reduce mandatory requirements

Signed-off-by: Vladimir Mandic <mandic00@live.com>

CHANGELOG.md

@@ -1,12 +1,12 @@
 # Change Log for SD.Next
 
-## Update for 2026-02-17
+## Update for 2026-02-18
 
-### Highlights for 2026-02-17
+### Highlights for 2026-02-18
 
 TBD
 
-### Details for 2026-02-17
+### Details for 2026-02-18
 
 - **Models**
   - [FireRed Image Edit](https://huggingface.co/FireRedTeam/FireRed-Image-Edit-1.0)  
@@ -28,6 +28,10 @@ TBD
   - **nunchaku** models are now listed in networks tab as reference models  
     instead of being used implicitly via quantization, thanks @CalamitousFelicitousness  
   - removed: old `codeformer` and `gfpgan` face restorers, thanks @CalamitousFelicitousness  
+- **Compute**
+  - **ROCm** support for additional AMD GPUs: `gfx103X`, thanks @crashingalexsan  
+  - **Cuda** `torch==2.10` removed support for `rtx1000` series, use following before first startup:  
+    > set TORCH_COMMAND='torch==2.9.1 torchvision==0.24.1 torchaudio==2.9.1 --index-url https://download.pytorch.org/whl/cu126'  
 - **UI**
   - ui: **localization** improved translation quality and new translations locales:  
     *en, en1, en2, en3, en4, hr, es, it, fr, de, pt, ru, zh, ja, ko, hi, ar, bn, ur, id, vi, tr, sr, po, he, xx, yy, qq, tlh*  
@@ -39,7 +43,10 @@ TBD
 - **Internal**
   - `python==3.14` initial support  
     see [docs](https://vladmandic.github.io/sdnext-docs/Python/) for details  
-  - remove hard-dependnecies: `clip`, `numba`, `skimage`, `torchsde`  
+  - remove hard-dependnecies:  
+    `clip, numba, skimage, torchsde, omegaconf, antlr, patch-ng, patch-ng, astunparse, addict, inflection, jsonmerge, kornia`,  
+    `resize-right, voluptuous, yapf, sqlalchemy, invisible-watermark, pi-heif, ftfy, blendmodes, PyWavelets`  
+    these are now installed on-demand when needed  
   - refactor: to/from image/tensor logic, thanks @CalamitousFelicitousness  
   - refactor: switch to `pyproject.toml` for tool configs  
   - refactor: reorganize `cli` scripts  

cli/api-pulid.js

@@ -81,7 +81,7 @@ async function main() {
   } else {
     const json = await res.json();
     console.log('result:', json.info);
-    for (const i in json.images) { // eslint-disable-line guard-for-in
+    for (const i in json.images) {
       const file = args.output || `/tmp/test-${i}.jpg`;
       const data = atob(json.images[i]);
       fs.writeFileSync(file, data, 'binary');

cli/api-txt2img.js

@@ -41,7 +41,7 @@ async function main() {
   } else {
     const json = await res.json();
     console.log('result:', json.info);
-    for (const i in json.images) { // eslint-disable-line guard-for-in
+    for (const i in json.images) {
       const f = `/tmp/test-${i}.jpg`;
       fs.writeFileSync(f, atob(json.images[i]), 'binary');
       console.log('image saved:', f);

cli/process.py

@@ -6,7 +6,6 @@ import base64
 import numpy as np
 import mediapipe as mp
 from PIL import Image, ImageOps
-from pi_heif import register_heif_opener
 from skimage.metrics import structural_similarity as ssim
 from scipy.stats import beta
 
@@ -261,7 +260,6 @@ def file(filename: str, folder: str, tag = None, requested = []):
     res = Result(fn = filename, typ='unknown', tag=tag, requested = requested)
     # open image
     try:
-        register_heif_opener()
         res.image = Image.open(filename)
         if res.image.mode == 'RGBA':
             res.image = res.image.convert('RGB')

html/locale_ar.json

@@ -11071,4 +11071,4 @@
       "hint": "استخراج خريطة العمق باستخدام نموذج Zoe"
     }
   ]
-}
+}

html/locale_bn.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_de.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_en.json

@@ -1654,4 +1654,4 @@
       {"id":"","label":"Z values","localized":"","hint":"Separate values for Z axis using commas","ui":"script_xyz_grid_script"},
       {"id":"","label":"Zoe Depth","localized":"","hint":"","ui":"control"}
   ]
-}
+}

html/locale_es.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_fr.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_he.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_hi.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_hr.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_id.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_it.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_ja.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_ko.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_nb.json

@@ -11071,4 +11071,4 @@
       "hint": "Utilizes the Zoe model for estimating relative depth from a single 2D image for ControlNet."
     }
   ]
-}
+}

html/locale_po.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_pt.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_qq.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_ru.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_sr.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_tb.json

@@ -11071,4 +11071,4 @@
       "hint": "Utilizes the Zoe neural heuristic to compute a monochromatic spatial depth-parallax map."
     }
   ]
-}
+}

html/locale_tlh.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_tr.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_ur.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_vi.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_xx.json

@@ -11071,4 +11071,4 @@
       "hint": ""
     }
   ]
-}
+}

html/locale_zh.json

@@ -11071,4 +11071,4 @@
       "hint": "Zoe 深度图估计模型"
     }
   ]
-}
+}

installer.py

@@ -698,9 +698,9 @@ def check_diffusers():
     current = opts.get('diffusers_version', '') if minor > -1 else ''
     if (minor == -1) or ((current != target_commit) and (not args.experimental)):
         if minor == -1:
-            log.info(f'Diffusers install: commit={target_commit}')
+            log.info(f'Install: package="diffusers" commit={target_commit}')
         else:
-            log.info(f'Diffusers update: current={pkg.version} hash={current} target={target_commit}')
+            log.info(f'Update: package="diffusers" current={pkg.version} hash={current} target={target_commit}')
             pip('uninstall --yes diffusers', ignore=True, quiet=True, uv=False)
         if args.skip_git:
             log.warning('Git: marked as not available but required for diffusers installation')
@@ -728,9 +728,9 @@ def check_transformers():
         target_tokenizers = '0.22.2'
     if (pkg_transformers is None) or ((pkg_transformers.version != target_transformers) or (pkg_tokenizers is None) or ((pkg_tokenizers.version != target_tokenizers) and (not args.experimental))):
         if pkg_transformers is None:
-            log.info(f'Transformers install: version={target_transformers}')
+            log.info(f'Install: package="transformers" version={target_transformers}')
         else:
-            log.info(f'Transformers update: current={pkg_transformers.version} target={target_transformers}')
+            log.info(f'Update: package="transformers" current={pkg_transformers.version} target={target_transformers}')
         pip('uninstall --yes transformers', ignore=True, quiet=True, uv=False)
         pip(f'install --upgrade tokenizers=={target_tokenizers}', ignore=False, quiet=True, uv=False)
         pip(f'install --upgrade transformers=={target_transformers}', ignore=False, quiet=True, uv=False)
@@ -961,7 +961,7 @@ def check_cudnn():
 
 # check torch version
 def check_torch():
-    log.info('Verifying torch installation')
+    log.info('Torch: verifying installation')
     t_start = time.time()
     if args.skip_torch:
         log.info('Torch: skip tests')
@@ -1030,7 +1030,7 @@ def check_torch():
 
     if 'torch' in torch_command:
         if not installed('torch'):
-            log.info(f'Torch: download and install in progress... cmd="{torch_command}"')
+            log.info(f'Install: package="torch" download and install in progress... cmd="{torch_command}"')
             install('--upgrade pip', 'pip', reinstall=True) # pytorch rocm is too large for older pip
         install(torch_command, 'torch torchvision', quiet=True)
 
@@ -1366,6 +1366,9 @@ def install_insightface():
 def install_optional():
     t_start = time.time()
     log.info('Installing optional requirements...')
+    install('pi-heif')
+    install('addict')
+    install('yapf')
     install('--no-build-isolation git+https://github.com/Disty0/BasicSR@23c1fb6f5c559ef5ce7ad657f2fa56e41b121754', 'basicsr', ignore=True, quiet=True)
     install('av', ignore=True, quiet=True)
     install('beautifulsoup4', ignore=True, quiet=True)

javascript/civitai.js

@@ -1,7 +1,7 @@
 String.prototype.format = function (args) { // eslint-disable-line no-extend-native, func-names
   let thisString = '';
   for (let charPos = 0; charPos < this.length; charPos++) thisString += this[charPos];
-  for (const key in args) { // eslint-disable-line guard-for-in
+  for (const key in args) {
     const stringKey = `{${key}}`;
     thisString = thisString.replace(new RegExp(stringKey, 'g'), args[key]);
   }

modules/api/models.py

@@ -1,7 +1,7 @@
+import re
 import inspect
 from typing import Any, Optional, Dict, List, Type, Callable, Union
 from pydantic import BaseModel, Field, create_model # pylint: disable=no-name-in-module
-from inflection import underscore
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
 import modules.shared as shared
 
@@ -29,6 +29,12 @@ if not hasattr(BaseModel, "__config__"):
     BaseModel.__config__ = DummyConfig
 
 
+def underscore(name: str) -> str: # Convert CamelCase or PascalCase string to underscore_case (snake_case).
+    # use instead of inflection.underscore
+    s1 = re.sub('([a-z0-9])([A-Z])', r'\1_\2', name)
+    s2 = re.sub('([A-Z]+)([A-Z][a-z])', r'\1_\2', s1)
+    return s2.lower()
+
 class PydanticModelGenerator:
     def __init__(
         self,

modules/cfgzero/wan_t2v_pipeline.py

@@ -15,7 +15,6 @@
 import html
 from typing import Any, Callable, Dict, List, Optional, Union
 
-import ftfy
 import regex as re
 import torch
 from transformers import AutoTokenizer, UMT5EncoderModel
@@ -86,6 +85,9 @@ def optimized_scale(positive_flat, negative_flat):
     return st_star
 
 def basic_clean(text):
+    from installer import install
+    install('ftfy')
+    import ftfy
     text = ftfy.fix_text(text)
     text = html.unescape(html.unescape(text))
     return text.strip()

modules/extras.py

@@ -33,7 +33,7 @@ def run_modelmerger(id_task, **kwargs):  # pylint: disable=unused-argument
     from installer import install
     install('tensordict', quiet=True)
     try:
-        from tensordict import TensorDict
+        from tensordict import TensorDict # pylint: disable=unused-import
     except Exception as e:
         shared.log.error(f"Merge: {e}")
         return [*[gr.update() for _ in range(4)], "tensordict not available"]

modules/face/faceid.py

@@ -70,7 +70,7 @@ def face_id(
         shared.prompt_styles.apply_styles_to_extra(p)
 
         if shared.opts.cuda_compile_backend == 'none':
-            token_merge.apply_token_merging(p.sd_model)
+            token_merge.apply_token_merging(shared.sd_model)
             sd_hijack_freeu.apply_freeu(p)
 
         script_callbacks.before_process_callback(p)

modules/image/save.py

@@ -13,11 +13,6 @@ from modules.image.watermark import set_watermark
 
 debug = errors.log.trace if os.environ.get('SD_PATH_DEBUG', None) is not None else lambda *args, **kwargs: None
 debug_save = errors.log.trace if os.environ.get('SD_SAVE_DEBUG', None) is not None else lambda *args, **kwargs: None
-try:
-    from pi_heif import register_heif_opener
-    register_heif_opener()
-except Exception:
-    pass
 
 
 def sanitize_filename_part(text, replace_spaces=True):

modules/postprocess/realesrgan_model.py

@@ -9,6 +9,8 @@ from modules import devices
 class UpscalerRealESRGAN(Upscaler):
     def __init__(self, dirname):
         from installer import install
+        install('addict')
+        install('yapf')
         install('--no-build-isolation git+https://github.com/Disty0/BasicSR@23c1fb6f5c559ef5ce7ad657f2fa56e41b121754', 'basicsr', ignore=True, quiet=True)
         from basicsr.archs.rrdbnet_arch import RRDBNet
         self.name = "RealESRGAN"

modules/processing_diffusers.py

@@ -75,7 +75,7 @@ def process_pre(p: processing.StableDiffusionProcessing):
         # apply-with-unapply
         sd_models_compile.check_deepcache(enable=True)
         ipadapter.apply(shared.sd_model, p)
-        token_merge.apply_token_merging(p.sd_model)
+        token_merge.apply_token_merging(shared.sd_model)
         hidiffusion.apply(p, shared.sd_model_type)
         ras.apply(shared.sd_model, p)
         pag.apply(p)
@@ -117,7 +117,7 @@ def process_post(p: processing.StableDiffusionProcessing):
     try:
         sd_models_compile.check_deepcache(enable=False)
         ipadapter.unapply(shared.sd_model, unload=getattr(p, 'ip_adapter_unload', False))
-        token_merge.remove_token_merging(p.sd_model)
+        token_merge.remove_token_merging(shared.sd_model)
         hidiffusion.unapply()
         ras.unapply(shared.sd_model)
         pag.unapply()

modules/processing_helpers.py

@@ -7,7 +7,6 @@ import torch
 import numpy as np
 import cv2
 from PIL import Image
-from blendmodes.blend import blendLayers, BlendType
 from modules import shared, devices, images, sd_models, sd_samplers, sd_vae, sd_hijack_hypertile, processing_vae, timer
 from modules.api import helpers
 
@@ -38,7 +37,9 @@ def setup_color_correction(image):
 def apply_color_correction(correction, original_image):
     from installer import install
     install('scikit-image', quiet=True)
+    install('blendmodes', quiet=True)
     from skimage import exposure
+    from blendmodes.blend import blendLayers, BlendType
     shared.log.debug(f"Applying color correction: correction={correction.shape} image={original_image}")
     np_image = np.asarray(original_image)
     np_recolor = cv2.cvtColor(np_image, cv2.COLOR_RGB2LAB)

modules/rocm.py

@@ -129,7 +129,7 @@ class Agent:
             return "v2-staging/gfx1152"
         if self.gfx_version == 0x1153:
             return "v2-staging/gfx1153"
-        if self.gfx_version in (0x1030, 0x1032,):
+        if self.gfx_version in (0x1030, 0x1031, 0x1032, 0x1034,):
             return "v2-staging/gfx103X-dgpu"
         #if (self.gfx_version & 0xFFF0) == 0x1010:
         #    return "gfx101X-dgpu"

modules/seedvr/src/common/config.py

@@ -1,7 +1,12 @@
 import importlib
 from typing import Any, Callable, List, Union
-from omegaconf import DictConfig, ListConfig, OmegaConf
 
+try:
+    from installer import install
+    install('omegaconf')
+    from omegaconf import DictConfig, ListConfig, OmegaConf
+except Exception as e:
+    raise ImportError(f"Failed to import omegaconf. Error: {e}") from e
 
 try:
     OmegaConf.register_new_resolver("eval", eval)
@@ -10,7 +15,7 @@ except Exception as e:
         raise
 
 
-def load_config(path: str, argv: List[str] = None) -> Union[DictConfig, ListConfig]:
+def load_config(path: str, argv: List[str] = None):
     """
     Load a configuration. Will resolve inheritance.
     """
@@ -25,7 +30,7 @@ def load_config(path: str, argv: List[str] = None) -> Union[DictConfig, ListConf
 
 def resolve_recursive(
     config: Any,
-    resolver: Callable[[Union[DictConfig, ListConfig]], Union[DictConfig, ListConfig]],
+    resolver: Callable[[Any], Any],
 ) -> Any:
     config = resolver(config)
     if isinstance(config, DictConfig):
@@ -41,7 +46,7 @@ def resolve_recursive(
     return config
 
 
-def resolve_inheritance(config: Union[DictConfig, ListConfig]) -> Any:
+def resolve_inheritance(config: Any) -> Any:
     """
     Recursively resolve inheritance if the config contains:
     __inherit__: path/to/parent.yaml or a ListConfig of such paths.
@@ -104,7 +109,7 @@ def import_item(path: Union[str, List[str]], name: str) -> Any:
         raise ValueError(f"Path must be string or list of strings, got: {type(path)}")
 
 
-def create_object(config: DictConfig) -> Any:
+def create_object(config: Any) -> Any:
     """
     Create an object from config.
     The config is expected to contains the following:

modules/seedvr/src/common/diffusion/config.py

@@ -17,7 +17,6 @@ Utility functions for creating schedules and samplers from config.
 """
 
 import torch
-from omegaconf import DictConfig
 
 from .samplers.base import Sampler
 from .samplers.euler import EulerSampler
@@ -28,7 +27,7 @@ from .timesteps.sampling.trailing import UniformTrailingSamplingTimesteps
 
 
 def create_schedule_from_config(
-    config: DictConfig,
+    config,
 ) -> Schedule:
     """
     Create a schedule from configuration.
@@ -40,7 +39,7 @@ def create_schedule_from_config(
 
 
 def create_sampler_from_config(
-    config: DictConfig,
+    config,
     schedule: Schedule,
     timesteps: SamplingTimesteps,
 ) -> Sampler:
@@ -57,7 +56,7 @@ def create_sampler_from_config(
 
 
 def create_sampling_timesteps_from_config(
-    config: DictConfig,
+    config,
     schedule: Schedule,
     device: torch.device,
 ) -> SamplingTimesteps:

modules/seedvr/src/core/infer.py

@@ -1,7 +1,6 @@
 from typing import List, Optional, Tuple, Union
 import torch
 from einops import rearrange
-from omegaconf import DictConfig, ListConfig
 from ..common.diffusion import classifier_free_guidance_dispatcher, create_sampler_from_config, create_sampling_timesteps_from_config, create_schedule_from_config
 from ..models.dit_v2 import na
 
@@ -40,7 +39,9 @@ def optimized_channels_to_second(tensor):
 
 
 class VideoDiffusionInfer():
-    def __init__(self, config: DictConfig, device: str, dtype: torch.dtype):
+    def __init__(self, config, device: str, dtype: torch.dtype):
+        from installer import install
+        install('omegaconf')
         self.config = config
         self.device = device
         self.dtype = dtype
@@ -48,6 +49,7 @@ class VideoDiffusionInfer():
         self.dit = None
         self.sampler = None
         self.schedule = None
+
     def get_condition(self, latent: torch.Tensor, latent_blur: torch.Tensor, task: str) -> torch.Tensor:
         t, h, w, c = latent.shape
         cond = torch.zeros([t, h, w, c + 1], device=latent.device, dtype=latent.dtype)
@@ -93,6 +95,7 @@ class VideoDiffusionInfer():
 
     @torch.no_grad()
     def vae_encode(self, samples: List[torch.Tensor]) -> List[torch.Tensor]:
+        from omegaconf import ListConfig
         use_sample = self.config.vae.get("use_sample", True)
         latents = []
         if len(samples) > 0:
@@ -138,6 +141,7 @@ class VideoDiffusionInfer():
     @torch.no_grad()
     def vae_decode(self, latents: List[torch.Tensor], target_dtype: torch.dtype = None) -> List[torch.Tensor]:
         """🚀 VAE decode optimisé - décodage direct sans chunking, compatible avec autocast externe"""
+        from omegaconf import ListConfig
         samples = []
         if len(latents) > 0:
             device = self.device

modules/seedvr/src/core/model_manager.py

@@ -1,6 +1,5 @@
 import os
 import torch
-from omegaconf import OmegaConf
 from safetensors.torch import load_file as load_safetensors_file
 from huggingface_hub import hf_hub_download
 from ..optimization.memory_manager import preinitialize_rope_cache
@@ -9,6 +8,10 @@ from ..core.infer import VideoDiffusionInfer
 
 
 def configure_runner(model_name, cache_dir, device:str='cpu', dtype:torch.dtype=None):
+    from installer import install
+    install('omegaconf')
+    from omegaconf import OmegaConf
+
     repo_id = "vladmandic/SeedVR2"
     script_directory = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
     config_path = os.path.join(script_directory, './config_7b.yaml') if "7b" in model_name else os.path.join(script_directory, './config_3b.yaml')

modules/ui_extra_networks.py

@@ -437,7 +437,7 @@ class ExtraNetworksPage:
         files = list(files_cache.list_files(reference_path, ext_filter=exts, recursive=False))
         if shared.opts.diffusers_dir in path:
             path = os.path.relpath(path, shared.opts.diffusers_dir)
-            fn = os.path.join(reference_path, path.replace('models--', '').replace('\\', '/').split('/')[0])
+            fn = os.path.join(reference_path, path.replace('models--', '').replace('\\', '/').split('/')[0]) # pylint: disable=use-maxsplit-arg
         else:
             fn = os.path.splitext(path)[0]
             files += list(files_cache.list_files(os.path.dirname(path), ext_filter=exts, recursive=False))

package.json

@@ -25,9 +25,9 @@
     "eslint-ui": "cd extensions-builtin/sdnext-modernui && eslint . javascript/",
     "ruff": ". venv/bin/activate && ruff check",
     "ruff-win": "venv\\scripts\\activate && ruff check",
-    "pylint": ". venv/bin/activate && pylint --disable=W0511 *.py modules/ pipelines/ scripts/ extensions-builtin/ | grep -v '^*'",
-    "pylint-win": "venv\\scripts\\activate && pylint --disable=W0511 *.py modules/ pipelines/ scripts/ extensions-builtin/",
-    "lint": "npm run format && npm run eslint && npm run eslint-ui && npm run ruff && npm run pylint | grep -v TODO",
+    "pylint": ". venv/bin/activate && pylint *.py modules/ pipelines/ scripts/ extensions-builtin/ | grep -v '^*'",
+    "pylint-win": "venv\\scripts\\activate && pylint *.py modules/ pipelines/ scripts/ extensions-builtin/",
+    "lint": "npm run format && npm run eslint && npm run eslint-ui && npm run ruff && npm run pylint",
     "lint-win": "npm run format-win && npm run eslint && npm run eslint-ui && npm run ruff-win && npm run pylint-win",
     "test": ". venv/bin/activate; python launch.py --debug --test",
     "todo": "grep -oIPR 'TODO.*' *.py modules/ pipelines/ | sort -u",

pipelines/hdm/hdm/utils/__init__.py

@@ -1,5 +1,4 @@
 import importlib
-import omegaconf
 from inspect import isfunction
 from random import shuffle
 
@@ -16,6 +15,9 @@ def get_obj_from_str(string, reload=False):
 
 
 def instantiate(obj):
+    from installer import install
+    install('omegaconf')
+    import omegaconf
     if isinstance(obj, omegaconf.DictConfig):
         obj = dict(**obj)
     if isinstance(obj, dict) and "class" in obj:

pipelines/hdm/hdm/utils/config.py

@@ -1,9 +1,13 @@
 import os
-import toml
-import omegaconf
 
 
 def load_train_config(file):
+    from installer import install
+    install('omegaconf')
+    install('toml')
+    import omegaconf
+    import toml
+
     config = toml.load(file)
 
     model = config["model"]

pipelines/model_google.py

@@ -56,7 +56,7 @@ class GoogleNanoBananaPipeline():
         )
 
     def img2img(self, prompt, image):
-        from google import genai
+        from google import genai # pylint: disable=no-name-in-module
         image_bytes = io.BytesIO()
         image.save(image_bytes, format='JPEG')
         return self.client.models.generate_content(
@@ -109,7 +109,7 @@ class GoogleNanoBananaPipeline():
         return args
 
     def __call__(self, prompt: list[str], width: int, height: int, image: Image.Image = None):
-        from google import genai
+        from google import genai # pylint: disable=no-name-in-module
         if self.client is None:
             args = self.get_args()
             if args is None:

pyproject.toml

@@ -81,6 +81,7 @@ ignore = [
   "B006",   # Do not use mutable data structures for argument defaults
   "B008",   # Do not perform function call in argument defaults
   "B905",   # Strict zip() usage
+  "ASYNC240", # Async functions should not use os.path methods
   "C420",   # Unnecessary dict comprehension for iterable; use `dict.fromkeys` instead
   "C408",   # Unnecessary `dict` call
   "I001",   # Import block is un-sorted or un-formatted
@@ -194,7 +195,7 @@ main.ignore-patterns=[
                 ".*_model_arch_v2.py$",
                 ]
 main.ignored-modules=""
-main.jobs=8
+main.jobs=4
 main.limit-inference-results=100
 main.load-plugins=""
 main.persistent=false
@@ -334,15 +335,15 @@ similarities.ignore-imports=true
 similarities.ignore-signatures=true
 similarities.min-similarity-lines=4
 spelling.max-spelling-suggestions=4
-# spelling.dict=""
-# spelling.ignore-comment-directives=["fmt: on","fmt: off","noqa:","noqa","nosec","isort:skip","mypy:"]
-# spelling.ignore-words=""
-# spelling.private-dict-file=""
-# spelling.store-unknown-words=false
 string.check-quote-consistency=false
 string.check-str-concat-over-line-jumps=false
 typecheck.contextmanager-decorators="contextlib.contextmanager"
-typecheck.generated-members=["numpy.*","logging.*","torch.*","cv2.*"]
+typecheck.generated-members=[
+        "numpy.*",
+        "logging.*",
+        "torch.*",
+        "cv2.*",
+        ]
 typecheck.ignore-none=true
 typecheck.ignore-on-opaque-inference=true
 typecheck.ignored-checks-for-mixins=["no-member","not-async-context-manager","not-context-manager","attribute-defined-outside-init"]

requirements.txt

@@ -3,35 +3,19 @@ setuptools==69.5.1
 wheel
 
 # standard
-patch-ng
 anyio
-addict
-astunparse
 filetype
 future
 GitPython
-httpcore
-inflection
-jsonmerge
-kornia
 lark
-omegaconf
 piexif
 mpmath
 psutil
 pyyaml
-resize-right
 toml
 voluptuous
-yapf
 fasteners
 orjson
-sqlalchemy
-invisible-watermark
-PyWavelets
-pi-heif
-ftfy
-blendmodes
 
 # versioned
 fastapi==0.124.4
@@ -40,13 +24,11 @@ safetensors==0.7.0
 peft==0.18.1
 httpx==0.28.1
 compel==2.2.1
-antlr4-python3-runtime==4.9.3
 requests==2.32.3
 tqdm==4.67.3
 accelerate==1.12.0
 einops==0.8.1
 huggingface_hub==0.36.2
-numexpr==2.11.0
 numpy==2.1.2
 pandas==2.3.1
 protobuf==4.25.3

scripts/pulid/eva_clip/tokenizer.py

@@ -8,7 +8,6 @@ import os
 from functools import lru_cache
 from typing import Union, List
 
-import ftfy
 import regex as re
 import torch
 
@@ -58,6 +57,9 @@ def get_pairs(word):
 
 
 def basic_clean(text):
+    from installer import install
+    install('ftfy')
+    import ftfy
     text = ftfy.fix_text(text)
     text = html.unescape(html.unescape(text))
     return text.strip()

scripts/pulid/pulid_sdxl.py

@@ -14,11 +14,12 @@ from torchvision.transforms import InterpolationMode
 from torchvision.transforms.functional import normalize, resize
 
 import insightface
-from basicsr.utils import img2tensor, tensor2img
 from facexlib.parsing import init_parsing_model
 from facexlib.utils.face_restoration_helper import FaceRestoreHelper
 from insightface.app import FaceAnalysis
 
+from .pulid_utils import img2tensor, tensor2img
+
 from eva_clip import create_model_and_transforms
 from eva_clip.constants import OPENAI_DATASET_MEAN, OPENAI_DATASET_STD
 from encoders_transformer import IDFormer, IDEncoder

wiki

@@ -1 +1 @@
-Subproject commit c0924688d04e3b41399f2cbd8e6050d937bebc06
+Subproject commit 51a98c9e39bc8a226987a10c54eaaba36bfa8e8e