Refactor - intermediate step of Implementing MultiGPU node registration and class definition retrieval for custom nodes

This commit is contained in:
John Pollock
2024-12-30 07:54:57 -06:00
parent 0b3ba045c4
commit caee8716b6
+136 -97
View File
@@ -1,29 +1,103 @@
import time
import os
import ast
import copy
import torch
import comfy.model_management
import os
import importlib.util
import logging
from typing import Dict, Type
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logging.info("MultiGPU: Initialization started")
current_device = comfy.model_management.get_torch_device()
logging.info(f"MultiGPU: Initial device {current_device}")
def find_node_definition(module_path: str, node_name: str) -> Dict:
"""
Finds a specific node class definition by searching Python files in the given path.
"""
search_dir = os.path.join("custom_nodes", module_path)
if not os.path.exists(search_dir):
logging.info(f"MultiGPU: No custom_nodes directory {module_path}, skipping")
return None
py_files = []
for root, _, files in os.walk(search_dir):
for file in files:
if file.endswith('.py'):
py_files.append(os.path.join(root, file))
if not py_files:
return None
try:
for file_path in py_files:
with open(file_path, 'r', encoding='utf-8') as f:
tree = ast.parse(f.read())
def get_torch_device_patched():
if (
not torch.cuda.is_available()
or comfy.model_management.cpu_state == comfy.model_management.CPUState.CPU
or "cpu" in str(current_device).lower()
):
return torch.device("cpu")
return torch.device(current_device)
for node in ast.walk(tree):
if isinstance(node, ast.ClassDef) and node.name == node_name:
class_info = {
'input_types': None,
'return_types': None,
'function': None,
'category': None
}
comfy.model_management.get_torch_device = get_torch_device_patched
for item in node.body:
if isinstance(item, ast.FunctionDef) and item.name == 'INPUT_TYPES':
if any(d.id == 'classmethod' for d in item.decorator_list if isinstance(d, ast.Name)):
for stmt in item.body:
if isinstance(stmt, ast.Return):
try:
class_info['input_types'] = ast.literal_eval(stmt.value)
except:
pass
elif isinstance(item, ast.Assign):
for target in item.targets:
if isinstance(target, ast.Name):
try:
if target.id == 'RETURN_TYPES':
class_info['return_types'] = ast.literal_eval(item.value)
elif target.id == 'FUNCTION':
class_info['function'] = ast.literal_eval(item.value)
elif target.id == 'CATEGORY':
class_info['category'] = ast.literal_eval(item.value)
except:
pass
return class_info
except Exception as e:
logging.error(f"MultiGPU: Error scanning for {node_name}: {str(e)}")
return None
def create_multigpu_node(node_name: str, class_info: Dict) -> Type:
"""Creates a MultiGPU version of the node"""
class MultiGPUNode:
@classmethod
def INPUT_TYPES(cls):
inputs = copy.deepcopy(class_info['input_types'])
if inputs is None:
inputs = {"required": {}, "optional": {}}
elif "required" not in inputs:
inputs["required"] = {}
devices = ["cpu"] + [f"cuda:{i}" for i in range(torch.cuda.device_count())]
inputs["required"]["device"] = (devices,)
return inputs
RETURN_TYPES = class_info['return_types'] if class_info['return_types'] is not None else tuple()
FUNCTION = "override"
CATEGORY = "multigpu"
def override(self, *args, device="cpu", **kwargs):
global current_device
current_device = device
return args if isinstance(args, tuple) else (args,)
MultiGPUNode.__name__ = f"{node_name}MultiGPU"
return MultiGPUNode
def override_class(cls):
"""Creates a MultiGPU version of a node class that preserves original functionality."""
class NodeOverride(cls):
@classmethod
def INPUT_TYPES(s):
@@ -43,96 +117,61 @@ def override_class(cls):
return NodeOverride
def register_module(module_path, target_nodes):
def register_core_nodes(target_nodes: list):
"""Register MultiGPU versions of core ComfyUI nodes"""
try:
# For core nodes, skip module loading and just register from global mappings
if not module_path:
logging.info("MultiGPU: Starting core node registration")
from nodes import NODE_CLASS_MAPPINGS as GLOBAL_NODE_CLASS_MAPPINGS
for node in target_nodes:
if node in GLOBAL_NODE_CLASS_MAPPINGS:
NODE_CLASS_MAPPINGS[f"{node}MultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS[node])
logging.info(f"MultiGPU: Registered core node {node}")
else:
logging.info(f"MultiGPU: Core node {node} not found - this shouldn't happen!")
return
# For custom nodes, try to load module first
full_path = os.path.join("custom_nodes", module_path, "__init__.py")
logging.info(f"MultiGPU: Checking for module at {full_path}")
if not os.path.exists(full_path):
logging.info(f"MultiGPU: Module {module_path} not found - skipping")
return
logging.info(f"MultiGPU: Found {module_path}, attempting to load")
spec = importlib.util.spec_from_file_location(module_path, full_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
logging.info(f"MultiGPU: Executed {module_path} initialization")
from nodes import NODE_CLASS_MAPPINGS as GLOBAL_NODE_CLASS_MAPPINGS
logging.info(f"MultiGPU: Looking for {module_path} nodes in global mappings")
logging.info("MultiGPU: Processing core nodes")
for node in target_nodes:
if node in GLOBAL_NODE_CLASS_MAPPINGS:
NODE_CLASS_MAPPINGS[f"{node}MultiGPU"] = override_class(GLOBAL_NODE_CLASS_MAPPINGS[node])
logging.info(f"MultiGPU: Successfully wrapped {node}")
logging.info(f"MultiGPU: Registered {node}MultiGPU")
else:
logging.info(f"MultiGPU: Node {node} from {module_path} not found in global mappings")
logging.info(f"MultiGPU: Core node {node} not found")
except Exception as e:
logging.error(f"MultiGPU: Error processing core nodes: {str(e)}")
def register_module(module_path: str, target_nodes: list):
"""Register MultiGPU versions of custom nodes"""
try:
# Handle custom nodes
logging.info(f"MultiGPU: Processing module {module_path}")
search_dir = os.path.join("custom_nodes", module_path)
if not os.path.exists(search_dir):
logging.info(f"MultiGPU: Module directory {module_path} not found, skipping")
return
# List all Python files in the module once
py_files = []
for root, _, files in os.walk(search_dir):
for file in files:
if file.endswith('.py'):
py_files.append(os.path.basename(file))
if py_files:
logging.info(f"MultiGPU: Searching in {module_path}: {', '.join(sorted(py_files))}")
for node in target_nodes:
class_info = find_node_definition(module_path, node)
if class_info:
NODE_CLASS_MAPPINGS[f"{node}MultiGPU"] = create_multigpu_node(node, class_info)
logging.info(f"MultiGPU: Registered {node}MultiGPU")
except Exception as e:
logging.info(f"MultiGPU: Error processing {module_path}: {str(e)}")
logging.error(f"MultiGPU: Error in {module_path}: {str(e)}")
# Initialize
NODE_CLASS_MAPPINGS = {}
current_device = None
# Let's test just one new module at a time, starting with GGUF
logging.info("MultiGPU: Starting Core ComfyUI registration")
register_module("", [
"UNETLoader",
"VAELoader",
"CLIPLoader",
"DualCLIPLoader",
"TripleCLIPLoader",
"CheckpointLoaderSimple",
"ControlNetLoader"
])
# Register all modules
register_module("", ["UNETLoader", "VAELoader", "CLIPLoader", "DualCLIPLoader","TripleCLIPLoader", "CheckpointLoaderSimple", "ControlNetLoader"])
register_module("ComfyUI-GGUF", ["UnetLoaderGGUF", "UnetLoaderGGUFAdvanced", "CLIPLoaderGGUF","DualCLIPLoaderGGUF", "TripleCLIPLoaderGGUF"])
register_module("x-flux-comfyui", ["LoadFluxControlNet"])
register_module("ComfyUI-Florence2", ["Florence2ModelLoader", "DownloadAndLoadFlorence2Model"])
register_module("ComfyUI-LTXVideo", ["LTXVLoader"])
register_module("ComfyUI-MMAudio", [ "MMAudioFeatureUtilsLoader", "MMAudioModelLoader", "MMAudioSampler"])
register_module("ComfyUI_bitsandbytes_NF4", ["CheckpointLoaderNF4"])
logging.info("MultiGPU: Starting GGUF registration")
register_module("ComfyUI-GGUF", [
"UnetLoaderGGUF",
"UnetLoaderGGUFAdvanced",
"CLIPLoaderGGUF",
"DualCLIPLoaderGGUF",
"TripleCLIPLoaderGGUF"
])
logging.info("MultiGPU: Starting X-Flux ControlNet registration")
register_module("x-flux-comfyui", [
"LoadFluxControlNet"
])
logging.info("MultiGPU: Starting Florence2 registration")
register_module("ComfyUI-Florence2", [
"Florence2ModelLoader",
"DownloadAndLoadFlorence2Model"
])
logging.info("MultiGPU: Starting LTXVideo registration")
register_module("ComfyUI-LTXVideo", [
"LTXVLoader"
])
logging.info("MultiGPU: Starting MMAudio registration")
register_module("ComfyUI-MMAudio", [
"MMAudioFeatureUtilsLoader",
"MMAudioModelLoader",
"MMAudioSampler"
])
logging.info("MultiGPU: Starting NF4 registration")
register_module("ComfyUI_bnb_nf4_fp4_Loaders", [
"CheckpointLoaderNF4",
"UNETLoaderNF4"
])
logging.info(f"MultiGPU: Registration complete. Final mappings: {', '.join(NODE_CLASS_MAPPINGS.keys())}")
logging.info("MultiGPU: Registration complete")
logging.info(f"MultiGPU: Registered nodes: {', '.join(sorted(NODE_CLASS_MAPPINGS.keys()))}")