feat: latest comfyui, intial pyinstaller support

.pre-commit-config.yaml

@@ -6,17 +6,17 @@ repos:
     -   id: end-of-file-fixer
     -   id: trailing-whitespace
 -   repo: https://github.com/psf/black
-    rev: 23.12.1
+    rev: 24.1.1
     hooks:
     -   id: black
         exclude: ^hordelib/nodes/.*\..*$
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.11
+    rev: v0.2.1
     hooks:
     -    id: ruff
 -   repo: https://github.com/pre-commit/mirrors-mypy
     rev: 'v1.8.0'
     hooks:
     -   id: mypy
         exclude: ^examples/.*$ # FIXME
-        additional_dependencies: [pydantic, strenum, types-colorama, types-docutils, types-Pillow, types-psutil, types-Pygments, types-pywin32, types-PyYAML, types-regex, types-requests, types-setuptools, types-tabulate, types-tqdm, types-urllib3]
+        additional_dependencies: [pydantic, strenum, types-colorama, types-docutils, types-Pillow, types-psutil, types-Pygments, types-pywin32, types-PyYAML, types-regex, types-requests, types-setuptools, types-tabulate, types-tqdm, types-urllib3, horde_sdk]

hordelib/__pyinstaller.py

@@ -0,0 +1,10 @@
+import pathlib
+
+
+def get_hook_dirs() -> list[str]:
+    return [str(pathlib.Path(__file__).parent / "pyinstaller_hooks")]
+
+
+def get_PyInstaller_tests() -> list[str]:
+    return []  # FIXME
+    return [str(pathlib.Path(__file__).parent / "pyinstaller_tests")]

hordelib/consts.py

@@ -6,7 +6,7 @@
 
 from hordelib.config_path import get_hordelib_path
 
-COMFYUI_VERSION = "b4e915e74560bd2c090f9b4ed6b73b0781b7050e"
+COMFYUI_VERSION = "c5a369a33ddb622827552716d9b0119035a2e666"
 """The exact version of ComfyUI version to load."""
 
 REMOTE_PROXY = ""

hordelib/model_manager/base.py

@@ -498,17 +498,20 @@ def download_file(
                     response.raise_for_status()
 
                 # Write the content to file in chunks
-                with open(partial_pathname, "ab") as f, tqdm(
-                    # all optional kwargs
-                    unit="B",
-                    initial=partial_size,
-                    unit_scale=True,
-                    unit_divisor=1024,
-                    miniters=1,
-                    desc=filename,
-                    total=remote_file_size + partial_size,
-                    # disable=UserSettings.download_progress_callback is not None,
-                ) as pbar:
+                with (
+                    open(partial_pathname, "ab") as f,
+                    tqdm(
+                        # all optional kwargs
+                        unit="B",
+                        initial=partial_size,
+                        unit_scale=True,
+                        unit_divisor=1024,
+                        miniters=1,
+                        desc=filename,
+                        total=remote_file_size + partial_size,
+                        # disable=UserSettings.download_progress_callback is not None,
+                    ) as pbar,
+                ):
                     downloaded = partial_size
                     for chunk in response.iter_content(chunk_size=1024 * 1024 * 16):
                         response.raise_for_status()

hordelib/model_manager/hyper.py

@@ -1,4 +1,5 @@
 """Home for the controller class ModelManager, and related meta information."""
+
 import os
 import threading
 from collections.abc import Callable, Iterable
@@ -180,9 +181,9 @@ def init_model_managers(
             self.active_model_managers.append(
                 resolve_manager_to_load_type(
                     multiprocessing_lock=multiprocessing_lock,
-                    civitai_api_token=os.environ["CIVIT_API_TOKEN"]
-                    if "CIVIT_API_TOKEN" in os.environ.keys()
-                    else None,
+                    civitai_api_token=(
+                        os.environ["CIVIT_API_TOKEN"] if "CIVIT_API_TOKEN" in os.environ.keys() else None
+                    ),
                 ),
             )
 

hordelib/nodes/comfy_controlnet_preprocessors/hed/__init__.py

@@ -115,7 +115,7 @@ def __init__(self):
         )
         modelpath = os.path.join(builtins.annotator_ckpts_path, "network-bsds500.pth")
         if not os.path.exists(modelpath):
-            from comfy_controlnet_preprocessors.util import load_file_from_url
+            from hordelib.nodes.comfy_controlnet_preprocessors.util import load_file_from_url
 
             load_file_from_url(remote_model_path, model_dir=builtins.annotator_ckpts_path)
         self.netNetwork = Network(modelpath).to(model_management.get_torch_device()).eval()

hordelib/nodes/comfy_controlnet_preprocessors/leres/__init__.py

@@ -45,7 +45,7 @@ def download_model_if_not_existed():
     # if os.path.exists(old_model_path):
     #    model_path = old_model_path
     if not os.path.exists(model_path):
-        from comfy_controlnet_preprocessors.util import load_file_from_url
+        from hordelib.nodes.comfy_controlnet_preprocessors.util import load_file_from_url
 
         load_file_from_url(remote_model_path_leres, model_dir=builtins.annotator_ckpts_path)
         os.rename(os.path.join(builtins.annotator_ckpts_path, "res101.pth"), model_path)
@@ -66,7 +66,7 @@ def apply_leres(input_image, thr_a, thr_b):
     """ if boost and pix2pixmodel is None:
         pix2pixmodel_path = os.path.join(builtins.annotator_ckpts_path, "latest_net_G.pth")
         if not os.path.exists(pix2pixmodel_path):
-            from comfy_controlnet_preprocessors.util import load_file_from_url
+            from hordelib.nodes.comfy_controlnet_preprocessors.util import load_file_from_url
             load_file_from_url(remote_model_path_pix2pix, model_dir=builtins.annotator_ckpts_path)
 
         opt = TestOptions().parse()
@@ -84,7 +84,6 @@ def apply_leres(input_image, thr_a, thr_b):
     height, width, dim = input_image.shape
 
     with torch.no_grad():
-
         if boost:
             depth = estimateboost(input_image, model, 0, pix2pixmodel, max(width, height))
         else:

hordelib/nodes/comfy_controlnet_preprocessors/leres/leres/net_tools.py

@@ -9,21 +9,22 @@ def get_func(func_name):
     function in this module or the path to a function relative to the base
     'modeling' module.
     """
-    if func_name == '':
+    if func_name == "":
         return None
     try:
-        parts = func_name.split('.')
+        parts = func_name.split(".")
         # Refers to a function in this module
         if len(parts) == 1:
             return globals()[parts[0]]
         # Otherwise, assume we're referencing a module under modeling
-        module_name = 'comfy_controlnet_preprocessors.leres.leres.' + '.'.join(parts[:-1])
+        module_name = "hordelib.nodes.comfy_controlnet_preprocessors.leres.leres." + ".".join(parts[:-1])
         module = importlib.import_module(module_name)
         return getattr(module, parts[-1])
     except Exception:
-        print('Failed to f1ind function: %s', func_name)
+        print("Failed to f1ind function: %s", func_name)
         raise
 
+
 def load_ckpt(args, depth_model, shift_model, focal_model):
     """
     Load checkpoint.
@@ -32,13 +33,10 @@ def load_ckpt(args, depth_model, shift_model, focal_model):
         print("loading checkpoint %s" % args.load_ckpt)
         checkpoint = torch.load(args.load_ckpt)
         if shift_model is not None:
-            shift_model.load_state_dict(strip_prefix_if_present(checkpoint['shift_model'], 'module.'),
-                                    strict=True)
+            shift_model.load_state_dict(strip_prefix_if_present(checkpoint["shift_model"], "module."), strict=True)
         if focal_model is not None:
-            focal_model.load_state_dict(strip_prefix_if_present(checkpoint['focal_model'], 'module.'),
-                                    strict=True)
-        depth_model.load_state_dict(strip_prefix_if_present(checkpoint['depth_model'], "module."),
-                                    strict=True)
+            focal_model.load_state_dict(strip_prefix_if_present(checkpoint["focal_model"], "module."), strict=True)
+        depth_model.load_state_dict(strip_prefix_if_present(checkpoint["depth_model"], "module."), strict=True)
         del checkpoint
         torch.cuda.empty_cache()
 

hordelib/nodes/comfy_controlnet_preprocessors/midas/api.py

@@ -92,7 +92,7 @@ def load_model(model_type):
 
     elif model_type == "dpt_hybrid":  # DPT-Hybrid
         if not os.path.exists(model_path):
-            from comfy_controlnet_preprocessors.util import load_file_from_url
+            from hordelib.nodes.comfy_controlnet_preprocessors.util import load_file_from_url
 
             load_file_from_url(remote_model_path, model_dir=builtins.annotator_ckpts_path)
 

hordelib/nodes/comfy_controlnet_preprocessors/mlsd/__init__.py

@@ -19,7 +19,7 @@ class MLSDdetector:
     def __init__(self):
         model_path = os.path.join(builtins.annotator_ckpts_path, "mlsd_large_512_fp32.pth")
         if not os.path.exists(model_path):
-            from comfy_controlnet_preprocessors.util import load_file_from_url
+            from hordelib.nodes.comfy_controlnet_preprocessors.util import load_file_from_url
 
             load_file_from_url(remote_model_path, model_dir=builtins.annotator_ckpts_path)
         model = MobileV2_MLSD_Large()

hordelib/nodes/comfy_controlnet_preprocessors/openpose/__init__.py

@@ -20,7 +20,7 @@ def __init__(self):
         hand_modelpath = os.path.join(builtins.annotator_ckpts_path, "hand_pose_model.pth")
 
         if not os.path.exists(hand_modelpath):
-            from comfy_controlnet_preprocessors.util import load_file_from_url
+            from hordelib.nodes.comfy_controlnet_preprocessors.util import load_file_from_url
 
             load_file_from_url(body_model_path, model_dir=builtins.annotator_ckpts_path)
             load_file_from_url(hand_model_path, model_dir=builtins.annotator_ckpts_path)

hordelib/nodes/comfy_controlnet_preprocessors/pidinet/__init__.py

@@ -3,7 +3,7 @@
 import numpy as np
 from einops import rearrange
 from .model import pidinet
-from comfy_controlnet_preprocessors.util import load_state_dict, load_file_from_url
+from hordelib.nodes.comfy_controlnet_preprocessors.util import load_state_dict, load_file_from_url
 import builtins
 import model_management
 

hordelib/nodes/comfy_controlnet_preprocessors/uniformer/__init__.py

@@ -1,7 +1,11 @@
 import os
 
-from comfy_controlnet_preprocessors.uniformer.mmseg.apis import init_segmentor, inference_segmentor, show_result_pyplot
-from comfy_controlnet_preprocessors.uniformer.mmseg.core.evaluation import get_palette
+from hordelib.nodes.comfy_controlnet_preprocessors.uniformer.mmseg.apis import (
+    init_segmentor,
+    inference_segmentor,
+    show_result_pyplot,
+)
+from hordelib.nodes.comfy_controlnet_preprocessors.uniformer.mmseg.core.evaluation import get_palette
 import builtins
 
 import model_management
@@ -14,7 +18,7 @@ class UniformerDetector:
     def __init__(self):
         modelpath = os.path.join(builtins.annotator_ckpts_path, "upernet_global_small.pth")
         if not os.path.exists(modelpath):
-            from comfy_controlnet_preprocessors.util import load_file_from_url
+            from hordelib.nodes.comfy_controlnet_preprocessors.util import load_file_from_url
 
             load_file_from_url(checkpoint_file, model_dir=builtins.annotator_ckpts_path)
         config_file = os.path.join(os.path.dirname(__file__), "exp", "upernet_global_small", "config.py")

hordelib/nodes/comfy_controlnet_preprocessors/uniformer/mmcv/cnn/bricks/activation.py

@@ -3,17 +3,18 @@
 import torch.nn as nn
 import torch.nn.functional as F
 
-from comfy_controlnet_preprocessors.uniformer.mmcv.utils import TORCH_VERSION, build_from_cfg, digit_version
+from hordelib.nodes.comfy_controlnet_preprocessors.uniformer.mmcv.utils import (
+    TORCH_VERSION,
+    build_from_cfg,
+    digit_version,
+)
 from .registry import ACTIVATION_LAYERS
 
-for module in [
-        nn.ReLU, nn.LeakyReLU, nn.PReLU, nn.RReLU, nn.ReLU6, nn.ELU,
-        nn.Sigmoid, nn.Tanh
-]:
+for module in [nn.ReLU, nn.LeakyReLU, nn.PReLU, nn.RReLU, nn.ReLU6, nn.ELU, nn.Sigmoid, nn.Tanh]:
     ACTIVATION_LAYERS.register_module(module=module)
 
 
-@ACTIVATION_LAYERS.register_module(name='Clip')
+@ACTIVATION_LAYERS.register_module(name="Clip")
 @ACTIVATION_LAYERS.register_module()
 class Clamp(nn.Module):
     """Clamp activation layer.
@@ -28,7 +29,7 @@ class Clamp(nn.Module):
             Default to 1.
     """
 
-    def __init__(self, min=-1., max=1.):
+    def __init__(self, min=-1.0, max=1.0):
         super(Clamp, self).__init__()
         self.min = min
         self.max = max
@@ -71,8 +72,7 @@ def forward(self, input):
         return F.gelu(input)
 
 
-if (TORCH_VERSION == 'parrots'
-        or digit_version(TORCH_VERSION) < digit_version('1.4')):
+if TORCH_VERSION == "parrots" or digit_version(TORCH_VERSION) < digit_version("1.4"):
     ACTIVATION_LAYERS.register_module(module=GELU)
 else:
     ACTIVATION_LAYERS.register_module(module=nn.GELU)