Files
olivv-cs-ComfyUI-FunPack/modules/loaders/vae/nodes.py
T
digital-garbageandClaude Opus 5 74671329f9 log: a severity, a source, and a message
[Log] Info: FunPack Diffusion Model Loader | flux.safetensors loaded, attention sage
    [Log] Alert: MiniMaxH3ImageToVideo node | no "first_image" input is connected
    [Log] Warning: FunPack LoRA Loader | style.safetensors is empty and will not load
    [Log] Critical: torch | cannot allocate 14 GB (3 GB free); the run will not start

The difference between the middle two is the one that matters. Alert is a
choice you may not have made on purpose. Warning is something that will NOT
do what its name says -- the level v4 needed and did not have, which is how
560 handlers came to swallow a failure and carry on, so a feature could be
switched on, do nothing, and never say so.

Info is not decoration either: "loaded on GPU using sage attention" is how
an attention setting that did nothing gets noticed months before the
pictures look wrong enough to investigate.

Every call site moved -- there is no note() left to be vague through -- and
the loaders now say what they actually loaded rather than only what they
were asked for. Records are kept in a bounded ring as well as printed, so a
long rental session cannot turn the log into a memory leak, and served at
/funpack/api/log so a person can read it somewhere other than a terminal
full of ComfyUI's own output. There is a page for it.

Also dropped the preflight this was traded for: min and max are already
declared and already enforced at both doors, and a second protection layer
around a check that exists is ceremony.

Two mistakes worth keeping: a log line reached into the model's shape to
describe it and could have failed the load it was only narrating; and both
new pages passed `children` to an element that takes `rows`, which the kit
accepted and silently dropped. It throws on an unknown element and not on an
unknown prop.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-29 17:09:33 +03:00

60 lines
2.2 KiB
Python

"""Loading a VAE, with an explicit dtype and a report of what happened.
Two differences from core's VAELoader, both carried over from v4 where they were
proven: the dtype is chosen rather than guessed, and a second output narrates
what actually loaded. Silent success that produced the wrong thing is the failure
mode these exist to remove.
"""
import comfy.sd
import comfy.utils
import folder_paths
import torch
from comfy_api.latest import io
from ..._core import log
# Chosen, not inferred. bf16 is the default because fp16 is a known failure on
# the AV VAEs, and fp32 decodes slowly for no visible gain.
DTYPES = {
"bfloat16": torch.bfloat16,
"float16": torch.float16,
"float32": torch.float32,
}
def vae_files():
# Empty is a legitimate state -- a fresh install has no models. Returning an
# empty list lets the node exist and say so, rather than failing to register.
return folder_paths.get_filename_list("vae")
class FunPackVAELoader(io.ComfyNode):
@classmethod
def define_schema(cls) -> io.Schema:
return io.Schema(
# Frozen once shipped: this string is stored as `class_type` in every
# saved workflow, so changing it silently breaks them.
node_id="FunPackVAELoader",
display_name="FunPack VAE Loader",
category="FunPack/Loaders",
description="Load a VAE with an explicit compute dtype.",
inputs=[
io.Combo.Input("vae_name", options=vae_files()),
io.Combo.Input("dtype", options=list(DTYPES), default="bfloat16"),
],
outputs=[
io.Vae.Output(display_name="vae"),
io.String.Output(display_name="status"),
],
)
@classmethod
def execute(cls, vae_name: str, dtype: str) -> io.NodeOutput:
path = folder_paths.get_full_path_or_raise("vae", vae_name)
state_dict = comfy.utils.load_torch_file(path)
vae = comfy.sd.VAE(sd=state_dict, dtype=DTYPES[dtype])
vae.throw_exception_if_invalid()
log.info("FunPack VAE Loader", f"{vae_name} loaded as {dtype}")
return io.NodeOutput(vae, f"{vae_name} loaded as {dtype}")