Initial commit
This commit is contained in:
TK3R
@@ -0,0 +1,39 @@
|
||||
name: Lint
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [ main ]
|
||||
pull_request:
|
||||
branches: [ main ]
|
||||
|
||||
jobs:
|
||||
lint:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12", "3.13"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install flake8 black
|
||||
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
|
||||
|
||||
- name: Lint with flake8
|
||||
run: |
|
||||
# stop the build if there are Python syntax errors or undefined names
|
||||
flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
|
||||
# exit-zero treats all errors as warnings
|
||||
flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
|
||||
|
||||
- name: Check formatting with black
|
||||
run: |
|
||||
black --check .
|
||||
+147
@@ -0,0 +1,147 @@
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.pyc
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
pip-wheel-metadata/
|
||||
share/python-wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# PyInstaller
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
.python-version
|
||||
|
||||
# pipenv
|
||||
Pipfile.lock
|
||||
|
||||
# PEP 582
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# VS Code
|
||||
.vscode/
|
||||
*.code-workspace
|
||||
|
||||
# macOS
|
||||
.DS_Store
|
||||
.AppleDouble
|
||||
.LSOverride
|
||||
|
||||
# Windows
|
||||
Thumbs.db
|
||||
Thumbs.db:encryptable
|
||||
ehthumbs.db
|
||||
ehthumbs_vista.db
|
||||
*.stackdump
|
||||
[Dd]esktop.ini
|
||||
$RECYCLE.BIN/
|
||||
*.lnk
|
||||
|
||||
# ComfyUI specific
|
||||
web/extensions/
|
||||
temp/
|
||||
@@ -0,0 +1,67 @@
|
||||
# Contributing to ComfyUI TK3R Extensions
|
||||
|
||||
Thank you for considering contributing to ComfyUI TK3R Extensions! This document provides guidelines for contributing to the project.
|
||||
|
||||
## How to Contribute
|
||||
|
||||
### Reporting Bugs
|
||||
|
||||
If you find a bug, please open an issue on GitHub with:
|
||||
- A clear, descriptive title
|
||||
- Steps to reproduce the issue
|
||||
- Expected behavior
|
||||
- Actual behavior
|
||||
- Your environment (OS, Python version, ComfyUI version)
|
||||
- Screenshots if applicable
|
||||
|
||||
### Suggesting Enhancements
|
||||
|
||||
Enhancement suggestions are welcome! Please open an issue with:
|
||||
- A clear, descriptive title
|
||||
- Detailed description of the proposed functionality
|
||||
- Why this enhancement would be useful
|
||||
- Examples of how it would be used
|
||||
|
||||
### Pull Requests
|
||||
|
||||
1. Fork the repository
|
||||
2. Create a new branch (`git checkout -b feature/amazing-feature`)
|
||||
3. Make your changes
|
||||
4. Ensure your code follows the existing style
|
||||
5. Test your changes thoroughly
|
||||
6. Commit your changes (`git commit -m 'Add amazing feature'`)
|
||||
7. Push to the branch (`git push origin feature/amazing-feature`)
|
||||
8. Open a Pull Request
|
||||
|
||||
### Code Style
|
||||
|
||||
- Follow PEP 8 guidelines
|
||||
- Use meaningful variable and function names
|
||||
- Add comments for complex logic
|
||||
- Include docstrings for functions and classes
|
||||
- Keep functions focused and concise
|
||||
|
||||
### Testing
|
||||
|
||||
- Test your changes with different ComfyUI workflows
|
||||
- Ensure backward compatibility when possible
|
||||
- Document any breaking changes clearly
|
||||
|
||||
### Documentation
|
||||
|
||||
- Update the README.md if you add new features
|
||||
- Add usage examples for new nodes
|
||||
- Update the changelog
|
||||
|
||||
## Code of Conduct
|
||||
|
||||
- Be respectful and constructive
|
||||
- Welcome newcomers and help them learn
|
||||
- Focus on what is best for the community
|
||||
- Show empathy towards other community members
|
||||
|
||||
## Questions?
|
||||
|
||||
Feel free to open an issue for questions or join the discussion in existing issues.
|
||||
|
||||
Thank you for contributing! 🎉
|
||||
@@ -0,0 +1,674 @@
|
||||
GNU GENERAL PUBLIC LICENSE
|
||||
Version 3, 29 June 2007
|
||||
|
||||
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
|
||||
Everyone is permitted to copy and distribute verbatim copies
|
||||
of this license document, but changing it is not allowed.
|
||||
|
||||
Preamble
|
||||
|
||||
The GNU General Public License is a free, copyleft license for
|
||||
software and other kinds of works.
|
||||
|
||||
The licenses for most software and other practical works are designed
|
||||
to take away your freedom to share and change the works. By contrast,
|
||||
the GNU General Public License is intended to guarantee your freedom to
|
||||
share and change all versions of a program--to make sure it remains free
|
||||
software for all its users. We, the Free Software Foundation, use the
|
||||
GNU General Public License for most of our software; it applies also to
|
||||
any other work released this way by its authors. You can apply it to
|
||||
your programs, too.
|
||||
|
||||
When we speak of free software, we are referring to freedom, not
|
||||
price. Our General Public Licenses are designed to make sure that you
|
||||
have the freedom to distribute copies of free software (and charge for
|
||||
them if you wish), that you receive source code or can get it if you
|
||||
want it, that you can change the software or use pieces of it in new
|
||||
free programs, and that you know you can do these things.
|
||||
|
||||
To protect your rights, we need to prevent others from denying you
|
||||
these rights or asking you to surrender the rights. Therefore, you have
|
||||
certain responsibilities if you distribute copies of the software, or if
|
||||
you modify it: responsibilities to respect the freedom of others.
|
||||
|
||||
For example, if you distribute copies of such a program, whether
|
||||
gratis or for a fee, you must pass on to the recipients the same
|
||||
freedoms that you received. You must make sure that they, too, receive
|
||||
or can get the source code. And you must show them these terms so they
|
||||
know their rights.
|
||||
|
||||
Developers that use the GNU GPL protect your rights with two steps:
|
||||
(1) assert copyright on the software, and (2) offer you this License
|
||||
giving you legal permission to copy, distribute and/or modify it.
|
||||
|
||||
For the developers' and authors' protection, the GPL clearly explains
|
||||
that there is no warranty for this free software. For both users' and
|
||||
authors' sake, the GPL requires that modified versions be marked as
|
||||
changed, so that their problems will not be attributed erroneously to
|
||||
authors of previous versions.
|
||||
|
||||
Some devices are designed to deny users access to install or run
|
||||
modified versions of the software inside them, although the manufacturer
|
||||
can do so. This is fundamentally incompatible with the aim of
|
||||
protecting users' freedom to change the software. The systematic
|
||||
pattern of such abuse occurs in the area of products for individuals to
|
||||
use, which is precisely where it is most unacceptable. Therefore, we
|
||||
have designed this version of the GPL to prohibit the practice for those
|
||||
products. If such problems arise substantially in other domains, we
|
||||
stand ready to extend this provision to those domains in future versions
|
||||
of the GPL, as needed to protect the freedom of users.
|
||||
|
||||
Finally, every program is threatened constantly by software patents.
|
||||
States should not allow patents to restrict development and use of
|
||||
software on general-purpose computers, but in those that do, we wish to
|
||||
avoid the special danger that patents applied to a free program could
|
||||
make it effectively proprietary. To prevent this, the GPL assures that
|
||||
patents cannot be used to render the program non-free.
|
||||
|
||||
The precise terms and conditions for copying, distribution and
|
||||
modification follow.
|
||||
|
||||
TERMS AND CONDITIONS
|
||||
|
||||
0. Definitions.
|
||||
|
||||
"This License" refers to version 3 of the GNU General Public License.
|
||||
|
||||
"Copyright" also means copyright-like laws that apply to other kinds of
|
||||
works, such as semiconductor masks.
|
||||
|
||||
"The Program" refers to any copyrightable work licensed under this
|
||||
License. Each licensee is addressed as "you". "Licensees" and
|
||||
"recipients" may be individuals or organizations.
|
||||
|
||||
To "modify" a work means to copy from or adapt all or part of the work
|
||||
in a fashion requiring copyright permission, other than the making of an
|
||||
exact copy. The resulting work is called a "modified version" of the
|
||||
earlier work or a work "based on" the earlier work.
|
||||
|
||||
A "covered work" means either the unmodified Program or a work based
|
||||
on the Program.
|
||||
|
||||
To "propagate" a work means to do anything with it that, without
|
||||
permission, would make you directly or secondarily liable for
|
||||
infringement under applicable copyright law, except executing it on a
|
||||
computer or modifying a private copy. Propagation includes copying,
|
||||
distribution (with or without modification), making available to the
|
||||
public, and in some countries other activities as well.
|
||||
|
||||
To "convey" a work means any kind of propagation that enables other
|
||||
parties to make or receive copies. Mere interaction with a user through
|
||||
a computer network, with no transfer of a copy, is not conveying.
|
||||
|
||||
An interactive user interface displays "Appropriate Legal Notices"
|
||||
to the extent that it includes a convenient and prominently visible
|
||||
feature that (1) displays an appropriate copyright notice, and (2)
|
||||
tells the user that there is no warranty for the work (except to the
|
||||
extent that warranties are provided), that licensees may convey the
|
||||
work under this License, and how to view a copy of this License. If
|
||||
the interface presents a list of user commands or options, such as a
|
||||
menu, a prominent item in the list meets this criterion.
|
||||
|
||||
1. Source Code.
|
||||
|
||||
The "source code" for a work means the preferred form of the work
|
||||
for making modifications to it. "Object code" means any non-source
|
||||
form of a work.
|
||||
|
||||
A "Standard Interface" means an interface that either is an official
|
||||
standard defined by a recognized standards body, or, in the case of
|
||||
interfaces specified for a particular programming language, one that
|
||||
is widely used among developers working in that language.
|
||||
|
||||
The "System Libraries" of an executable work include anything, other
|
||||
than the work as a whole, that (a) is included in the normal form of
|
||||
packaging a Major Component, but which is not part of that Major
|
||||
Component, and (b) serves only to enable use of the work with that
|
||||
Major Component, or to implement a Standard Interface for which an
|
||||
implementation is available to the public in source code form. A
|
||||
"Major Component", in this context, means a major essential component
|
||||
(kernel, window system, and so on) of the specific operating system
|
||||
(if any) on which the executable work runs, or a compiler used to
|
||||
produce the work, or an object code interpreter used to run it.
|
||||
|
||||
The "Corresponding Source" for a work in object code form means all
|
||||
the source code needed to generate, install, and (for an executable
|
||||
work) run the object code and to modify the work, including scripts to
|
||||
control those activities. However, it does not include the work's
|
||||
System Libraries, or general-purpose tools or generally available free
|
||||
programs which are used unmodified in performing those activities but
|
||||
which are not part of the work. For example, Corresponding Source
|
||||
includes interface definition files associated with source files for
|
||||
the work, and the source code for shared libraries and dynamically
|
||||
linked subprograms that the work is specifically designed to require,
|
||||
such as by intimate data communication or control flow between those
|
||||
subprograms and other parts of the work.
|
||||
|
||||
The Corresponding Source need not include anything that users
|
||||
can regenerate automatically from other parts of the Corresponding
|
||||
Source.
|
||||
|
||||
The Corresponding Source for a work in source code form is that
|
||||
same work.
|
||||
|
||||
2. Basic Permissions.
|
||||
|
||||
All rights granted under this License are granted for the term of
|
||||
copyright on the Program, and are irrevocable provided the stated
|
||||
conditions are met. This License explicitly affirms your unlimited
|
||||
permission to run the unmodified Program. The output from running a
|
||||
covered work is covered by this License only if the output, given its
|
||||
content, constitutes a covered work. This License acknowledges your
|
||||
rights of fair use or other equivalent, as provided by copyright law.
|
||||
|
||||
You may make, run and propagate covered works that you do not
|
||||
convey, without conditions so long as your license otherwise remains
|
||||
in force. You may convey covered works to others for the sole purpose
|
||||
of having them make modifications exclusively for you, or provide you
|
||||
with facilities for running those works, provided that you comply with
|
||||
the terms of this License in conveying all material for which you do
|
||||
not control copyright. Those thus making or running the covered works
|
||||
for you must do so exclusively on your behalf, under your direction
|
||||
and control, on terms that prohibit them from making any copies of
|
||||
your copyrighted material outside their relationship with you.
|
||||
|
||||
Conveying under any other circumstances is permitted solely under
|
||||
the conditions stated below. Sublicensing is not allowed; section 10
|
||||
makes it unnecessary.
|
||||
|
||||
3. Protecting Users' Legal Rights From Anti-Circumvention Law.
|
||||
|
||||
No covered work shall be deemed part of an effective technological
|
||||
measure under any applicable law fulfilling obligations under article
|
||||
11 of the WIPO copyright treaty adopted on 20 December 1996, or
|
||||
similar laws prohibiting or restricting circumvention of such
|
||||
measures.
|
||||
|
||||
When you convey a covered work, you waive any legal power to forbid
|
||||
circumvention of technological measures to the extent such circumvention
|
||||
is effected by exercising rights under this License with respect to
|
||||
the covered work, and you disclaim any intention to limit operation or
|
||||
modification of the work as a means of enforcing, against the work's
|
||||
users, your or third parties' legal rights to forbid circumvention of
|
||||
technological measures.
|
||||
|
||||
4. Conveying Verbatim Copies.
|
||||
|
||||
You may convey verbatim copies of the Program's source code as you
|
||||
receive it, in any medium, provided that you conspicuously and
|
||||
appropriately publish on each copy an appropriate copyright notice;
|
||||
keep intact all notices stating that this License and any
|
||||
non-permissive terms added in accord with section 7 apply to the code;
|
||||
keep intact all notices of the absence of any warranty; and give all
|
||||
recipients a copy of this License along with the Program.
|
||||
|
||||
You may charge any price or no price for each copy that you convey,
|
||||
and you may offer support or warranty protection for a fee.
|
||||
|
||||
5. Conveying Modified Source Versions.
|
||||
|
||||
You may convey a work based on the Program, or the modifications to
|
||||
produce it from the Program, in the form of source code under the
|
||||
terms of section 4, provided that you also meet all of these conditions:
|
||||
|
||||
a) The work must carry prominent notices stating that you modified
|
||||
it, and giving a relevant date.
|
||||
|
||||
b) The work must carry prominent notices stating that it is
|
||||
released under this License and any conditions added under section
|
||||
7. This requirement modifies the requirement in section 4 to
|
||||
"keep intact all notices".
|
||||
|
||||
c) You must license the entire work, as a whole, under this
|
||||
License to anyone who comes into possession of a copy. This
|
||||
License will therefore apply, along with any applicable section 7
|
||||
additional terms, to the whole of the work, and all its parts,
|
||||
regardless of how they are packaged. This License gives no
|
||||
permission to license the work in any other way, but it does not
|
||||
invalidate such permission if you have separately received it.
|
||||
|
||||
d) If the work has interactive user interfaces, each must display
|
||||
Appropriate Legal Notices; however, if the Program has interactive
|
||||
interfaces that do not display Appropriate Legal Notices, your
|
||||
work need not make them do so.
|
||||
|
||||
A compilation of a covered work with other separate and independent
|
||||
works, which are not by their nature extensions of the covered work,
|
||||
and which are not combined with it such as to form a larger program,
|
||||
in or on a volume of a storage or distribution medium, is called an
|
||||
"aggregate" if the compilation and its resulting copyright are not
|
||||
used to limit the access or legal rights of the compilation's users
|
||||
beyond what the individual works permit. Inclusion of a covered work
|
||||
in an aggregate does not cause this License to apply to the other
|
||||
parts of the aggregate.
|
||||
|
||||
6. Conveying Non-Source Forms.
|
||||
|
||||
You may convey a covered work in object code form under the terms
|
||||
of sections 4 and 5, provided that you also convey the
|
||||
machine-readable Corresponding Source under the terms of this License,
|
||||
in one of these ways:
|
||||
|
||||
a) Convey the object code in, or embodied in, a physical product
|
||||
(including a physical distribution medium), accompanied by the
|
||||
Corresponding Source fixed on a durable physical medium
|
||||
customarily used for software interchange.
|
||||
|
||||
b) Convey the object code in, or embodied in, a physical product
|
||||
(including a physical distribution medium), accompanied by a
|
||||
written offer, valid for at least three years and valid for as
|
||||
long as you offer spare parts or customer support for that product
|
||||
model, to give anyone who possesses the object code either (1) a
|
||||
copy of the Corresponding Source for all the software in the
|
||||
product that is covered by this License, on a durable physical
|
||||
medium customarily used for software interchange, for a price no
|
||||
more than your reasonable cost of physically performing this
|
||||
conveying of source, or (2) access to copy the
|
||||
Corresponding Source from a network server at no charge.
|
||||
|
||||
c) Convey individual copies of the object code with a copy of the
|
||||
written offer to provide the Corresponding Source. This
|
||||
alternative is allowed only occasionally and noncommercially, and
|
||||
only if you received the object code with such an offer, in accord
|
||||
with subsection 6b.
|
||||
|
||||
d) Convey the object code by offering access from a designated
|
||||
place (gratis or for a charge), and offer equivalent access to the
|
||||
Corresponding Source in the same way through the same place at no
|
||||
further charge. You need not require recipients to copy the
|
||||
Corresponding Source along with the object code. If the place to
|
||||
copy the object code is a network server, the Corresponding Source
|
||||
may be on a different server (operated by you or a third party)
|
||||
that supports equivalent copying facilities, provided you maintain
|
||||
clear directions next to the object code saying where to find the
|
||||
Corresponding Source. Regardless of what server hosts the
|
||||
Corresponding Source, you remain obligated to ensure that it is
|
||||
available for as long as needed to satisfy these requirements.
|
||||
|
||||
e) Convey the object code using peer-to-peer transmission, provided
|
||||
you inform other peers where the object code and Corresponding
|
||||
Source of the work are being offered to the general public at no
|
||||
charge under subsection 6d.
|
||||
|
||||
A separable portion of the object code, whose source code is excluded
|
||||
from the Corresponding Source as a System Library, need not be
|
||||
included in conveying the object code work.
|
||||
|
||||
A "User Product" is either (1) a "consumer product", which means any
|
||||
tangible personal property which is normally used for personal, family,
|
||||
or household purposes, or (2) anything designed or sold for incorporation
|
||||
into a dwelling. In determining whether a product is a consumer product,
|
||||
doubtful cases shall be resolved in favor of coverage. For a particular
|
||||
product received by a particular user, "normally used" refers to a
|
||||
typical or common use of that class of product, regardless of the status
|
||||
of the particular user or of the way in which the particular user
|
||||
actually uses, or expects or is expected to use, the product. A product
|
||||
is a consumer product regardless of whether the product has substantial
|
||||
commercial, industrial or non-consumer uses, unless such uses represent
|
||||
the only significant mode of use of the product.
|
||||
|
||||
"Installation Information" for a User Product means any methods,
|
||||
procedures, authorization keys, or other information required to install
|
||||
and execute modified versions of a covered work in that User Product from
|
||||
a modified version of its Corresponding Source. The information must
|
||||
suffice to ensure that the continued functioning of the modified object
|
||||
code is in no case prevented or interfered with solely because
|
||||
modification has been made.
|
||||
|
||||
If you convey an object code work under this section in, or with, or
|
||||
specifically for use in, a User Product, and the conveying occurs as
|
||||
part of a transaction in which the right of possession and use of the
|
||||
User Product is transferred to the recipient in perpetuity or for a
|
||||
fixed term (regardless of how the transaction is characterized), the
|
||||
Corresponding Source conveyed under this section must be accompanied
|
||||
by the Installation Information. But this requirement does not apply
|
||||
if neither you nor any third party retains the ability to install
|
||||
modified object code on the User Product (for example, the work has
|
||||
been installed in ROM).
|
||||
|
||||
The requirement to provide Installation Information does not include a
|
||||
requirement to continue to provide support service, warranty, or updates
|
||||
for a work that has been modified or installed by the recipient, or for
|
||||
the User Product in which it has been modified or installed. Access to a
|
||||
network may be denied when the modification itself materially and
|
||||
adversely affects the operation of the network or violates the rules and
|
||||
protocols for communication across the network.
|
||||
|
||||
Corresponding Source conveyed, and Installation Information provided,
|
||||
in accord with this section must be in a format that is publicly
|
||||
documented (and with an implementation available to the public in
|
||||
source code form), and must require no special password or key for
|
||||
unpacking, reading or copying.
|
||||
|
||||
7. Additional Terms.
|
||||
|
||||
"Additional permissions" are terms that supplement the terms of this
|
||||
License by making exceptions from one or more of its conditions.
|
||||
Additional permissions that are applicable to the entire Program shall
|
||||
be treated as though they were included in this License, to the extent
|
||||
that they are valid under applicable law. If additional permissions
|
||||
apply only to part of the Program, that part may be used separately
|
||||
under those permissions, but the entire Program remains governed by
|
||||
this License without regard to the additional permissions.
|
||||
|
||||
When you convey a copy of a covered work, you may at your option
|
||||
remove any additional permissions from that copy, or from any part of
|
||||
it. (Additional permissions may be written to require their own
|
||||
removal in certain cases when you modify the work.) You may place
|
||||
additional permissions on material, added by you to a covered work,
|
||||
for which you have or can give appropriate copyright permission.
|
||||
|
||||
Notwithstanding any other provision of this License, for material you
|
||||
add to a covered work, you may (if authorized by the copyright holders of
|
||||
that material) supplement the terms of this License with terms:
|
||||
|
||||
a) Disclaiming warranty or limiting liability differently from the
|
||||
terms of sections 15 and 16 of this License; or
|
||||
|
||||
b) Requiring preservation of specified reasonable legal notices or
|
||||
author attributions in that material or in the Appropriate Legal
|
||||
Notices displayed by works containing it; or
|
||||
|
||||
c) Prohibiting misrepresentation of the origin of that material, or
|
||||
requiring that modified versions of such material be marked in
|
||||
reasonable ways as different from the original version; or
|
||||
|
||||
d) Limiting the use for publicity purposes of names of licensors or
|
||||
authors of the material; or
|
||||
|
||||
e) Declining to grant rights under trademark law for use of some
|
||||
trade names, trademarks, or service marks; or
|
||||
|
||||
f) Requiring indemnification of licensors and authors of that
|
||||
material by anyone who conveys the material (or modified versions of
|
||||
it) with contractual assumptions of liability to the recipient, for
|
||||
any liability that these contractual assumptions directly impose on
|
||||
those licensors and authors.
|
||||
|
||||
All other non-permissive additional terms are considered "further
|
||||
restrictions" within the meaning of section 10. If the Program as you
|
||||
received it, or any part of it, contains a notice stating that it is
|
||||
governed by this License along with a term that is a further
|
||||
restriction, you may remove that term. If a license document contains
|
||||
a further restriction but permits relicensing or conveying under this
|
||||
License, you may add to a covered work material governed by the terms
|
||||
of that license document, provided that the further restriction does
|
||||
not survive such relicensing or conveying.
|
||||
|
||||
If you add terms to a covered work in accord with this section, you
|
||||
must place, in the relevant source files, a statement of the
|
||||
additional terms that apply to those files, or a notice indicating
|
||||
where to find the applicable terms.
|
||||
|
||||
Additional terms, permissive or non-permissive, may be stated in the
|
||||
form of a separately written license, or stated as exceptions;
|
||||
the above requirements apply either way.
|
||||
|
||||
8. Termination.
|
||||
|
||||
You may not propagate or modify a covered work except as expressly
|
||||
provided under this License. Any attempt otherwise to propagate or
|
||||
modify it is void, and will automatically terminate your rights under
|
||||
this License (including any patent licenses granted under the third
|
||||
paragraph of section 11).
|
||||
|
||||
However, if you cease all violation of this License, then your
|
||||
license from a particular copyright holder is reinstated (a)
|
||||
provisionally, unless and until the copyright holder explicitly and
|
||||
finally terminates your license, and (b) permanently, if the copyright
|
||||
holder fails to notify you of the violation by some reasonable means
|
||||
prior to 60 days after the cessation.
|
||||
|
||||
Moreover, your license from a particular copyright holder is
|
||||
reinstated permanently if the copyright holder notifies you of the
|
||||
violation by some reasonable means, this is the first time you have
|
||||
received notice of violation of this License (for any work) from that
|
||||
copyright holder, and you cure the violation prior to 30 days after
|
||||
your receipt of the notice.
|
||||
|
||||
Termination of your rights under this section does not terminate the
|
||||
licenses of parties who have received copies or rights from you under
|
||||
this License. If your rights have been terminated and not permanently
|
||||
reinstated, you do not qualify to receive new licenses for the same
|
||||
material under section 10.
|
||||
|
||||
9. Acceptance Not Required for Having Copies.
|
||||
|
||||
You are not required to accept this License in order to receive or
|
||||
run a copy of the Program. Ancillary propagation of a covered work
|
||||
occurring solely as a consequence of using peer-to-peer transmission
|
||||
to receive a copy likewise does not require acceptance. However,
|
||||
nothing other than this License grants you permission to propagate or
|
||||
modify any covered work. These actions infringe copyright if you do
|
||||
not accept this License. Therefore, by modifying or propagating a
|
||||
covered work, you indicate your acceptance of this License to do so.
|
||||
|
||||
10. Automatic Licensing of Downstream Recipients.
|
||||
|
||||
Each time you convey a covered work, the recipient automatically
|
||||
receives a license from the original licensors, to run, modify and
|
||||
propagate that work, subject to this License. You are not responsible
|
||||
for enforcing compliance by third parties with this License.
|
||||
|
||||
An "entity transaction" is a transaction transferring control of an
|
||||
organization, or substantially all assets of one, or subdividing an
|
||||
organization, or merging organizations. If propagation of a covered
|
||||
work results from an entity transaction, each party to that
|
||||
transaction who receives a copy of the work also receives whatever
|
||||
licenses to the work the party's predecessor in interest had or could
|
||||
give under the previous paragraph, plus a right to possession of the
|
||||
Corresponding Source of the work from the predecessor in interest, if
|
||||
the predecessor has it or can get it with reasonable efforts.
|
||||
|
||||
You may not impose any further restrictions on the exercise of the
|
||||
rights granted or affirmed under this License. For example, you may
|
||||
not impose a license fee, royalty, or other charge for exercise of
|
||||
rights granted under this License, and you may not initiate litigation
|
||||
(including a cross-claim or counterclaim in a lawsuit) alleging that
|
||||
any patent claim is infringed by making, using, selling, offering for
|
||||
sale, or importing the Program or any portion of it.
|
||||
|
||||
11. Patents.
|
||||
|
||||
A "contributor" is a copyright holder who authorizes use under this
|
||||
License of the Program or a work on which the Program is based. The
|
||||
work thus licensed is called the contributor's "contributor version".
|
||||
|
||||
A contributor's "essential patent claims" are all patent claims
|
||||
owned or controlled by the contributor, whether already acquired or
|
||||
hereafter acquired, that would be infringed by some manner, permitted
|
||||
by this License, of making, using, or selling its contributor version,
|
||||
but do not include claims that would be infringed only as a
|
||||
consequence of further modification of the contributor version. For
|
||||
purposes of this definition, "control" includes the right to grant
|
||||
patent sublicenses in a manner consistent with the requirements of
|
||||
this License.
|
||||
|
||||
Each contributor grants you a non-exclusive, worldwide, royalty-free
|
||||
patent license under the contributor's essential patent claims, to
|
||||
make, use, sell, offer for sale, import and otherwise run, modify and
|
||||
propagate the contents of its contributor version.
|
||||
|
||||
In the following three paragraphs, a "patent license" is any express
|
||||
agreement or commitment, however denominated, not to enforce a patent
|
||||
(such as an express permission to practice a patent or covenant not to
|
||||
sue for patent infringement). To "grant" such a patent license to a
|
||||
party means to make such an agreement or commitment not to enforce a
|
||||
patent against the party.
|
||||
|
||||
If you convey a covered work, knowingly relying on a patent license,
|
||||
and the Corresponding Source of the work is not available for anyone
|
||||
to copy, free of charge and under the terms of this License, through a
|
||||
publicly available network server or other readily accessible means,
|
||||
then you must either (1) cause the Corresponding Source to be so
|
||||
available, or (2) arrange to deprive yourself of the benefit of the
|
||||
patent license for this particular work, or (3) arrange, in a manner
|
||||
consistent with the requirements of this License, to extend the patent
|
||||
license to downstream recipients. "Knowingly relying" means you have
|
||||
actual knowledge that, but for the patent license, your conveying the
|
||||
covered work in a country, or your recipient's use of the covered work
|
||||
in a country, would infringe one or more identifiable patents in that
|
||||
country that you have reason to believe are valid.
|
||||
|
||||
If, pursuant to or in connection with a single transaction or
|
||||
arrangement, you convey, or propagate by procuring conveyance of, a
|
||||
covered work, and grant a patent license to some of the parties
|
||||
receiving the covered work authorizing them to use, propagate, modify
|
||||
or convey a specific copy of the covered work, then the patent license
|
||||
you grant is automatically extended to all recipients of the covered
|
||||
work and works based on it.
|
||||
|
||||
A patent license is "discriminatory" if it does not include within
|
||||
the scope of its coverage, prohibits the exercise of, or is
|
||||
conditioned on the non-exercise of one or more of the rights that are
|
||||
specifically granted under this License. You may not convey a covered
|
||||
work if you are a party to an arrangement with a third party that is
|
||||
in the business of distributing software, under which you make payment
|
||||
to the third party based on the extent of your activity of conveying
|
||||
the work, and under which the third party grants, to any of the
|
||||
parties who would receive the covered work from you, a discriminatory
|
||||
patent license (a) in connection with copies of the covered work
|
||||
conveyed by you (or copies made from those copies), or (b) primarily
|
||||
for and in connection with specific products or compilations that
|
||||
contain the covered work, unless you entered into that arrangement,
|
||||
or that patent license was granted, prior to 28 March 2007.
|
||||
|
||||
Nothing in this License shall be construed as excluding or limiting
|
||||
any implied license or other defenses to infringement that may
|
||||
otherwise be available to you under applicable patent law.
|
||||
|
||||
12. No Surrender of Others' Freedom.
|
||||
|
||||
If conditions are imposed on you (whether by court order, agreement or
|
||||
otherwise) that contradict the conditions of this License, they do not
|
||||
excuse you from the conditions of this License. If you cannot convey a
|
||||
covered work so as to satisfy simultaneously your obligations under this
|
||||
License and any other pertinent obligations, then as a consequence you may
|
||||
not convey it at all. For example, if you agree to terms that obligate you
|
||||
to collect a royalty for further conveying from those to whom you convey
|
||||
the Program, the only way you could satisfy both those terms and this
|
||||
License would be to refrain entirely from conveying the Program.
|
||||
|
||||
13. Use with the GNU Affero General Public License.
|
||||
|
||||
Notwithstanding any other provision of this License, you have
|
||||
permission to link or combine any covered work with a work licensed
|
||||
under version 3 of the GNU Affero General Public License into a single
|
||||
combined work, and to convey the resulting work. The terms of this
|
||||
License will continue to apply to the part which is the covered work,
|
||||
but the special requirements of the GNU Affero General Public License,
|
||||
section 13, concerning interaction through a network will apply to the
|
||||
combination as such.
|
||||
|
||||
14. Revised Versions of this License.
|
||||
|
||||
The Free Software Foundation may publish revised and/or new versions of
|
||||
the GNU General Public License from time to time. Such new versions will
|
||||
be similar in spirit to the present version, but may differ in detail to
|
||||
address new problems or concerns.
|
||||
|
||||
Each version is given a distinguishing version number. If the
|
||||
Program specifies that a certain numbered version of the GNU General
|
||||
Public License "or any later version" applies to it, you have the
|
||||
option of following the terms and conditions either of that numbered
|
||||
version or of any later version published by the Free Software
|
||||
Foundation. If the Program does not specify a version number of the
|
||||
GNU General Public License, you may choose any version ever published
|
||||
by the Free Software Foundation.
|
||||
|
||||
If the Program specifies that a proxy can decide which future
|
||||
versions of the GNU General Public License can be used, that proxy's
|
||||
public statement of acceptance of a version permanently authorizes you
|
||||
to choose that version for the Program.
|
||||
|
||||
Later license versions may give you additional or different
|
||||
permissions. However, no additional obligations are imposed on any
|
||||
author or copyright holder as a result of your choosing to follow a
|
||||
later version.
|
||||
|
||||
15. Disclaimer of Warranty.
|
||||
|
||||
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
|
||||
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
|
||||
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
|
||||
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
|
||||
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
||||
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
|
||||
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
|
||||
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
|
||||
|
||||
16. Limitation of Liability.
|
||||
|
||||
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
|
||||
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
|
||||
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
|
||||
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
|
||||
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
|
||||
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
|
||||
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
|
||||
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
|
||||
SUCH DAMAGES.
|
||||
|
||||
17. Interpretation of Sections 15 and 16.
|
||||
|
||||
If the disclaimer of warranty and limitation of liability provided
|
||||
above cannot be given local legal effect according to their terms,
|
||||
reviewing courts shall apply local law that most closely approximates
|
||||
an absolute waiver of all civil liability in connection with the
|
||||
Program, unless a warranty or assumption of liability accompanies a
|
||||
copy of the Program in return for a fee.
|
||||
|
||||
END OF TERMS AND CONDITIONS
|
||||
|
||||
How to Apply These Terms to Your New Programs
|
||||
|
||||
If you develop a new program, and you want it to be of the greatest
|
||||
possible use to the public, the best way to achieve this is to make it
|
||||
free software which everyone can redistribute and change under these terms.
|
||||
|
||||
To do so, attach the following notices to the program. It is safest
|
||||
to attach them to the start of each source file to most effectively
|
||||
state the exclusion of warranty; and each file should have at least
|
||||
the "copyright" line and a pointer to where the full notice is found.
|
||||
|
||||
<one line to give the program's name and a brief idea of what it does.>
|
||||
Copyright (C) <year> <name of author>
|
||||
|
||||
This program is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU General Public License as published by
|
||||
the Free Software Foundation, either version 3 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
This program is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU General Public License
|
||||
along with this program. If not, see <https://www.gnu.org/licenses/>.
|
||||
|
||||
Also add information on how to contact you by electronic and paper mail.
|
||||
|
||||
If the program does terminal interaction, make it output a short
|
||||
notice like this when it starts in an interactive mode:
|
||||
|
||||
<program> Copyright (C) <year> <name of author>
|
||||
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
|
||||
This is free software, and you are welcome to redistribute it
|
||||
under certain conditions; type `show c' for details.
|
||||
|
||||
The hypothetical commands `show w' and `show c' should show the appropriate
|
||||
parts of the General Public License. Of course, your program's commands
|
||||
might be different; for a GUI interface, you would use an "about box".
|
||||
|
||||
You should also get your employer (if you work as a programmer) or school,
|
||||
if any, to sign a "copyright disclaimer" for the program, if necessary.
|
||||
For more information on this, and how to apply and follow the GNU GPL, see
|
||||
<https://www.gnu.org/licenses/>.
|
||||
|
||||
The GNU General Public License does not permit incorporating your program
|
||||
into proprietary programs. If your program is a subroutine library, you
|
||||
may consider it more useful to permit linking proprietary applications with
|
||||
the library. If this is what you want to do, use the GNU Lesser General
|
||||
Public License instead of this License. But first, please read
|
||||
<https://www.gnu.org/licenses/why-not-lgpl.html>.
|
||||
@@ -0,0 +1,116 @@
|
||||
# ComfyUI TK3R Extensions
|
||||
Extended versions of various ComfyUI nodes plus some utility nodes.
|
||||
|
||||
## Description
|
||||
This repository contains custom nodes for ComfyUI that provide extended capabilities beyond the standard nodes as well as some utility nodes.
|
||||
|
||||
|
||||
## Installation
|
||||
|
||||
### Method 1: ComfyUI Manager (Recommended)
|
||||
|
||||
1. Install [ComfyUI Manager](https://github.com/ltdrdata/ComfyUI-Manager)
|
||||
2. Search for "TK3R Extensions" in the manager
|
||||
3. Click Install
|
||||
|
||||
### Method 2: Manual Installation
|
||||
|
||||
1. Navigate to your ComfyUI custom nodes directory:
|
||||
```bash
|
||||
cd ComfyUI/custom_nodes
|
||||
```
|
||||
|
||||
2. Clone this repository:
|
||||
```bash
|
||||
git clone https://github.com/TK3R/ComfyUI_TK3R_Ext.git
|
||||
```
|
||||
|
||||
3. Restart ComfyUI
|
||||
|
||||
|
||||
## Usage
|
||||
After installation, the nodes will appear in ComfyUI under the "TK3R Advanced" and "TK3R Utility" categories. Each node provides specific functionality:
|
||||
|
||||
|
||||
### TK3R ControlNet Apply Advanced
|
||||
Advanced version of the ControlNet Apply node with a strength decay option. Allows gradual decay of the controlnet strength rather than sharp cutoff. Similar principle as the Qwen/ZImage controlnet nodes, see examples below.
|
||||
|
||||
|
||||
### TK3R Qwen Image Diffsynth ControlNet Advanced / TK3R ZImage Fun Controlnet
|
||||
Advanced version of the QwenImageDiffsynthControlnet / ZImageFunControlnet nodes with start / stop control as well as strength decay option, allowing significantly more control and making controlnets more useful. For example cutting off the controlnet influence earlier frees the model to fill in finer details, or you can cut off very early so that the controlnet only guides the general composition.
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
### TK3R Scheduled CFG Guider
|
||||
Advanced version of the CFGGuider node allowing per-step CFG scheduling.
|
||||
|
||||
|
||||
|
||||
git push --force -u origin mainnotes: The schedule is comma separated floats interpolated over the set amount of steps, if you want something like an exponential curve just copy the same values several times; *schedule* output is the CFG schedule for info/debugging reasons, *normalized_schedule* is an output that can be used with a graph node to compare against the sigma schedule of models where the sigmas go 1.0 - 0.0
|
||||
|
||||
|
||||
### TK3R TextEncodeQwenImageEditPlus Ext
|
||||
An enhanced version of the TextEncodeQwenImageEditPlus node; not my code, but I do not remember where I got it from and it was an overwrite of the default node so I separated it into my nodes.
|
||||
|
||||
|
||||
|
||||
|
||||
### TK3R CLIP Text Encode With Token Count
|
||||
A version of the CLIP Text Encode node showing the character and token count after encoding. Useful for staying within the token count limits of the various encoders. It also merges the lumina2 text encode sysprompt code so there's no need to use a separate node.
|
||||
|
||||
|
||||
|
||||
|
||||
### TK3R Image Compare
|
||||
This is a small utility node that caches the last input image. I use it together with rgthree Image Comparer to compare the current generation with the previous one. Simply wire the vae decode image output to its image input and output 1 will be the current image and output 2 - the previous one.
|
||||
|
||||
|
||||
|
||||
|
||||
### TK3R Lora Rank Reader
|
||||
A simple utility node that reads a lora and outputs its rank.
|
||||
|
||||
|
||||
|
||||
|
||||
### TK3R Safetensors Precision Reader
|
||||
A simple utility node that reads a safetensors file and outputs its floating-point precision.
|
||||
|
||||
|
||||
|
||||
|
||||
### TK3R Sigmas Interpolate
|
||||
A simple utility node that allows blending two sigma schedules with the same step count. Just for fun.
|
||||
|
||||
|
||||
|
||||
|
||||
## License
|
||||
GPLv3 License same as ComfyUI license as several nodes are derivatives of ComfyUI nodes - See LICENSE file for details
|
||||
|
||||
|
||||
## Credits
|
||||
- Node loader code adapted from [WAS Extras](https://github.com/WASasquatch/WAS_Extras), thank you [WAS](https://github.com/WASasquatch)
|
||||
- These nodes are mostly vibe-coded with different Github Copilot agents
|
||||
|
||||
|
||||
## Changelog
|
||||
|
||||
### v1.0.0
|
||||
- Initial release
|
||||
- TK3R ControlNet Apply Advanced
|
||||
- TK3R Qwen Image Diffsynth ControlNet Advanced / TK3R ZImage Fun Controlnet
|
||||
- TK3R Scheduled CFG Guider
|
||||
- TK3R TextEncodeQwenImageEditPlus Ext
|
||||
- TK3R CLIP Text Encode With Token Count
|
||||
- TK3R Image Compare
|
||||
- TK3r Lora Rank Reader
|
||||
- TK3R Safetensors Precision Reader
|
||||
- TK3R Sigmas Interpolate
|
||||
+139
@@ -0,0 +1,139 @@
|
||||
# code lifted from WAS Extras, thanks WAS
|
||||
|
||||
import importlib
|
||||
import pkgutil
|
||||
import time
|
||||
import traceback
|
||||
import os
|
||||
|
||||
|
||||
try:
|
||||
from rich.console import Console
|
||||
from rich.table import Table
|
||||
from rich.panel import Panel
|
||||
from rich.progress import Progress, SpinnerColumn, TimeElapsedColumn, TextColumn
|
||||
from rich.traceback import install as rich_traceback_install
|
||||
console = Console(force_terminal=True, no_color=False)
|
||||
rich_traceback_install(show_locals=False, word_wrap=True)
|
||||
except Exception:
|
||||
console = None
|
||||
|
||||
PREFIX = "[TK3R Ext] "
|
||||
|
||||
NODE_CLASS_MAPPINGS = {}
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {}
|
||||
|
||||
WEB_DIRECTORY = os.path.join(os.path.dirname(__file__), "web")
|
||||
|
||||
|
||||
class NodeLoader:
|
||||
def __init__(self, package_name: str, prefix: str = PREFIX):
|
||||
self.package_name = package_name
|
||||
self.prefix = prefix
|
||||
self.timings: dict[str, tuple[float, bool, Exception | None]] = {}
|
||||
|
||||
def module_path(self, module) -> str:
|
||||
spec = getattr(module, "__spec__", None)
|
||||
if spec and getattr(spec, "origin", None):
|
||||
return spec.origin
|
||||
return getattr(module, "__file__", repr(module))
|
||||
|
||||
def record(self, module, elapsed: float, ok: bool, err: Exception | None) -> None:
|
||||
self.timings[self.module_path(module)] = (elapsed, ok, err)
|
||||
if ok:
|
||||
NODE_CLASS_MAPPINGS.update(getattr(module, "NODE_CLASS_MAPPINGS", {}))
|
||||
NODE_DISPLAY_NAME_MAPPINGS.update(getattr(module, "NODE_DISPLAY_NAME_MAPPINGS", {}))
|
||||
|
||||
def import_module(self, fullname: str, package: str | None = None) -> tuple[object | None, bool]:
|
||||
t0 = time.time()
|
||||
ok = True
|
||||
err = None
|
||||
mod = None
|
||||
try:
|
||||
mod = importlib.import_module(fullname, package=package)
|
||||
except Exception as e:
|
||||
ok = False
|
||||
err = e
|
||||
if console is None:
|
||||
traceback.print_exc()
|
||||
else:
|
||||
console.print_exception()
|
||||
elapsed = time.time() - t0
|
||||
if mod is not None:
|
||||
self.record(mod, elapsed, ok, err)
|
||||
return mod, ok
|
||||
|
||||
def print_intro(self) -> None:
|
||||
msg = "A few enhanced vanilla nodes as well as some utility nodes. No warranty."
|
||||
if console:
|
||||
# Single rule and a single-titled panel
|
||||
console.rule(style="cyan")
|
||||
console.print(Panel(msg, title="TK3R Ext", border_style="cyan"))
|
||||
else:
|
||||
print(f"{self.prefix}A few enhanced vanilla nodes as well as some utility nodes. No warranty.")
|
||||
|
||||
def print_no_nodes_pkg(self) -> None:
|
||||
msg = "No ./nodes package found or import failed."
|
||||
if console:
|
||||
console.print(f"{self.prefix}[bold yellow]{msg}[/bold yellow]")
|
||||
else:
|
||||
print(f"{self.prefix}{msg}")
|
||||
|
||||
def print_summary(self) -> None:
|
||||
total = len(self.timings)
|
||||
ok_count = sum(1 for _, (_, ok, _) in self.timings.items() if ok)
|
||||
fail_count = total - ok_count
|
||||
if console:
|
||||
table = Table(
|
||||
expand=False,
|
||||
header_style="cyan",
|
||||
border_style="cyan",
|
||||
)
|
||||
table.add_column("Module/File", overflow="fold")
|
||||
table.add_column("Time (s)", justify="right")
|
||||
table.add_column("Status", justify="center")
|
||||
table.add_column("Error", overflow="fold")
|
||||
for path, (timing, success, err) in self.timings.items():
|
||||
status = "[green]OK[/green]" if success else "[red]FAILED[/red]"
|
||||
err_text = "" if err is None else f"{type(err).__name__}: {err}"
|
||||
table.add_row(str(path), f"{timing:.2f}", status, err_text)
|
||||
console.print(table)
|
||||
console.print(f"Totals: [green]{ok_count} ok[/green], [red]{fail_count} failed[/red], {total} modules.")
|
||||
else:
|
||||
print(f"{self.prefix} Import times:")
|
||||
for path, (timing, success, err) in self.timings.items():
|
||||
print(f" {timing:.1f} seconds{('' if success else ' (IMPORT FAILED)')}: {path}")
|
||||
if err:
|
||||
print("Error:", err)
|
||||
print(f"{self.prefix}Totals: {total} modules, {ok_count} ok, {fail_count} failed.")
|
||||
|
||||
def load_all(self) -> None:
|
||||
# self.print_intro()
|
||||
nodes_pkg, ok = self.import_module(".nodes", package=self.package_name)
|
||||
if not ok or nodes_pkg is None:
|
||||
self.print_no_nodes_pkg()
|
||||
self.print_summary()
|
||||
return
|
||||
if console:
|
||||
with Progress(
|
||||
SpinnerColumn(style="cyan"),
|
||||
TextColumn("[progress.description]{task.description}", style="bright_black"),
|
||||
TimeElapsedColumn(),
|
||||
console=console,
|
||||
transient=True,
|
||||
) as progress:
|
||||
task = progress.add_task("Loading nodes from ./nodes ...", total=None)
|
||||
for _, name, _ in pkgutil.walk_packages(nodes_pkg.__path__, prefix=nodes_pkg.__name__ + "."):
|
||||
self.import_module(name)
|
||||
progress.remove_task(task)
|
||||
else:
|
||||
print("Loading nodes from ./nodes ...")
|
||||
for _, name, _ in pkgutil.walk_packages(nodes_pkg.__path__, prefix=nodes_pkg.__name__ + "."):
|
||||
self.import_module(name)
|
||||
self.print_summary()
|
||||
|
||||
|
||||
_loader = NodeLoader(package_name=__name__, prefix=PREFIX)
|
||||
_loader.load_all()
|
||||
|
||||
__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", "WEB_DIRECTORY"]
|
||||
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|
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|
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|
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@@ -0,0 +1,368 @@
|
||||
"""
|
||||
Custom ControlNet nodes with start/stop percent and decay functionality.
|
||||
This file contains modified versions of QwenImageDiffsynthControlnet and related classes
|
||||
that support temporal control with decay modes.
|
||||
|
||||
Extracted from comfy_extras/nodes_model_patch.py to preserve custom modifications
|
||||
after ComfyUI updates.
|
||||
"""
|
||||
|
||||
import math
|
||||
import torch
|
||||
import comfy.utils
|
||||
import comfy.latent_formats
|
||||
import comfy.model_management
|
||||
import comfy.ldm.lumina.controlnet
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Sigma Window and Decay Utilities
|
||||
# ============================================================================
|
||||
|
||||
SIGMA_EPS = 1e-6
|
||||
|
||||
|
||||
def _clamp_percent(value: float) -> float:
|
||||
return max(0.0, min(1.0, float(value)))
|
||||
|
||||
|
||||
def _sigma_from_percent(model_sampling, percent: float) -> float:
|
||||
sigma = model_sampling.percent_to_sigma(percent)
|
||||
if isinstance(sigma, torch.Tensor):
|
||||
sigma = float(sigma.detach().cpu())
|
||||
return float(sigma)
|
||||
|
||||
|
||||
def resolve_sigma_window(model_sampling, start_percent: float, end_percent: float):
|
||||
start = _clamp_percent(start_percent)
|
||||
end = _clamp_percent(end_percent)
|
||||
sigma_start = _sigma_from_percent(model_sampling, start)
|
||||
sigma_end = _sigma_from_percent(model_sampling, end)
|
||||
sigma_high = max(sigma_start, sigma_end)
|
||||
sigma_low = min(sigma_start, sigma_end)
|
||||
if math.isclose(sigma_high, sigma_low, rel_tol=1e-6, abs_tol=SIGMA_EPS):
|
||||
sigma_high += SIGMA_EPS
|
||||
return sigma_low, sigma_high
|
||||
|
||||
|
||||
def current_sigma(transformer_options):
|
||||
if not isinstance(transformer_options, dict):
|
||||
return None
|
||||
sigma_tensor = transformer_options.get("sigmas")
|
||||
if not isinstance(sigma_tensor, torch.Tensor) or sigma_tensor.numel() == 0:
|
||||
return None
|
||||
return float(sigma_tensor.reshape(-1)[0].item())
|
||||
|
||||
|
||||
def sigma_within_window(transformer_options, sigma_low: float, sigma_high: float, sigma_val=None) -> bool:
|
||||
if sigma_val is None:
|
||||
sigma_val = current_sigma(transformer_options)
|
||||
if sigma_val is None:
|
||||
return True
|
||||
return (sigma_low - SIGMA_EPS) <= sigma_val <= (sigma_high + SIGMA_EPS)
|
||||
|
||||
|
||||
DECAY_MODES = ["none", "linear", "cosine", "exponential", "inverse_exponential"]
|
||||
|
||||
|
||||
def calculate_strength_multiplier(sigma_val, sigma_low, sigma_high, decay_mode="none"):
|
||||
"""Calculate strength multiplier based on sigma position within window.
|
||||
|
||||
Args:
|
||||
sigma_val: Current sigma value
|
||||
sigma_low: Low bound of sigma window (corresponds to stop_percent)
|
||||
sigma_high: High bound of sigma window (corresponds to start_percent)
|
||||
decay_mode: One of "none", "linear", "cosine", "exponential", "inverse_exponential"
|
||||
|
||||
Returns:
|
||||
Strength multiplier between 0.0 and 1.0
|
||||
"""
|
||||
if sigma_val is None:
|
||||
return 1.0
|
||||
|
||||
# Outside window check
|
||||
if sigma_val < sigma_low - SIGMA_EPS:
|
||||
return 0.0
|
||||
if sigma_val > sigma_high + SIGMA_EPS:
|
||||
return 0.0 if decay_mode != "none" else 1.0
|
||||
|
||||
# No decay - instant cutoff at stop_percent
|
||||
if decay_mode == "none":
|
||||
return 1.0
|
||||
|
||||
if sigma_high <= sigma_low:
|
||||
return 1.0
|
||||
|
||||
# Calculate normalized position: 1.0 at sigma_high (start), 0.0 at sigma_low (stop)
|
||||
t = (sigma_val - sigma_low) / (sigma_high - sigma_low)
|
||||
t = max(0.0, min(1.0, t)) # Clamp to [0, 1]
|
||||
|
||||
if decay_mode == "linear":
|
||||
return t
|
||||
elif decay_mode == "cosine":
|
||||
# Smooth S-curve using cosine interpolation
|
||||
return (1.0 - math.cos(t * math.pi)) / 2.0
|
||||
elif decay_mode == "exponential":
|
||||
# Fast decay at start, slow at end (strength drops quickly)
|
||||
return 1.0 - math.exp(-3.0 * t) / (1.0 - math.exp(-3.0)) if t > 0 else 0.0
|
||||
elif decay_mode == "inverse_exponential":
|
||||
# Slow decay at start, fast at end (strength holds longer)
|
||||
return (math.exp(3.0 * t) - 1.0) / (math.exp(3.0) - 1.0)
|
||||
else:
|
||||
return 1.0
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Patch Classes with Decay Support
|
||||
# ============================================================================
|
||||
|
||||
class DiffSynthCnetPatch:
|
||||
def __init__(self, model_patch, vae, image, strength, mask=None, sigma_low: float = float("-inf"), sigma_high: float = float("inf"),
|
||||
start_percent: float = 0.0, stop_percent: float = 1.0, decay_mode: str = "none"):
|
||||
self.model_patch = model_patch
|
||||
self.vae = vae
|
||||
self.image = image
|
||||
self.strength = strength
|
||||
self.mask = mask
|
||||
self.sigma_low = min(sigma_low, sigma_high)
|
||||
self.sigma_high = max(sigma_low, sigma_high)
|
||||
self.start_percent = start_percent
|
||||
self.stop_percent = stop_percent
|
||||
self.decay_mode = decay_mode
|
||||
self.encoded_image = model_patch.model.process_input_latent_image(self.encode_latent_cond(image))
|
||||
self.encoded_image_size = (image.shape[1], image.shape[2])
|
||||
|
||||
def encode_latent_cond(self, image):
|
||||
latent_image = self.vae.encode(image)
|
||||
if self.model_patch.model.additional_in_dim > 0:
|
||||
if self.mask is None:
|
||||
mask_ = torch.ones_like(latent_image)[:, :self.model_patch.model.additional_in_dim // 4]
|
||||
else:
|
||||
mask_ = comfy.utils.common_upscale(self.mask.mean(dim=1, keepdim=True), latent_image.shape[-1], latent_image.shape[-2], "bilinear", "none")
|
||||
|
||||
return torch.cat([latent_image, mask_], dim=1)
|
||||
else:
|
||||
return latent_image
|
||||
|
||||
def __call__(self, kwargs):
|
||||
transformer_options = kwargs.get("transformer_options")
|
||||
block_index = kwargs.get("block_index")
|
||||
sigma_val = current_sigma(transformer_options)
|
||||
|
||||
# Calculate strength multiplier based on position in sigma window
|
||||
strength_mult = calculate_strength_multiplier(sigma_val, self.sigma_low, self.sigma_high, self.decay_mode)
|
||||
effective_strength = self.strength * strength_mult
|
||||
|
||||
if strength_mult <= 0:
|
||||
return kwargs
|
||||
|
||||
x = kwargs.get("x")
|
||||
img = kwargs.get("img")
|
||||
spacial_compression = self.vae.spacial_compression_encode()
|
||||
if self.encoded_image is None or self.encoded_image_size != (x.shape[-2] * spacial_compression, x.shape[-1] * spacial_compression):
|
||||
image_scaled = comfy.utils.common_upscale(self.image.movedim(-1, 1), x.shape[-1] * spacial_compression, x.shape[-2] * spacial_compression, "area", "center")
|
||||
loaded_models = comfy.model_management.loaded_models(only_currently_used=True)
|
||||
self.encoded_image = self.model_patch.model.process_input_latent_image(self.encode_latent_cond(image_scaled.movedim(1, -1)))
|
||||
self.encoded_image_size = (image_scaled.shape[-2], image_scaled.shape[-1])
|
||||
comfy.model_management.load_models_gpu(loaded_models)
|
||||
|
||||
img[:, :self.encoded_image.shape[1]] += (self.model_patch.model.control_block(img[:, :self.encoded_image.shape[1]], self.encoded_image.to(img.dtype), block_index) * effective_strength)
|
||||
kwargs['img'] = img
|
||||
return kwargs
|
||||
|
||||
def to(self, device_or_dtype):
|
||||
if isinstance(device_or_dtype, torch.device):
|
||||
self.encoded_image = self.encoded_image.to(device_or_dtype)
|
||||
return self
|
||||
|
||||
def models(self):
|
||||
return [self.model_patch]
|
||||
|
||||
|
||||
class ZImageControlPatch:
|
||||
def __init__(self, model_patch, vae, image, strength, inpaint_image=None, mask=None, sigma_low: float = float("-inf"), sigma_high: float = float("inf"),
|
||||
start_percent: float = 0.0, stop_percent: float = 1.0, decay_mode: str = "none"):
|
||||
self.model_patch = model_patch
|
||||
self.vae = vae
|
||||
self.image = image
|
||||
self.inpaint_image = inpaint_image
|
||||
self.mask = mask
|
||||
self.strength = strength
|
||||
self.sigma_low = min(sigma_low, sigma_high)
|
||||
self.sigma_high = max(sigma_low, sigma_high)
|
||||
self.start_percent = start_percent
|
||||
self.stop_percent = stop_percent
|
||||
self.decay_mode = decay_mode
|
||||
self.encoded_image = self.encode_latent_cond(image)
|
||||
self.encoded_image_size = (image.shape[1], image.shape[2])
|
||||
self.temp_data = None
|
||||
|
||||
def encode_latent_cond(self, control_image, inpaint_image=None):
|
||||
latent_image = comfy.latent_formats.Flux().process_in(self.vae.encode(control_image))
|
||||
if self.model_patch.model.additional_in_dim > 0:
|
||||
if self.mask is None:
|
||||
mask_ = torch.zeros_like(latent_image)[:, :1]
|
||||
else:
|
||||
mask_ = comfy.utils.common_upscale(self.mask.mean(dim=1, keepdim=True), latent_image.shape[-1], latent_image.shape[-2], "bilinear", "none")
|
||||
if inpaint_image is None:
|
||||
inpaint_image = torch.ones_like(control_image) * 0.5
|
||||
|
||||
inpaint_image_latent = comfy.latent_formats.Flux().process_in(self.vae.encode(inpaint_image))
|
||||
|
||||
return torch.cat([latent_image, mask_, inpaint_image_latent], dim=1)
|
||||
else:
|
||||
return latent_image
|
||||
|
||||
def __call__(self, kwargs):
|
||||
transformer_options = kwargs.get("transformer_options")
|
||||
block_index = kwargs.get("block_index")
|
||||
block_type = kwargs.get("block_type", "")
|
||||
sigma_val = current_sigma(transformer_options)
|
||||
|
||||
# Calculate strength multiplier based on position in sigma window
|
||||
strength_mult = calculate_strength_multiplier(sigma_val, self.sigma_low, self.sigma_high, self.decay_mode)
|
||||
effective_strength = self.strength * strength_mult
|
||||
|
||||
if strength_mult <= 0:
|
||||
# Still need to pop img and txt as the original code does
|
||||
kwargs.pop("img", None)
|
||||
kwargs.pop("txt", None)
|
||||
return kwargs
|
||||
|
||||
x = kwargs.get("x")
|
||||
img = kwargs.get("img")
|
||||
img_input = kwargs.get("img_input")
|
||||
txt = kwargs.get("txt")
|
||||
pe = kwargs.get("pe")
|
||||
vec = kwargs.get("vec")
|
||||
spacial_compression = self.vae.spacial_compression_encode()
|
||||
if self.encoded_image is None or self.encoded_image_size != (x.shape[-2] * spacial_compression, x.shape[-1] * spacial_compression):
|
||||
image_scaled = comfy.utils.common_upscale(self.image.movedim(-1, 1), x.shape[-1] * spacial_compression, x.shape[-2] * spacial_compression, "area", "center")
|
||||
inpaint_scaled = None
|
||||
if self.inpaint_image is not None:
|
||||
inpaint_scaled = comfy.utils.common_upscale(self.inpaint_image.movedim(-1, 1), x.shape[-1] * spacial_compression, x.shape[-2] * spacial_compression, "area", "center").movedim(1, -1)
|
||||
loaded_models = comfy.model_management.loaded_models(only_currently_used=True)
|
||||
self.encoded_image = self.encode_latent_cond(image_scaled.movedim(1, -1), inpaint_scaled)
|
||||
self.encoded_image_size = (image_scaled.shape[-2], image_scaled.shape[-1])
|
||||
comfy.model_management.load_models_gpu(loaded_models)
|
||||
|
||||
cnet_blocks = self.model_patch.model.n_control_layers
|
||||
div = round(30 / cnet_blocks)
|
||||
|
||||
cnet_index = (block_index // div)
|
||||
cnet_index_float = (block_index / div)
|
||||
|
||||
kwargs.pop("img") # we do ops in place
|
||||
kwargs.pop("txt")
|
||||
|
||||
if cnet_index_float > (cnet_blocks - 1):
|
||||
self.temp_data = None
|
||||
return kwargs
|
||||
|
||||
if self.temp_data is None or self.temp_data[0] > cnet_index:
|
||||
if block_type == "noise_refiner":
|
||||
self.temp_data = (-3, (None, self.model_patch.model(txt, self.encoded_image.to(img.dtype), pe, vec)))
|
||||
else:
|
||||
self.temp_data = (-1, (None, self.model_patch.model(txt, self.encoded_image.to(img.dtype), pe, vec)))
|
||||
|
||||
if block_type == "noise_refiner":
|
||||
next_layer = self.temp_data[0] + 1
|
||||
self.temp_data = (next_layer, self.model_patch.model.forward_noise_refiner_block(block_index, self.temp_data[1][1], img_input[:, :self.temp_data[1][1].shape[1]], None, pe, vec))
|
||||
if self.temp_data[1][0] is not None:
|
||||
img[:, :self.temp_data[1][0].shape[1]] += (self.temp_data[1][0] * effective_strength)
|
||||
else:
|
||||
while self.temp_data[0] < cnet_index and (self.temp_data[0] + 1) < cnet_blocks:
|
||||
next_layer = self.temp_data[0] + 1
|
||||
self.temp_data = (next_layer, self.model_patch.model.forward_control_block(next_layer, self.temp_data[1][1], img_input[:, :self.temp_data[1][1].shape[1]], None, pe, vec))
|
||||
|
||||
if cnet_index_float == self.temp_data[0]:
|
||||
img[:, :self.temp_data[1][0].shape[1]] += (self.temp_data[1][0] * effective_strength)
|
||||
if cnet_blocks == self.temp_data[0] + 1:
|
||||
self.temp_data = None
|
||||
|
||||
return kwargs
|
||||
|
||||
def to(self, device_or_dtype):
|
||||
if isinstance(device_or_dtype, torch.device):
|
||||
self.encoded_image = self.encoded_image.to(device_or_dtype)
|
||||
self.temp_data = None
|
||||
return self
|
||||
|
||||
def models(self):
|
||||
return [self.model_patch]
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Main Node Class
|
||||
# ============================================================================
|
||||
|
||||
class TK3RQwenImageDiffsynthControlnetAdvanced:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": { "model": ("MODEL",),
|
||||
"model_patch": ("MODEL_PATCH",),
|
||||
"vae": ("VAE",),
|
||||
"image": ("IMAGE",),
|
||||
"strength": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
|
||||
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01}),
|
||||
"stop_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
|
||||
"decay": (DECAY_MODES, {"default": "none", "tooltip": "Strength decay curve: none=instant cutoff, linear=even decay, cosine=smooth S-curve, exponential=fast initial decay, inverse_exponential=slow initial decay"}),
|
||||
},
|
||||
"optional": {"mask": ("MASK",)}}
|
||||
RETURN_TYPES = ("MODEL",)
|
||||
FUNCTION = "diffsynth_controlnet"
|
||||
|
||||
CATEGORY = "TK3R/Advanced"
|
||||
|
||||
def diffsynth_controlnet(self, model, model_patch, vae, image, strength, start_percent=0.0, stop_percent=1.0, decay="none", mask=None):
|
||||
model_patched = model.clone()
|
||||
image = image[:, :, :, :3]
|
||||
model_sampling = model.get_model_object("model_sampling")
|
||||
if model_sampling is None:
|
||||
sigma_low, sigma_high = float("-inf"), float("inf")
|
||||
else:
|
||||
sigma_low, sigma_high = resolve_sigma_window(model_sampling, start_percent, stop_percent)
|
||||
if mask is not None:
|
||||
if mask.ndim == 3:
|
||||
mask = mask.unsqueeze(1)
|
||||
if mask.ndim == 4:
|
||||
mask = mask.unsqueeze(2)
|
||||
mask = 1.0 - mask
|
||||
|
||||
if isinstance(model_patch.model, comfy.ldm.lumina.controlnet.ZImage_Control):
|
||||
patch = ZImageControlPatch(model_patch, vae, image, strength, mask=mask, sigma_low=sigma_low, sigma_high=sigma_high, start_percent=start_percent, stop_percent=stop_percent, decay_mode=decay)
|
||||
model_patched.set_model_noise_refiner_patch(patch)
|
||||
model_patched.set_model_double_block_patch(patch)
|
||||
else:
|
||||
model_patched.set_model_double_block_patch(DiffSynthCnetPatch(model_patch, vae, image, strength, mask, sigma_low, sigma_high, start_percent, stop_percent, decay))
|
||||
return (model_patched,)
|
||||
|
||||
class TK3RZImageFunControlnet(TK3RQwenImageDiffsynthControlnetAdvanced):
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": { "model": ("MODEL",),
|
||||
"model_patch": ("MODEL_PATCH",),
|
||||
"vae": ("VAE",),
|
||||
"strength": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
|
||||
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01}),
|
||||
"stop_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
|
||||
"decay": (DECAY_MODES, {"default": "none", "tooltip": "Strength decay curve: none=instant cutoff, linear=even decay, cosine=smooth S-curve, exponential=fast initial decay, inverse_exponential=slow initial decay"}),
|
||||
},
|
||||
"optional": {"image": ("IMAGE",), "inpaint_image": ("IMAGE",), "mask": ("MASK",)}}
|
||||
|
||||
CATEGORY = "TK3R/Advanced"
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Node Registration
|
||||
# ============================================================================
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3RQwenImageDiffsynthControlnetAdvanced": TK3RQwenImageDiffsynthControlnetAdvanced,
|
||||
"TK3RZImageFunControlnet": TK3RZImageFunControlnet,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3RQwenImageDiffsynthControlnetAdvanced": "TK3R Qwen Image DiffSynth ControlNet Advanced (Custom)",
|
||||
"TK3RZImageFunControlnet": "TK3R ZImage Fun ControlNet (Custom)",
|
||||
}
|
||||
@@ -0,0 +1,74 @@
|
||||
import node_helpers
|
||||
import comfy.utils
|
||||
import math
|
||||
from typing_extensions import override
|
||||
from comfy_api.latest import ComfyExtension, io
|
||||
|
||||
class TK3RTextEncodeQwenImageEditPlus:
|
||||
"""
|
||||
This an enhanced version of the TextEncodeQwenImageEditPlus node, it is NOT my code, I originally got it from some repo and it was supposed to just overwrite the original file but this is not a good approach with all the constant Comfy updates, so I have added it as a separate node in my repo.
|
||||
"""
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"clip": ("CLIP", ),
|
||||
"prompt": ("STRING", {"multiline": True, "dynamicPrompts": True}),
|
||||
},
|
||||
"optional": {
|
||||
"vae": ("VAE", ),
|
||||
"image1": ("IMAGE", ),
|
||||
"image2": ("IMAGE", ),
|
||||
"image3": ("IMAGE", ),
|
||||
"image4": ("IMAGE", ),
|
||||
"target_latent": ("LATENT", ),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("CONDITIONING",)
|
||||
RETURN_NAMES = ("conditioning",)
|
||||
FUNCTION = "execute"
|
||||
CATEGORY = "TK3R/Advanced"
|
||||
|
||||
def execute(self, clip, prompt, vae=None, image1=None, image2=None, image3=None, image4=None, target_latent=None):
|
||||
ref_latents = []
|
||||
images = [image1, image2, image3, image4]
|
||||
images_vl = []
|
||||
llama_template = "<|im_start|>system\nDescribe key details of the input image (including any objects, characters, poses, facial features, clothing, setting, textures and style), then explain how the user's text instruction should alter, modify or recreate the image. Generate a new image that meets the user's requirements, which can vary from a small change to a completely new image using inputs as a guide.<|im_end|>\n<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n"
|
||||
image_prompt = ""
|
||||
|
||||
for i, image in enumerate(images):
|
||||
if image is not None:
|
||||
samples = image.movedim(-1, 1)
|
||||
total = int(384 * 384)
|
||||
|
||||
scale_by = math.sqrt(total / (samples.shape[3] * samples.shape[2]))
|
||||
width = round(samples.shape[3] * scale_by)
|
||||
height = round(samples.shape[2] * scale_by)
|
||||
|
||||
s = comfy.utils.common_upscale(samples, width, height, "lanczos", "center")
|
||||
images_vl.append(s.movedim(1, -1))
|
||||
if vae is not None:
|
||||
if target_latent is not None:
|
||||
twidth = target_latent["samples"].shape[-1] * 8
|
||||
theight = target_latent["samples"].shape[-2] * 8
|
||||
s = comfy.utils.common_upscale(samples, twidth, theight, "lanczos", "center")
|
||||
else:
|
||||
s = samples
|
||||
ref_latents.append(vae.encode(s.movedim(1, -1)[:, :, :, :3]))
|
||||
|
||||
image_prompt += "Picture {}: <|vision_start|><|image_pad|><|vision_end|>".format(i + 1)
|
||||
|
||||
tokens = clip.tokenize(image_prompt + prompt, images=images_vl, llama_template=llama_template)
|
||||
conditioning = clip.encode_from_tokens_scheduled(tokens)
|
||||
if len(ref_latents) > 0:
|
||||
conditioning = node_helpers.conditioning_set_values(conditioning, {"reference_latents": ref_latents}, append=True)
|
||||
return (conditioning,)
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3RTextEncodeQwenImageEditPlusExt": TK3RTextEncodeQwenImageEditPlus
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3RTextEncodeQwenImageEditPlusExt": "TK3R TextEncodeQwenImageEditPlus Ext"
|
||||
}
|
||||
@@ -0,0 +1,158 @@
|
||||
import torch
|
||||
|
||||
|
||||
class TK3RCLIPTextEncodeWithTokenCount:
|
||||
"""
|
||||
CLIPTextEncode with added token count output.
|
||||
Encodes text and returns both the conditioning and token count.
|
||||
"""
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"text": ("STRING", {
|
||||
"multiline": True,
|
||||
"default": "",
|
||||
"dynamicPrompts": True,
|
||||
"tooltip": "The text to be encoded."
|
||||
}),
|
||||
"clip": ("CLIP", {"tooltip": "The CLIP model used for encoding the text."}),
|
||||
"system_prompt": (list(cls.SYSTEM_PROMPT.keys()), {"default": "none", "tooltip": "System prompt for Lumina2 models. Use 'none' for other models."}),
|
||||
}
|
||||
}
|
||||
|
||||
SYSTEM_PROMPT = {
|
||||
"none": "",
|
||||
"lumina2: superior": "You are an assistant designed to generate superior images with the superior "\
|
||||
"degree of image-text alignment based on textual prompts or user prompts.",
|
||||
"lumina2: alignment": "You are an assistant designed to generate high-quality images with the "\
|
||||
"highest degree of image-text alignment based on textual prompts."
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("CONDITIONING", "INT", "STRING")
|
||||
RETURN_NAMES = ("conditioning", "token_count", "info")
|
||||
FUNCTION = "encode"
|
||||
CATEGORY = "TK3R/Utility"
|
||||
OUTPUT_NODE = True
|
||||
DESCRIPTION = "Encodes text prompt and outputs the conditioning along with token count information."
|
||||
|
||||
def encode(self, clip, text, system_prompt="none"):
|
||||
if clip is None:
|
||||
raise RuntimeError("ERROR: clip input is invalid: None\n\nIf the clip is from a checkpoint loader node your checkpoint does not contain a valid clip or text encoder model.")
|
||||
|
||||
# Apply system prompt if selected
|
||||
if system_prompt != "none":
|
||||
sys_prompt_text = self.SYSTEM_PROMPT[system_prompt]
|
||||
text = f'{sys_prompt_text} <Prompt Start> {text}'
|
||||
|
||||
# Tokenize the text
|
||||
tokens = clip.tokenize(text)
|
||||
|
||||
# Count tokens
|
||||
token_counts = {}
|
||||
total_tokens = 0
|
||||
|
||||
for key, token_data in tokens.items():
|
||||
count = 0
|
||||
|
||||
if isinstance(token_data, torch.Tensor):
|
||||
# Direct tensor: count non-padding tokens
|
||||
# For CLIP tokenizers, structure is: [start_token, ...content..., end_token, pad, pad, ...]
|
||||
# Common values: start=49406, end=49407, pad=49407
|
||||
flat_tokens = token_data.flatten()
|
||||
|
||||
# Skip the start token (first token)
|
||||
tokens_to_check = flat_tokens[1:] if len(flat_tokens) > 1 else flat_tokens
|
||||
|
||||
for i, token_id in enumerate(tokens_to_check):
|
||||
tid = token_id.item()
|
||||
|
||||
# Check if this is an end/pad token by looking ahead
|
||||
# If we see the same token repeated to the end, it's padding
|
||||
if i < len(tokens_to_check) - 1:
|
||||
# Check if all remaining tokens are the same (padding pattern)
|
||||
remaining = tokens_to_check[i:]
|
||||
if len(remaining) > 1 and all(t.item() == tid for t in remaining):
|
||||
# This is the start of padding, include current token as end token
|
||||
count += 1
|
||||
break
|
||||
|
||||
count += 1
|
||||
|
||||
# Add 1 for the start token
|
||||
count += 1
|
||||
|
||||
elif isinstance(token_data, list):
|
||||
# Handle nested list structures
|
||||
if len(token_data) > 0:
|
||||
inner_data = token_data[0]
|
||||
|
||||
if isinstance(inner_data, list):
|
||||
# Nested list structure (SDXL format: [[token_ids], [weights]])
|
||||
# Count non-padding tokens by looking for repeating end token pattern
|
||||
for i, token_id in enumerate(inner_data):
|
||||
# Check if remaining tokens are all the same (padding pattern)
|
||||
if i > 0 and i < len(inner_data) - 1:
|
||||
remaining = inner_data[i:]
|
||||
if len(remaining) > 1 and all(t == token_id for t in remaining):
|
||||
# Found padding start, include current token as end token
|
||||
count = i + 1
|
||||
break
|
||||
|
||||
# If no padding pattern found, use full length
|
||||
if count == 0:
|
||||
count = len(inner_data)
|
||||
elif isinstance(inner_data, torch.Tensor):
|
||||
# List containing tensor
|
||||
flat_tokens = inner_data.flatten()
|
||||
|
||||
# Skip start token
|
||||
tokens_to_check = flat_tokens[1:] if len(flat_tokens) > 1 else flat_tokens
|
||||
|
||||
for i, token_id in enumerate(tokens_to_check):
|
||||
tid = token_id.item() if isinstance(token_id, torch.Tensor) else token_id
|
||||
|
||||
# Check for padding pattern
|
||||
if i < len(tokens_to_check) - 1:
|
||||
remaining = tokens_to_check[i:]
|
||||
if len(remaining) > 1:
|
||||
remaining_vals = [t.item() if isinstance(t, torch.Tensor) else t for t in remaining]
|
||||
if all(v == tid for v in remaining_vals):
|
||||
count += 1
|
||||
break
|
||||
|
||||
count += 1
|
||||
|
||||
# Add 1 for start token
|
||||
count += 1
|
||||
else:
|
||||
# Direct list of tokens
|
||||
count = len(token_data)
|
||||
|
||||
token_counts[key] = count
|
||||
total_tokens = max(total_tokens, count)
|
||||
|
||||
# Build info string
|
||||
info_lines = [f"Total tokens: {total_tokens}"]
|
||||
info_lines.append(f"Text length: {len(text)} characters")
|
||||
|
||||
if len(token_counts) > 1:
|
||||
info_lines.append(f"\nTokenizer breakdown:")
|
||||
for key, count in token_counts.items():
|
||||
info_lines.append(f" {key}: {count} tokens")
|
||||
|
||||
info_string = "\n".join(info_lines)
|
||||
|
||||
# Encode from tokens (same as CLIPTextEncode)
|
||||
conditioning = clip.encode_from_tokens_scheduled(tokens)
|
||||
|
||||
return {"ui": {"text": [info_string]}, "result": (conditioning, total_tokens, info_string)}
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3R CLIP Text Encode With Token Count": TK3RCLIPTextEncodeWithTokenCount,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3R CLIP Text Encode With Token Count": "TK3R CLIP Text Encode With Token Count",
|
||||
}
|
||||
@@ -0,0 +1,213 @@
|
||||
import logging
|
||||
import math
|
||||
import torch
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
DECAY_MODES = ["none", "linear", "cosine", "exponential", "inverse_exponential"]
|
||||
|
||||
|
||||
def _clamp_percent(value: float) -> float:
|
||||
return max(0.0, min(1.0, float(value)))
|
||||
|
||||
|
||||
def _sigma_from_percent(model_sampling, percent: float) -> float:
|
||||
sigma = model_sampling.percent_to_sigma(percent)
|
||||
if isinstance(sigma, torch.Tensor):
|
||||
sigma = float(sigma.detach().cpu())
|
||||
return float(sigma)
|
||||
|
||||
|
||||
def resolve_sigma_window(model_sampling, start_percent: float, end_percent: float):
|
||||
start = _clamp_percent(start_percent)
|
||||
end = _clamp_percent(end_percent)
|
||||
sigma_start = _sigma_from_percent(model_sampling, start)
|
||||
sigma_end = _sigma_from_percent(model_sampling, end)
|
||||
sigma_high = max(sigma_start, sigma_end)
|
||||
sigma_low = min(sigma_start, sigma_end)
|
||||
if math.isclose(sigma_high, sigma_low, rel_tol=1e-6, abs_tol=1e-9):
|
||||
sigma_high += 1e-9
|
||||
return sigma_low, sigma_high
|
||||
|
||||
|
||||
def current_sigma(transformer_options):
|
||||
if not isinstance(transformer_options, dict):
|
||||
return None
|
||||
sigma_tensor = transformer_options.get("sigmas")
|
||||
if not isinstance(sigma_tensor, torch.Tensor) or sigma_tensor.numel() == 0:
|
||||
return None
|
||||
return float(sigma_tensor.reshape(-1)[0].item())
|
||||
|
||||
|
||||
def calculate_strength_multiplier(sigma_val, sigma_low, sigma_high, decay_mode="none"):
|
||||
if sigma_val is None:
|
||||
return 1.0
|
||||
|
||||
if sigma_val < sigma_low - 1e-9:
|
||||
return 0.0
|
||||
if sigma_val > sigma_high + 1e-9:
|
||||
return 0.0 if decay_mode != "none" else 1.0
|
||||
|
||||
if decay_mode == "none":
|
||||
return 1.0
|
||||
|
||||
if sigma_high <= sigma_low:
|
||||
return 1.0
|
||||
|
||||
t = (sigma_val - sigma_low) / (sigma_high - sigma_low)
|
||||
t = max(0.0, min(1.0, t))
|
||||
|
||||
if decay_mode == "linear":
|
||||
return t
|
||||
if decay_mode == "cosine":
|
||||
return (1.0 - math.cos(t * math.pi)) / 2.0
|
||||
if decay_mode == "exponential":
|
||||
return 1.0 - math.exp(-3.0 * t) / (1.0 - math.exp(-3.0)) if t > 0 else 0.0
|
||||
if decay_mode == "inverse_exponential":
|
||||
return (math.exp(3.0 * t) - 1.0) / (math.exp(3.0) - 1.0)
|
||||
return 1.0
|
||||
|
||||
|
||||
class DecayControlNetWrapper:
|
||||
"""Scales control outputs per step using sigma-window decay.
|
||||
|
||||
Transparently wraps a controlnet and delegates all attributes/methods to it,
|
||||
except get_control which applies decay-based strength scaling.
|
||||
"""
|
||||
|
||||
def __init__(self, inner, start_percent: float, end_percent: float, decay_mode: str):
|
||||
object.__setattr__(self, 'inner', inner)
|
||||
object.__setattr__(self, 'start_percent', start_percent)
|
||||
object.__setattr__(self, 'end_percent', end_percent)
|
||||
object.__setattr__(self, 'decay_mode', decay_mode)
|
||||
object.__setattr__(self, 'sigma_low', float("-inf"))
|
||||
object.__setattr__(self, 'sigma_high', float("inf"))
|
||||
|
||||
def __getattr__(self, name):
|
||||
"""Delegate attribute access to inner controlnet."""
|
||||
return getattr(self.inner, name)
|
||||
|
||||
def __setattr__(self, name, value):
|
||||
"""Delegate attribute setting to inner controlnet, except internal state."""
|
||||
if name in ('inner', 'start_percent', 'end_percent', 'decay_mode', 'sigma_low', 'sigma_high'):
|
||||
object.__setattr__(self, name, value)
|
||||
else:
|
||||
setattr(self.inner, name, value)
|
||||
|
||||
def pre_run(self, model, percent_to_timestep_function):
|
||||
try:
|
||||
sampling = getattr(model, "model_sampling", None)
|
||||
if sampling is not None:
|
||||
self.sigma_low, self.sigma_high = resolve_sigma_window(sampling, self.start_percent, self.end_percent)
|
||||
except Exception as e:
|
||||
logger.warning("DecayControlNetWrapper: failed to resolve sigma window (%s)", e)
|
||||
return self.inner.pre_run(model, percent_to_timestep_function)
|
||||
|
||||
def get_control(self, x_noisy, t, cond, batched_number, transformer_options):
|
||||
ctrl = self.inner.get_control(x_noisy, t, cond, batched_number, transformer_options)
|
||||
if ctrl is None:
|
||||
return None
|
||||
|
||||
sigma_val = current_sigma(transformer_options)
|
||||
mult = calculate_strength_multiplier(sigma_val, self.sigma_low, self.sigma_high, self.decay_mode)
|
||||
if mult == 1.0:
|
||||
return ctrl
|
||||
if mult == 0.0:
|
||||
return None
|
||||
|
||||
try:
|
||||
for key in ctrl:
|
||||
arr = ctrl[key]
|
||||
for i, x in enumerate(arr):
|
||||
if x is not None:
|
||||
arr[i] = x * mult
|
||||
except Exception as e:
|
||||
logger.warning("DecayControlNetWrapper: scaling failed (%s)", e)
|
||||
return ctrl
|
||||
|
||||
def cleanup(self):
|
||||
return self.inner.cleanup()
|
||||
|
||||
def get_models(self):
|
||||
return self.inner.get_models()
|
||||
|
||||
def get_extra_hooks(self):
|
||||
return self.inner.get_extra_hooks()
|
||||
|
||||
def inference_memory_requirements(self, dtype):
|
||||
return self.inner.inference_memory_requirements(dtype)
|
||||
|
||||
def copy(self):
|
||||
return DecayControlNetWrapper(self.inner.copy(), self.start_percent, self.end_percent, self.decay_mode)
|
||||
|
||||
def set_previous_controlnet(self, prev):
|
||||
self.inner.set_previous_controlnet(prev)
|
||||
return self
|
||||
|
||||
def set_cond_hint(self, *args, **kwargs):
|
||||
return self.inner.set_cond_hint(*args, **kwargs)
|
||||
|
||||
class TK3RControlNetApplyAdvanced:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"positive": ("CONDITIONING", ),
|
||||
"negative": ("CONDITIONING", ),
|
||||
"control_net": ("CONTROL_NET", ),
|
||||
"image": ("IMAGE", ),
|
||||
"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
|
||||
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
|
||||
"end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
|
||||
"decay": (DECAY_MODES, {"default": "none", "tooltip": "Strength decay: none, linear, cosine, exponential, inverse_exponential."}),
|
||||
},
|
||||
"optional": {
|
||||
"vae": ("VAE", ),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("CONDITIONING","CONDITIONING")
|
||||
RETURN_NAMES = ("positive", "negative")
|
||||
FUNCTION = "apply_controlnet"
|
||||
|
||||
CATEGORY = "TK3R/Advanced"
|
||||
|
||||
def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent, decay="none", vae=None, extra_concat=[]):
|
||||
if strength == 0:
|
||||
return (positive, negative)
|
||||
|
||||
control_hint = image.movedim(-1,1)
|
||||
cnets = {}
|
||||
|
||||
out = []
|
||||
for conditioning in [positive, negative]:
|
||||
c = []
|
||||
for t in conditioning:
|
||||
d = t[1].copy()
|
||||
|
||||
prev_cnet = d.get('control', None)
|
||||
if prev_cnet in cnets:
|
||||
c_net = cnets[prev_cnet]
|
||||
else:
|
||||
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat)
|
||||
c_net.set_previous_controlnet(prev_cnet)
|
||||
if decay != "none":
|
||||
c_net = DecayControlNetWrapper(c_net, start_percent, end_percent, decay)
|
||||
cnets[prev_cnet] = c_net
|
||||
|
||||
d['control'] = c_net
|
||||
d['control_apply_to_uncond'] = False
|
||||
n = [t[0], d]
|
||||
c.append(n)
|
||||
out.append(c)
|
||||
return (out[0], out[1])
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3R ControlNet Apply Advanced": TK3RControlNetApplyAdvanced,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3R ControlNet Apply Advanced": "TK3R ControlNet Apply Advanced",
|
||||
}
|
||||
@@ -0,0 +1,46 @@
|
||||
import torch
|
||||
|
||||
|
||||
class TK3RImageCompare:
|
||||
"""
|
||||
Node that outputs both current and previous image inputs.
|
||||
Useful for comparing consecutive frames or tracking image changes.
|
||||
"""
|
||||
# Class-level cache to store the last image
|
||||
_last_image = {}
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": { "image": ("IMAGE",)}}
|
||||
|
||||
RETURN_TYPES = ("IMAGE", "IMAGE")
|
||||
RETURN_NAMES = ("current", "previous")
|
||||
FUNCTION = "compare"
|
||||
|
||||
CATEGORY = "TK3R/Utility"
|
||||
|
||||
def compare(self, image):
|
||||
# Generate a unique key for this node instance
|
||||
# Using id(self) to track per-instance
|
||||
instance_id = id(self)
|
||||
|
||||
# Get the previous image for this instance, if it exists
|
||||
if instance_id in TK3RImageCompare._last_image:
|
||||
previous = TK3RImageCompare._last_image[instance_id]
|
||||
else:
|
||||
# First run - return current image for both outputs
|
||||
previous = image
|
||||
|
||||
# Store current image as the new "last" image for next run
|
||||
TK3RImageCompare._last_image[instance_id] = image.clone()
|
||||
|
||||
return (image, previous)
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3R Image Compare": TK3RImageCompare,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3R Image Compare": "TK3R Image Compare",
|
||||
}
|
||||
@@ -0,0 +1,89 @@
|
||||
"""
|
||||
LoRA Rank Reader Node
|
||||
|
||||
A ComfyUI node that reads and displays the rank of a LoRA safetensors file.
|
||||
"""
|
||||
|
||||
from safetensors import safe_open
|
||||
import os
|
||||
|
||||
import folder_paths
|
||||
|
||||
|
||||
class TK3RLoRARankReader:
|
||||
"""
|
||||
Reads a LoRA .safetensors file and outputs information about its rank.
|
||||
|
||||
The rank (r) is the bottleneck dimension in LoRA matrices, which determines
|
||||
the model's capacity and file size.
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"lora_name": (folder_paths.get_filename_list("loras"), {"tooltip": "The name of the LoRA."}),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("info",)
|
||||
FUNCTION = "read_rank"
|
||||
CATEGORY = "TK3R/Utility"
|
||||
DESCRIPTION = "Reads and displays the rank of a LoRA safetensors file."
|
||||
OUTPUT_NODE = True
|
||||
|
||||
def read_rank(self, lora_name):
|
||||
lora_path = folder_paths.get_full_path_or_raise("loras", lora_name)
|
||||
|
||||
try:
|
||||
with safe_open(lora_path, framework="pt") as f:
|
||||
# Search for the first 'A' or 'down' matrix to identify the rank
|
||||
# These matrices have the shape (rank, original_dimension)
|
||||
keys = f.keys()
|
||||
target_key = next((k for k in keys if "lora_A" in k or "lora_down" in k), None)
|
||||
|
||||
if target_key:
|
||||
tensor_shape = f.get_slice(target_key).get_shape()
|
||||
# The rank 'r' is the smaller bottleneck dimension, typically the first index
|
||||
rank = tensor_shape[0]
|
||||
|
||||
info_lines = [
|
||||
f"=== LoRA Analysis ===",
|
||||
f"File: {os.path.basename(lora_path)}",
|
||||
f"Rank (r): {rank}",
|
||||
f"Sample key: {target_key}",
|
||||
f"Tensor shape: {tensor_shape}"
|
||||
]
|
||||
|
||||
# Check for Alpha in metadata if it exists
|
||||
metadata = f.metadata()
|
||||
if metadata and 'ss_network_alpha' in metadata:
|
||||
info_lines.append(f"Network Alpha: {metadata['ss_network_alpha']}")
|
||||
|
||||
# Count total LoRA layers
|
||||
lora_layer_count = len([k for k in keys if "lora_A" in k or "lora_down" in k])
|
||||
info_lines.append(f"Total LoRA layers: {lora_layer_count}")
|
||||
|
||||
info_text = "\n".join(info_lines)
|
||||
print(info_text)
|
||||
return (info_text,)
|
||||
else:
|
||||
error_msg = f"Error: Could not find LoRA weight matrices in {lora_path}"
|
||||
print(error_msg)
|
||||
return (error_msg,)
|
||||
|
||||
except Exception as e:
|
||||
error_msg = f"Error opening file: {str(e)}"
|
||||
print(error_msg)
|
||||
return (error_msg,)
|
||||
|
||||
|
||||
# Register nodes
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3RLoRARankReader": TK3RLoRARankReader,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3RLoRARankReader": "LoRA Rank Reader",
|
||||
}
|
||||
@@ -0,0 +1,114 @@
|
||||
"""
|
||||
Safetensors Precision Reader Node
|
||||
|
||||
A ComfyUI node that reads and displays the floating-point precision of a safetensors file.
|
||||
"""
|
||||
|
||||
import os
|
||||
import logging
|
||||
import traceback
|
||||
|
||||
import folder_paths
|
||||
|
||||
|
||||
class TK3RSafetensorsPrecisionReader:
|
||||
"""
|
||||
Reads a safetensors file and reports the floating-point precision used (fp8, fp16, bf16, fp32, etc.)
|
||||
"""
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"file_path": ("STRING", {"default": "", "multiline": False, "tooltip": "Full path to safetensors file"}),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("PRECISION_INFO",)
|
||||
FUNCTION = "read_precision"
|
||||
CATEGORY = "TK3R/Utility"
|
||||
OUTPUT_NODE = True
|
||||
|
||||
def read_precision(self, file_path):
|
||||
import safetensors.torch
|
||||
|
||||
try:
|
||||
# If relative path provided, try to resolve from models folder
|
||||
if not os.path.isabs(file_path):
|
||||
models_dir = folder_paths.get_folder_paths("checkpoints")[0]
|
||||
models_dir = os.path.dirname(models_dir) # Go up to models folder
|
||||
file_path = os.path.join(models_dir, file_path)
|
||||
|
||||
logging.info(f"\n[TK3R Sft Precision Reader] Reading file: {file_path}")
|
||||
|
||||
dtype_counts = {}
|
||||
total_tensors = 0
|
||||
|
||||
with safetensors.torch.safe_open(file_path, framework="pt") as f:
|
||||
keys = list(f.keys())
|
||||
total_tensors = len(keys)
|
||||
|
||||
logging.info(f" Total tensors: {total_tensors}")
|
||||
|
||||
for key in keys:
|
||||
tensor = f.get_tensor(key)
|
||||
dtype_str = str(tensor.dtype).replace('torch.', '')
|
||||
|
||||
if dtype_str not in dtype_counts:
|
||||
dtype_counts[dtype_str] = 0
|
||||
dtype_counts[dtype_str] += 1
|
||||
|
||||
# Determine primary precision
|
||||
if not dtype_counts:
|
||||
return ("ERROR: No tensors found in file",)
|
||||
|
||||
# Sort by count to find most common dtype
|
||||
sorted_dtypes = sorted(dtype_counts.items(), key=lambda x: x[1], reverse=True)
|
||||
primary_dtype = sorted_dtypes[0][0]
|
||||
primary_count = sorted_dtypes[0][1]
|
||||
|
||||
# Map torch dtypes to common names
|
||||
precision_map = {
|
||||
'float32': 'fp32',
|
||||
'float16': 'fp16',
|
||||
'bfloat16': 'bf16',
|
||||
'float8_e4m3fn': 'fp8 (e4m3)',
|
||||
'float8_e5m2': 'fp8 (e5m2)',
|
||||
'int8': 'int8',
|
||||
'uint8': 'uint8',
|
||||
}
|
||||
|
||||
primary_precision = precision_map.get(primary_dtype, primary_dtype)
|
||||
|
||||
# Build detailed info
|
||||
info_lines = [
|
||||
f"File: {os.path.basename(file_path)}",
|
||||
f"Primary Precision: {primary_precision}",
|
||||
f"Total Tensors: {total_tensors}",
|
||||
"\nPrecision Breakdown:"
|
||||
]
|
||||
|
||||
for dtype, count in sorted_dtypes:
|
||||
precision_name = precision_map.get(dtype, dtype)
|
||||
percentage = (count / total_tensors) * 100
|
||||
info_lines.append(f" {precision_name}: {count} tensors ({percentage:.1f}%)")
|
||||
|
||||
result = "\n".join(info_lines)
|
||||
logging.info(f"\n[TK3R Sft Precision Reader] Result:\n{result}")
|
||||
|
||||
return (result,)
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"ERROR: {str(e)}\n{traceback.format_exc()}"
|
||||
logging.error(f"\n[TK3R Sft Precision Reader] {error_message}")
|
||||
return (error_message,)
|
||||
|
||||
|
||||
# Register nodes
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3R Safetensors Precision Reader": TK3RSafetensorsPrecisionReader,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3RSafetensorsPrecisionReader": "TK3R Safetensors Precision Reader",
|
||||
}
|
||||
@@ -0,0 +1,213 @@
|
||||
import logging
|
||||
import math
|
||||
import torch
|
||||
import comfy.samplers
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class Guider_CFGSchedule(comfy.samplers.CFGGuider):
|
||||
def set_cfg_schedule(self, schedule):
|
||||
if isinstance(schedule, list):
|
||||
schedule = torch.tensor(schedule, dtype=torch.float32)
|
||||
self.cfg_schedule = schedule
|
||||
self.last_sigma_idx = None
|
||||
# Set cfg to the first value for compatibility
|
||||
if len(schedule) > 0:
|
||||
self.cfg = float(schedule[0].item())
|
||||
|
||||
def predict_noise(self, x, timestep, model_options={}, seed=None):
|
||||
sched_len = int(self.cfg_schedule.shape[-1]) if hasattr(self, "cfg_schedule") else 0
|
||||
if sched_len == 0:
|
||||
cond_scale = self.cfg
|
||||
else:
|
||||
current_sigma = timestep[0].item() if isinstance(timestep, torch.Tensor) else timestep[0]
|
||||
|
||||
# Find which step range this sigma falls in
|
||||
try:
|
||||
sample_sigmas = model_options["transformer_options"]["sample_sigmas"]
|
||||
# Sigmas are in descending order. Find where current_sigma fits
|
||||
sigma_idx = 0
|
||||
for i in range(len(sample_sigmas) - 1):
|
||||
if current_sigma >= sample_sigmas[i + 1]:
|
||||
sigma_idx = i
|
||||
break
|
||||
sigma_idx = i + 1
|
||||
except Exception as e:
|
||||
logger.warning(f"Could not get sample_sigmas: {e}, using index 0")
|
||||
sigma_idx = 0
|
||||
|
||||
# Only log when sigma_idx changes (new actual step)
|
||||
if self.last_sigma_idx is None or sigma_idx != self.last_sigma_idx:
|
||||
self.last_sigma_idx = sigma_idx
|
||||
step_idx = min(sigma_idx, sched_len - 1)
|
||||
logger.info(f"[CFG Schedule] Step {sigma_idx}: CFG = {float(self.cfg_schedule[step_idx].item()):.1f} (sigma={current_sigma:.4f})")
|
||||
|
||||
step_idx = min(sigma_idx, sched_len - 1)
|
||||
cond_scale = float(self.cfg_schedule[step_idx].item())
|
||||
|
||||
negative_cond = self.conds.get("negative", None)
|
||||
positive_cond = self.conds.get("positive", None)
|
||||
return comfy.samplers.sampling_function(self.inner_model, x, timestep, negative_cond, positive_cond, cond_scale, model_options=model_options, seed=seed)
|
||||
|
||||
class TK3RCFGScheduleGuider:
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"model": ("MODEL",),
|
||||
"positive": ("CONDITIONING",),
|
||||
"negative": ("CONDITIONING",),
|
||||
"cfg_schedule": ("STRING", {"default": "3.0, 2.0, 1.5, 1.0", "multiline": False}),
|
||||
"interpolate_steps": ("INT", {"default": 0, "min": 0, "max": 1000, "step": 1}),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("GUIDER", "SIGMAS", "SIGMAS")
|
||||
RETURN_NAMES = ("guider", "schedule", "normalized_schedule")
|
||||
FUNCTION = "execute"
|
||||
CATEGORY = "TK3R/Advanced"
|
||||
|
||||
def execute(self, model, positive, negative, cfg_schedule, interpolate_steps):
|
||||
# Parse the string into a list of floats
|
||||
try:
|
||||
cfg_values = [float(x.strip()) for x in cfg_schedule.split(',')]
|
||||
logger.info(f"[CFG Schedule] Parsed CFG schedule: {[f'{x:.1f}' for x in cfg_values]}")
|
||||
|
||||
# Interpolate if steps > 0
|
||||
if interpolate_steps > 0:
|
||||
cfg_values = self._interpolate_schedule(cfg_values, interpolate_steps)
|
||||
logger.info(f"[CFG Schedule] Interpolated to {interpolate_steps} steps: {[f'{x:.1f}' for x in cfg_values]}")
|
||||
|
||||
cfg_tensor = torch.tensor(cfg_values, dtype=torch.float32)
|
||||
except (ValueError, AttributeError) as e:
|
||||
logger.warning(f"Failed to parse cfg_schedule '{cfg_schedule}': {e}. Using default 8.0")
|
||||
cfg_tensor = torch.tensor([8.0], dtype=torch.float32)
|
||||
|
||||
guider = Guider_CFGSchedule(model)
|
||||
guider.set_conds(positive, negative)
|
||||
guider.set_cfg_schedule(cfg_tensor)
|
||||
|
||||
# Create normalized schedule (0-1 range)
|
||||
min_cfg = cfg_tensor.min()
|
||||
max_cfg = cfg_tensor.max()
|
||||
if max_cfg > min_cfg:
|
||||
normalized_schedule = (cfg_tensor - min_cfg) / (max_cfg - min_cfg)
|
||||
else:
|
||||
# All values are the same, normalize to 1.0
|
||||
normalized_schedule = torch.ones_like(cfg_tensor)
|
||||
|
||||
return (guider, cfg_tensor, normalized_schedule)
|
||||
|
||||
def _interpolate_schedule(self, values, steps):
|
||||
"""Interpolate the schedule values over the specified number of steps."""
|
||||
if len(values) == 1:
|
||||
# Single value, repeat it
|
||||
return values * steps
|
||||
|
||||
if steps == len(values):
|
||||
# Already the right length
|
||||
return values
|
||||
|
||||
# Create interpolated values
|
||||
input_indices = torch.linspace(0, len(values) - 1, len(values))
|
||||
output_indices = torch.linspace(0, len(values) - 1, steps)
|
||||
|
||||
# Linear interpolation
|
||||
values_tensor = torch.tensor(values, dtype=torch.float32)
|
||||
interpolated = torch.zeros(steps, dtype=torch.float32)
|
||||
|
||||
for i, out_idx in enumerate(output_indices):
|
||||
# Find the two surrounding input indices
|
||||
left_idx = int(torch.floor(out_idx).item())
|
||||
right_idx = min(left_idx + 1, len(values) - 1)
|
||||
|
||||
# Calculate interpolation weight
|
||||
if left_idx == right_idx:
|
||||
interpolated[i] = values_tensor[left_idx]
|
||||
else:
|
||||
weight = out_idx - left_idx
|
||||
interpolated[i] = values_tensor[left_idx] * (1 - weight) + values_tensor[right_idx] * weight
|
||||
|
||||
return interpolated.tolist()
|
||||
|
||||
|
||||
class Guider_CFGSigmaInterpolate(comfy.samplers.CFGGuider):
|
||||
def set_sigma_schedule(self, start_cfg, end_cfg, linear_blend):
|
||||
self.start_cfg = start_cfg
|
||||
self.end_cfg = end_cfg
|
||||
self.linear_blend = linear_blend
|
||||
# Set cfg for compatibility
|
||||
self.cfg = start_cfg
|
||||
|
||||
def predict_noise(self, x, timestep, model_options={}, seed=None):
|
||||
current_sigma = timestep[0].item() if isinstance(timestep, torch.Tensor) else timestep[0]
|
||||
|
||||
# Sigma-based interpolation (follows sigma schedule)
|
||||
sigma_progress = 1.0 - max(0.0, min(1.0, current_sigma)) # Clamp to [0, 1]
|
||||
|
||||
# Linear-based interpolation (based on position in sampling schedule)
|
||||
linear_progress = sigma_progress # Default to same as sigma
|
||||
try:
|
||||
sample_sigmas = model_options["transformer_options"]["sample_sigmas"]
|
||||
# Find position in the sigma schedule
|
||||
sigma_idx = 0
|
||||
for i in range(len(sample_sigmas) - 1):
|
||||
if current_sigma >= sample_sigmas[i + 1]:
|
||||
sigma_idx = i
|
||||
break
|
||||
sigma_idx = i + 1
|
||||
linear_progress = sigma_idx / max(1, len(sample_sigmas) - 1)
|
||||
except Exception as e:
|
||||
logger.warning(f"Could not get sample_sigmas for linear progress: {e}")
|
||||
|
||||
# Blend between linear and sigma schedules
|
||||
# linear_blend = 0.0 means full linear schedule
|
||||
# linear_blend = 1.0 means full sigma schedule
|
||||
blended_progress = (sigma_progress * self.linear_blend) + (linear_progress * (1.0 - self.linear_blend))
|
||||
cond_scale = self.start_cfg + (self.end_cfg - self.start_cfg) * blended_progress
|
||||
|
||||
logger.info(f"[CFG Sigma Interpolate] Sigma={current_sigma:.4f}, SigmaProgress={sigma_progress:.4f}, LinearProgress={linear_progress:.4f}, Blend={self.linear_blend:.2f}, CFG={cond_scale:.4f}")
|
||||
|
||||
negative_cond = self.conds.get("negative", None)
|
||||
positive_cond = self.conds.get("positive", None)
|
||||
return comfy.samplers.sampling_function(self.inner_model, x, timestep, negative_cond, positive_cond, cond_scale, model_options=model_options, seed=seed)
|
||||
|
||||
|
||||
class TK3RCFGSigmaInterpolate:
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"model": ("MODEL",),
|
||||
"positive": ("CONDITIONING",),
|
||||
"negative": ("CONDITIONING",),
|
||||
"cfg_start": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 30.0, "step": 0.1}),
|
||||
"cfg_end": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 30.0, "step": 0.1}),
|
||||
"linear_blend": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.05}),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("GUIDER",)
|
||||
RETURN_NAMES = ("guider",)
|
||||
FUNCTION = "execute"
|
||||
CATEGORY = "TK3R/Advanced"
|
||||
|
||||
def execute(self, model, positive, negative, cfg_start, cfg_end, linear_blend):
|
||||
logger.info(f"[CFG Sigma Interpolate] Creating guider with start_cfg={cfg_start}, end_cfg={cfg_end}, linear_blend={linear_blend}")
|
||||
|
||||
guider = Guider_CFGSigmaInterpolate(model)
|
||||
guider.set_conds(positive, negative)
|
||||
guider.set_sigma_schedule(cfg_start, cfg_end, linear_blend)
|
||||
return (guider,)
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3R Scheduled CFG Guider": TK3RCFGScheduleGuider,
|
||||
"TK3R CFG Sigma Interpolate": TK3RCFGSigmaInterpolate,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3R Scheduled CFG Guider": "TK3R Scheduled CFG Guider",
|
||||
"TK3R CFG Sigma Interpolate": "TK3R CFG Sigma Interpolate",
|
||||
}
|
||||
@@ -0,0 +1,50 @@
|
||||
"""
|
||||
Interpolate between two sigma schedules by averaging each pair
|
||||
"""
|
||||
|
||||
import torch
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class TK3RSigmasInterpolate:
|
||||
"""Interpolate between two sigma schedules by averaging corresponding values"""
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"sigmas_1": ("SIGMAS", {"tooltip": "First sigma schedule"}),
|
||||
"sigmas_2": ("SIGMAS", {"tooltip": "Second sigma schedule"}),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("SIGMAS",)
|
||||
RETURN_NAMES = ("sigmas",)
|
||||
FUNCTION = "interpolate_sigmas"
|
||||
CATEGORY = "TK3R/Utility"
|
||||
DESCRIPTION = "Interpolate between two sigma schedules by averaging each pair. If lengths don't match, returns first sigma schedule unchanged."
|
||||
|
||||
def interpolate_sigmas(self, sigmas_1, sigmas_2):
|
||||
# Check if lengths match
|
||||
if len(sigmas_1) != len(sigmas_2):
|
||||
logger.error(
|
||||
f"TK3RSigmasInterpolate: Sigma length mismatch! "
|
||||
f"sigmas_1 has {len(sigmas_1)} values, sigmas_2 has {len(sigmas_2)} values. "
|
||||
f"Returning sigmas_1 unchanged."
|
||||
)
|
||||
return (sigmas_1,)
|
||||
|
||||
# Average the two sigma schedules
|
||||
interpolated_sigmas = (sigmas_1 + sigmas_2) / 2.0
|
||||
|
||||
return (interpolated_sigmas,)
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"TK3RSigmasInterpolate": TK3RSigmasInterpolate,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"TK3RSigmasInterpolate": "TK3R Sigmas Interpolate",
|
||||
}
|
||||
@@ -0,0 +1,44 @@
|
||||
[project]
|
||||
name = "comfyui_tk3r_ext"
|
||||
version = "1.0.0"
|
||||
description = "Extended versions of various ComfyUI nodes"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.8"
|
||||
license = {text = "GPLv3"}
|
||||
authors = [
|
||||
{name = "TK3R"}
|
||||
]
|
||||
keywords = ["comfyui", "custom-nodes", "stable-diffusion", "controlnet"]
|
||||
classifiers = [
|
||||
"Development Status :: 4 - Beta",
|
||||
"Intended Audience :: Developers",
|
||||
"License :: OSI Approved :: GPLv3 License",
|
||||
"Operating System :: OS Independent",
|
||||
"Environment :: GPU :: NVIDIA CUDA",
|
||||
"Environment :: GPU :: AMD ROCm",
|
||||
"Environment :: GPU :: Apple Metal",
|
||||
"Programming Language :: Python :: 3",
|
||||
"Programming Language :: Python :: 3.8",
|
||||
"Programming Language :: Python :: 3.9",
|
||||
"Programming Language :: Python :: 3.10",
|
||||
"Programming Language :: Python :: 3.11",
|
||||
"Topic :: Scientific/Engineering :: Artificial Intelligence",
|
||||
]
|
||||
|
||||
dependencies = [
|
||||
"rich>=10.0.0"
|
||||
]
|
||||
|
||||
[project.urls]
|
||||
Homepage = "https://github.com/TK3R/ComfyUI_TK3R_Ext"
|
||||
Repository = "https://github.com/TK3R/ComfyUI_TK3R_Ext"
|
||||
Issues = "https://github.com/TK3R/ComfyUI_TK3R_Ext/issues"
|
||||
|
||||
[build-system]
|
||||
requires = ["setuptools>=45", "wheel"]
|
||||
build-backend = "setuptools.build_meta"
|
||||
|
||||
[tool.comfy]
|
||||
PublisherId = "TK3R"
|
||||
DisplayName = "TK3R Ext"
|
||||
requires-comfyui = ">=1.0.0"
|
||||
@@ -0,0 +1 @@
|
||||
rich>=10.0.0
|
||||
@@ -0,0 +1,48 @@
|
||||
import { app } from "../../scripts/app.js";
|
||||
import { ComfyWidgets } from "../../scripts/widgets.js";
|
||||
|
||||
app.registerExtension({
|
||||
name: "TK3R.TextOutput",
|
||||
async beforeRegisterNodeDef(nodeType, nodeData, app) {
|
||||
if (nodeData.name === "TK3RCLIPTextEncodeWithTokenCount" || nodeData.name === "TK3R CLIP Text Encode With Token Count") {
|
||||
const onExecuted = nodeType.prototype.onExecuted;
|
||||
nodeType.prototype.onExecuted = function (message) {
|
||||
onExecuted?.apply(this, arguments);
|
||||
|
||||
if (this.widgets) {
|
||||
const pos = this.widgets.findIndex((w) => w.name === "output_text");
|
||||
if (pos !== -1) {
|
||||
for (let i = pos; i < this.widgets.length; i++) {
|
||||
this.widgets[i].onRemove?.();
|
||||
}
|
||||
this.widgets.length = pos;
|
||||
}
|
||||
}
|
||||
|
||||
const text = message.text;
|
||||
if (!text) { return; }
|
||||
|
||||
// Create widget as multiline initially to get a textarea
|
||||
const w = ComfyWidgets["STRING"](this, "output_text", ["STRING", { multiline: true }], app).widget;
|
||||
w.inputEl.readOnly = true;
|
||||
w.inputEl.style.opacity = 0.6;
|
||||
w.inputEl.rows = 2;
|
||||
w.inputEl.style.height = "auto";
|
||||
w.value = text[0];
|
||||
|
||||
// Trick ComfyUI/LiteGraph into treating this as a fixed-size widget
|
||||
// so it doesn't try to expand it to fill remaining vertical space
|
||||
w.options = w.options || {};
|
||||
w.options.multiline = false;
|
||||
|
||||
// Override computeSize to return fixed small height
|
||||
w.computeSize = function(width) {
|
||||
return [width, 40]; // ~40px for 2 lines
|
||||
}
|
||||
|
||||
// Refresh node appearance without resetting dimensions
|
||||
this.onResize?.(this.size);
|
||||
};
|
||||
}
|
||||
},
|
||||
});
|
||||
Reference in New Issue
Block a user