -7,7 +7,6 @@ import execution
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import uuid
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import json
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import glob
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import torch
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from PIL import Image
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from io import BytesIO
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@ -284,9 +283,8 @@ class PromptServer():
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@routes.get("/system_stats")
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async def get_queue(request):
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device_index = comfy.model_management.get_torch_device()
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device = torch.device(device_index)
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device_name = comfy.model_management.get_torch_device_name(device_index)
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device = comfy.model_management.get_torch_device()
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device_name = comfy.model_management.get_torch_device_name(device)
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vram_total, torch_vram_total = comfy.model_management.get_total_memory(device, torch_total_too=True)
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vram_free, torch_vram_free = comfy.model_management.get_free_memory(device, torch_free_too=True)
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system_stats = {
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