Files
studio/node_helpers.py
Hanzo Dev 5cf6ce2508 Rename all internal modules: comfy* → studio*
Complete module rename across 552 files:
- comfy/ → studio/
- comfy_extras/ → studio_extras/
- comfy_api/ → studio_api/
- comfy_api_nodes/ → studio_api_nodes/
- comfy_config/ → studio_config/
- comfy_execution/ → studio_execution/
- comfy/comfy_types/ → studio/node_types/
- comfyui_version.py → studio_version.py
- All test directories renamed
- All import statements updated
- All internal identifiers renamed (ComfyNodeABC → StudioNodeABC, etc.)
- All wire protocol types renamed (COMFY_* → STUDIO_*)
- No backward compatibility shims — clean break
- External pip packages preserved (comfyui-frontend-package, comfy-kitchen, etc.)
- 518 Python files syntax-validated, 0 errors
2026-02-23 12:49:38 -08:00

61 lines
1.6 KiB
Python

import hashlib
import torch
from studio.cli_args import args
from PIL import ImageFile, UnidentifiedImageError
def conditioning_set_values(conditioning, values={}, append=False):
c = []
for t in conditioning:
n = [t[0], t[1].copy()]
for k in values:
val = values[k]
if append:
old_val = n[1].get(k, None)
if old_val is not None:
val = old_val + val
n[1][k] = val
c.append(n)
return c
def pillow(fn, arg):
prev_value = None
try:
x = fn(arg)
except (OSError, UnidentifiedImageError, ValueError): #PIL issues #4472 and #2445, also fixes issue #3416
prev_value = ImageFile.LOAD_TRUNCATED_IMAGES
ImageFile.LOAD_TRUNCATED_IMAGES = True
x = fn(arg)
finally:
if prev_value is not None:
ImageFile.LOAD_TRUNCATED_IMAGES = prev_value
return x
def hasher():
hashfuncs = {
"md5": hashlib.md5,
"sha1": hashlib.sha1,
"sha256": hashlib.sha256,
"sha512": hashlib.sha512
}
return hashfuncs[args.default_hashing_function]
def string_to_torch_dtype(string):
if string == "fp32":
return torch.float32
if string == "fp16":
return torch.float16
if string == "bf16":
return torch.bfloat16
def image_alpha_fix(destination, source):
if destination.shape[-1] < source.shape[-1]:
source = source[...,:destination.shape[-1]]
elif destination.shape[-1] > source.shape[-1]:
destination = torch.nn.functional.pad(destination, (0, 1))
destination[..., -1] = 1.0
return destination, source