changed methodology (again) to run their code and then scan their LOCAL dict, not the global dict. This will work and be robust I strongly believe
Still too much new code, but we'll slim it down later
This commit is contained in:
John Pollock
+121
-138
@@ -1,107 +1,42 @@
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import os
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import ast
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import time
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import copy
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import torch
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import comfy.model_management
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import os
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import importlib.util
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import logging
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from typing import Dict, Type
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##############################################################################
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# INITIAL SETUP
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##############################################################################
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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logging.info("MultiGPU: Initialization started")
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def find_node_definition(module_path: str, node_name: str) -> Dict:
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"""
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Finds a specific node class definition by searching Python files in the given path.
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"""
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search_dir = os.path.join("custom_nodes", module_path)
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if not os.path.exists(search_dir):
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logging.info(f"MultiGPU: No custom_nodes directory {module_path}, skipping")
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return None
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py_files = []
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for root, _, files in os.walk(search_dir):
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for file in files:
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if file.endswith('.py'):
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py_files.append(os.path.join(root, file))
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if not py_files:
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return None
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try:
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for file_path in py_files:
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with open(file_path, 'r', encoding='utf-8') as f:
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tree = ast.parse(f.read())
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current_device = comfy.model_management.get_torch_device()
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logging.info(f"MultiGPU: Initial device {current_device}")
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for node in ast.walk(tree):
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if isinstance(node, ast.ClassDef) and node.name == node_name:
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class_info = {
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'input_types': None,
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'return_types': None,
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'function': None,
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'category': None
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}
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def get_torch_device_patched():
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if (
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not torch.cuda.is_available()
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or comfy.model_management.cpu_state == comfy.model_management.CPUState.CPU
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or "cpu" in str(current_device).lower()
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):
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return torch.device("cpu")
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return torch.device(current_device)
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for item in node.body:
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if isinstance(item, ast.FunctionDef) and item.name == 'INPUT_TYPES':
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if any(d.id == 'classmethod' for d in item.decorator_list if isinstance(d, ast.Name)):
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for stmt in item.body:
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if isinstance(stmt, ast.Return):
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try:
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class_info['input_types'] = ast.literal_eval(stmt.value)
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except:
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pass
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elif isinstance(item, ast.Assign):
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for target in item.targets:
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if isinstance(target, ast.Name):
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try:
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if target.id == 'RETURN_TYPES':
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class_info['return_types'] = ast.literal_eval(item.value)
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elif target.id == 'FUNCTION':
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class_info['function'] = ast.literal_eval(item.value)
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elif target.id == 'CATEGORY':
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class_info['category'] = ast.literal_eval(item.value)
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except:
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pass
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return class_info
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except Exception as e:
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logging.error(f"MultiGPU: Error scanning for {node_name}: {str(e)}")
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return None
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def create_multigpu_node(node_name: str, class_info: Dict) -> Type:
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"""Creates a MultiGPU version of the node"""
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class MultiGPUNode:
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@classmethod
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def INPUT_TYPES(cls):
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inputs = copy.deepcopy(class_info['input_types'])
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if inputs is None:
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inputs = {"required": {}, "optional": {}}
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elif "required" not in inputs:
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inputs["required"] = {}
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devices = ["cpu"] + [f"cuda:{i}" for i in range(torch.cuda.device_count())]
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inputs["required"]["device"] = (devices,)
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return inputs
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RETURN_TYPES = class_info['return_types'] if class_info['return_types'] is not None else tuple()
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FUNCTION = "override"
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CATEGORY = "multigpu"
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def override(self, *args, device="cpu", **kwargs):
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global current_device
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current_device = device
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return args if isinstance(args, tuple) else (args,)
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MultiGPUNode.__name__ = f"{node_name}MultiGPU"
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return MultiGPUNode
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comfy.model_management.get_torch_device = get_torch_device_patched
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##############################################################################
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# OVERRIDE CLASS
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##############################################################################
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def override_class(cls):
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"""Creates a MultiGPU version of a node class that preserves original functionality."""
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class NodeOverride(cls):
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@classmethod
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def INPUT_TYPES(s):
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inputs = copy.deepcopy(cls.INPUT_TYPES())
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# In case some node forgot "required"
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if "required" not in inputs:
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inputs["required"] = {}
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devices = ["cpu"] + [f"cuda:{i}" for i in range(torch.cuda.device_count())]
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inputs["required"]["device"] = (devices,)
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return inputs
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@@ -109,69 +44,117 @@ def override_class(cls):
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CATEGORY = "multigpu"
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FUNCTION = "override"
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def override(self, *args, device, **kwargs):
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def override(self, *args, device="cpu", **kwargs):
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global current_device
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current_device = device
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fn = getattr(super(), cls.FUNCTION)
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return fn(*args, **kwargs)
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return NodeOverride
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def register_core_nodes(target_nodes: list):
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"""Register MultiGPU versions of core ComfyUI nodes"""
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##############################################################################
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# OUR LOCAL MAPPING OF MULTIGPU OVERRIDE NODES
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# (No strict reason it has to be before the function defs, but it's typical.)
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##############################################################################
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NODE_CLASS_MAPPINGS = {}
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##############################################################################
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# PART 1: CORE NODES
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##############################################################################
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def register_core_nodes(core_node_names):
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"""
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Uses ComfyUI's GLOBAL_NODE_CLASS_MAPPINGS to wrap core nodes.
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"""
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logging.info("MultiGPU: Starting core node registration")
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try:
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from nodes import NODE_CLASS_MAPPINGS as GLOBAL_NODE_CLASS_MAPPINGS
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logging.info("MultiGPU: Processing core nodes")
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for node in target_nodes:
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if node in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS[f"{node}MultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS[node])
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logging.info(f"MultiGPU: Registered {node}MultiGPU")
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else:
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logging.info(f"MultiGPU: Core node {node} not found")
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except Exception as e:
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logging.error(f"MultiGPU: Error processing core nodes: {str(e)}")
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except ImportError as e:
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logging.error(f"MultiGPU: Could not import ComfyUI global node mappings: {e}")
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return
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for node in core_node_names:
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if node in GLOBAL_NODE_CLASS_MAPPINGS:
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NODE_CLASS_MAPPINGS[f"{node}MultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS[node])
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logging.info(f"MultiGPU: Registered core node {node}")
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else:
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logging.info(f"MultiGPU: Core node '{node}' not found in ComfyUI global mappings")
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##############################################################################
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# PART 2: CUSTOM NODES (LOCAL DICTIONARY APPROACH, with extra debug logs)
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##############################################################################
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def register_module(module_path: str, target_nodes: list, local_map_name="NODE_CLASS_MAPPINGS"):
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"""
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1) Load custom_nodes/<module_path>/__init__.py via importlib
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2) Grab the dictionary named `local_map_name` (default: 'NODE_CLASS_MAPPINGS') from that module
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3) For each node in target_nodes, if found in that local dictionary, wrap it
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4) No fallback to ComfyUI's global mappings
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"""
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base_dir = os.path.join("custom_nodes", module_path)
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init_file = os.path.join(base_dir, "__init__.py")
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logging.info(f"MultiGPU: Checking custom node module at: {init_file}")
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if not os.path.exists(init_file):
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logging.info(f"MultiGPU: Module {module_path} not found or missing __init__.py, skipping.")
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return
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def register_module(module_path: str, target_nodes: list):
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"""Register MultiGPU versions of custom nodes"""
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try:
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# Handle custom nodes
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logging.info(f"MultiGPU: Processing module {module_path}")
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search_dir = os.path.join("custom_nodes", module_path)
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if not os.path.exists(search_dir):
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logging.info(f"MultiGPU: Module directory {module_path} not found, skipping")
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return
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# List all Python files in the module once
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py_files = []
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for root, _, files in os.walk(search_dir):
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for file in files:
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if file.endswith('.py'):
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py_files.append(os.path.basename(file))
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if py_files:
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logging.info(f"MultiGPU: Searching in {module_path}: {', '.join(sorted(py_files))}")
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for node in target_nodes:
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class_info = find_node_definition(module_path, node)
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if class_info:
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NODE_CLASS_MAPPINGS[f"{node}MultiGPU"] = create_multigpu_node(node, class_info)
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logging.info(f"MultiGPU: Registered {node}MultiGPU")
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logging.info(f"MultiGPU: Found {module_path}, loading local dictionary from {init_file}")
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spec = importlib.util.spec_from_file_location(module_path, init_file)
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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logging.info(f"MultiGPU: Executed {module_path} initialization")
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except Exception as e:
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logging.error(f"MultiGPU: Error in {module_path}: {str(e)}")
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logging.error(f"MultiGPU: Error loading {module_path}: {e}")
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return
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# Initialize
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NODE_CLASS_MAPPINGS = {}
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current_device = None
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# Grab that module's local dictionary (e.g. NODE_CLASS_MAPPINGS)
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local_map = getattr(module, local_map_name, None)
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if not local_map:
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logging.info(f"MultiGPU: {module_path} has no '{local_map_name}' dictionary, skipping override.")
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return
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# DEBUG: Show everything this node map provides
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all_defined_nodes = list(local_map.keys())
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logging.info(f"MultiGPU: {module_path} local dict keys: {all_defined_nodes}")
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# Wrap each node we want
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for node in target_nodes:
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if node in local_map:
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mgpu_class = override_class(local_map[node])
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NODE_CLASS_MAPPINGS[f"{node}MultiGPU"] = mgpu_class
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logging.info(f"MultiGPU: Successfully wrapped {node} from {module_path}")
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else:
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logging.info(f"MultiGPU: Node '{node}' not found in {module_path}'s local dictionary")
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##############################################################################
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# EXAMPLE USAGE
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##############################################################################
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# 1) CORE NODES
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register_core_nodes([
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"UNETLoader",
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"VAELoader",
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"CLIPLoader",
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"DualCLIPLoader",
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"TripleCLIPLoader",
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"CheckpointLoaderSimple",
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"ControlNetLoader",
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])
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# 2) CUSTOM NODES
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register_module("ComfyUI-GGUF", [
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"UnetLoaderGGUF",
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"UnetLoaderGGUFAdvanced",
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"CLIPLoaderGGUF",
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"DualCLIPLoaderGGUF",
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"TripleCLIPLoaderGGUF",
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])
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# Register all modules
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register_module("", ["UNETLoader", "VAELoader", "CLIPLoader", "DualCLIPLoader","TripleCLIPLoader", "CheckpointLoaderSimple", "ControlNetLoader"])
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register_module("ComfyUI-GGUF", ["UnetLoaderGGUF", "UnetLoaderGGUFAdvanced", "CLIPLoaderGGUF","DualCLIPLoaderGGUF", "TripleCLIPLoaderGGUF"])
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register_module("x-flux-comfyui", ["LoadFluxControlNet"])
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register_module("ComfyUI-Florence2", ["Florence2ModelLoader", "DownloadAndLoadFlorence2Model"])
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register_module("ComfyUI-LTXVideo", ["LTXVLoader"])
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register_module("ComfyUI-MMAudio", [ "MMAudioFeatureUtilsLoader", "MMAudioModelLoader", "MMAudioSampler"])
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register_module("ComfyUI-MMAudio", ["MMAudioFeatureUtilsLoader", "MMAudioModelLoader", "MMAudioSampler"])
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register_module("ComfyUI_bitsandbytes_NF4", ["CheckpointLoaderNF4"])
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logging.info("MultiGPU: Registration complete")
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logging.info(f"MultiGPU: Registered nodes: {', '.join(sorted(NODE_CLASS_MAPPINGS.keys()))}")
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logging.info("MultiGPU: Registration complete.")
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logging.info("MultiGPU: Final mappings: " + ", ".join(sorted(NODE_CLASS_MAPPINGS.keys())))
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