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Merge remote-tracking branch 'origin/master' into feat/cache-provider-api

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Deep Mehta
2026-03-03 15:11:17 -08:00
parent 04097e6902 f719a9d928
commit f5c5ff5c56
264 changed files with 20689 additions and 1608 deletions
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41
execution.py
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@@ -12,7 +12,11 @@ import asyncio
import torch
from comfy.cli_args import args
import comfy.memory_management
import comfy.model_management
import comfy_aimdo.model_vbar
from latent_preview import set_preview_method
import nodes
from comfy_execution.caching import (
@@ -515,7 +519,16 @@ async def execute(server, dynprompt, caches, current_item, extra_data, executed,
def pre_execute_cb(call_index):
# TODO - How to handle this with async functions without contextvars (which requires Python 3.12)?
GraphBuilder.set_default_prefix(unique_id, call_index, 0)
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)
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
unblock = execution_list.add_external_block(unique_id)
@@ -604,6 +617,8 @@ async def execute(server, dynprompt, caches, current_item, extra_data, executed,
logging.info("Memory summary: {}".format(comfy.model_management.debug_memory_summary()))
logging.error("Got an OOM, unloading all loaded models.")
comfy.model_management.unload_all_models()
elif isinstance(ex, RuntimeError) and ("mat1 and mat2 shapes" in str(ex)) and "Sampler" in class_type:
tips = "\n\nTIPS: If you have any \"Load CLIP\" or \"*CLIP Loader\" nodes in your workflow connected to this sampler node make sure the correct file(s) and type is selected."
error_details = {
"node_id": real_node_id,
@@ -1027,22 +1042,34 @@ async def validate_prompt(prompt_id, prompt, partial_execution_list: Union[list[
outputs = set()
for x in prompt:
if 'class_type' not in prompt[x]:
node_data = prompt[x]
node_title = node_data.get('_meta', {}).get('title')
error = {
"type": "invalid_prompt",
"message": "Cannot execute because a node is missing the class_type property.",
"type": "missing_node_type",
"message": f"Node '{node_title or f'ID #{x}'}' has no class_type. The workflow may be corrupted or a custom node is missing.",
"details": f"Node ID '#{x}'",
"extra_info": {}
"extra_info": {
"node_id": x,
"class_type": None,
"node_title": node_title
}
}
return (False, error, [], {})
class_type = prompt[x]['class_type']
class_ = nodes.NODE_CLASS_MAPPINGS.get(class_type, None)
if class_ is None:
node_data = prompt[x]
node_title = node_data.get('_meta', {}).get('title', class_type)
error = {
"type": "invalid_prompt",
"message": f"Cannot execute because node {class_type} does not exist.",
"type": "missing_node_type",
"message": f"Node '{node_title}' not found. The custom node may not be installed.",
"details": f"Node ID '#{x}'",
"extra_info": {}
"extra_info": {
"node_id": x,
"class_type": class_type,
"node_title": node_title
}
}
return (False, error, [], {})