fix debug

.gitignore

@@ -0,0 +1,182 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.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/
+cover/
+
+# 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
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__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/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# User config files
+.vscode/
+output/
+
+ckpts/
+outputs/
+temps/

models/unet_2d_blocks_custom.py

@@ -22,7 +22,7 @@ from torch import nn
 from diffusers.utils import is_torch_version, logging
 # from diffusers.models.attention import AdaGroupNorm
 from diffusers.models.attention_processor import Attention, AttnAddedKVProcessor, AttnAddedKVProcessor2_0
-from diffusers.models.dual_transformer_2d import DualTransformer2DModel
+# from diffusers.models.dual_transformer_2d import DualTransformer2DModel
 from diffusers.models.resnet import Downsample2D, FirDownsample2D, FirUpsample2D, KDownsample2D, KUpsample2D, ResnetBlock2D, Upsample2D
 # from diffusers.models.transformer_2d import Transformer2DModel
 from models.transformer_2d_custom import Transformer2DModel
@@ -582,16 +582,17 @@ class UNetMidBlock2DCrossAttn(nn.Module):
                     )
                 )
             else:
-                attentions.append(
-                    DualTransformer2DModel(
-                        num_attention_heads,
-                        in_channels // num_attention_heads,
-                        in_channels=in_channels,
-                        num_layers=1,
-                        cross_attention_dim=cross_attention_dim,
-                        norm_num_groups=resnet_groups,
-                    )
-                )
+                # attentions.append(
+                #     DualTransformer2DModel(
+                #         num_attention_heads,
+                #         in_channels // num_attention_heads,
+                #         in_channels=in_channels,
+                #         num_layers=1,
+                #         cross_attention_dim=cross_attention_dim,
+                #         norm_num_groups=resnet_groups,
+                #     )
+                # )
+                pass
             resnets.append(
                 ResnetBlock2D(
                     in_channels=in_channels,
@@ -951,16 +952,17 @@ class CrossAttnDownBlock2D(nn.Module):
                     )
                 )
             else:
-                attentions.append(
-                    DualTransformer2DModel(
-                        num_attention_heads,
-                        out_channels // num_attention_heads,
-                        in_channels=out_channels,
-                        num_layers=1,
-                        cross_attention_dim=cross_attention_dim,
-                        norm_num_groups=resnet_groups,
-                    )
-                )
+                # attentions.append(
+                #     DualTransformer2DModel(
+                #         num_attention_heads,
+                #         out_channels // num_attention_heads,
+                #         in_channels=out_channels,
+                #         num_layers=1,
+                #         cross_attention_dim=cross_attention_dim,
+                #         norm_num_groups=resnet_groups,
+                #     )
+                # )
+                pass
         self.attentions = nn.ModuleList(attentions)
         self.resnets = nn.ModuleList(resnets)
 
@@ -2140,16 +2142,17 @@ class CrossAttnUpBlock2D(nn.Module):
                     )
                 )
             else:
-                attentions.append(
-                    DualTransformer2DModel(
-                        num_attention_heads,
-                        out_channels // num_attention_heads,
-                        in_channels=out_channels,
-                        num_layers=1,
-                        cross_attention_dim=cross_attention_dim,
-                        norm_num_groups=resnet_groups,
-                    )
-                )
+                # attentions.append(
+                #     DualTransformer2DModel(
+                #         num_attention_heads,
+                #         out_channels // num_attention_heads,
+                #         in_channels=out_channels,
+                #         num_layers=1,
+                #         cross_attention_dim=cross_attention_dim,
+                #         norm_num_groups=resnet_groups,
+                #     )
+                # )
+                pass
         self.attentions = nn.ModuleList(attentions)
         self.resnets = nn.ModuleList(resnets)
 

requirements.txt

@@ -8,7 +8,7 @@ ftfy
 # Training
 bs4==0.0.1              # Needed for text cleaning
 bson==0.5.10
-diffusers==0.19.3       # diffusers[torch]==0.19.3 in control
+diffusers==0.29.0       # diffusers[torch]==0.19.3 in control
 einops==0.6.0
 ftfy==6.1.1             # Needed for text cleaning
 kornia==0.6.12
@@ -30,7 +30,7 @@ httpx==0.23.3
 opencv-python
 open_clip_torch
 protobuf==3.20.0
-huggingface_hub==0.25.2 --force-reinstall
 
-open_clip_torch
-git+https://github.com/openai/CLIP.git
+git+https://github.com/openai/CLIP.git
+
+huggingface_hub==0.30.2