Merge branch 'comfyanonymous:master' into pbar-throttle-priority

app/model_manager.py

@@ -44,7 +44,7 @@ class ModelFileManager:
         @routes.get("/experiment/models/{folder}")
         async def get_all_models(request):
             folder = request.match_info.get("folder", None)
-            if not folder in folder_paths.folder_names_and_paths:
+            if folder not in folder_paths.folder_names_and_paths:
                 return web.Response(status=404)
             files = self.get_model_file_list(folder)
             return web.json_response(files)
@@ -55,7 +55,7 @@ class ModelFileManager:
             path_index = int(request.match_info.get("path_index", None))
             filename = request.match_info.get("filename", None)
 
-            if not folder_name in folder_paths.folder_names_and_paths:
+            if folder_name not in folder_paths.folder_names_and_paths:
                 return web.Response(status=404)
 
             folders = folder_paths.folder_names_and_paths[folder_name]

comfy/hooks.py

@@ -527,7 +527,8 @@ class HookKeyframeGroup:
                         if self._current_keyframe.get_effective_guarantee_steps(max_sigma) > 0:
                             break
                     # if eval_c is outside the percent range, stop looking further
-                    else: break
+                    else:
+                        break
         # update steps current context is used
         self._current_used_steps += 1
         # update current timestep this was performed on

comfy/ldm/chroma_radiance/model.py

@@ -270,7 +270,7 @@ class ChromaRadiance(Chroma):
         bad_keys = tuple(
             k
             for k, v in overrides.items()
-            if type(v) != type(getattr(params, k)) and (v is not None or k not in nullable_keys)
+            if not isinstance(v, type(getattr(params, k))) and (v is not None or k not in nullable_keys)
         )
         if bad_keys:
             e = f"Invalid value(s) in transformer_options chroma_radiance_options: {', '.join(bad_keys)}"

comfy/ldm/hunyuan_video/upsampler.py

@@ -3,7 +3,8 @@ import torch.nn as nn
 import torch.nn.functional as F
 from comfy.ldm.modules.diffusionmodules.model import ResnetBlock, VideoConv3d
 from comfy.ldm.hunyuan_video.vae_refiner import RMS_norm
-import model_management, model_patcher
+import model_management
+import model_patcher
 
 class SRResidualCausalBlock3D(nn.Module):
     def __init__(self, channels: int):

comfy/ldm/modules/diffusionmodules/model.py

@@ -394,7 +394,8 @@ class Model(nn.Module):
                  attn_resolutions, dropout=0.0, resamp_with_conv=True, in_channels,
                  resolution, use_timestep=True, use_linear_attn=False, attn_type="vanilla"):
         super().__init__()
-        if use_linear_attn: attn_type = "linear"
+        if use_linear_attn:
+            attn_type = "linear"
         self.ch = ch
         self.temb_ch = self.ch*4
         self.num_resolutions = len(ch_mult)
@@ -548,7 +549,8 @@ class Encoder(nn.Module):
                  conv3d=False, time_compress=None,
                  **ignore_kwargs):
         super().__init__()
-        if use_linear_attn: attn_type = "linear"
+        if use_linear_attn:
+            attn_type = "linear"
         self.ch = ch
         self.temb_ch = 0
         self.num_resolutions = len(ch_mult)

comfy/ldm/modules/ema.py

@@ -45,7 +45,7 @@ class LitEma(nn.Module):
                     shadow_params[sname] = shadow_params[sname].type_as(m_param[key])
                     shadow_params[sname].sub_(one_minus_decay * (shadow_params[sname] - m_param[key]))
                 else:
-                    assert not key in self.m_name2s_name
+                    assert key not in self.m_name2s_name
 
     def copy_to(self, model):
         m_param = dict(model.named_parameters())
@@ -54,7 +54,7 @@ class LitEma(nn.Module):
             if m_param[key].requires_grad:
                 m_param[key].data.copy_(shadow_params[self.m_name2s_name[key]].data)
             else:
-                assert not key in self.m_name2s_name
+                assert key not in self.m_name2s_name
 
     def store(self, parameters):
         """

comfy/ldm/util.py

@@ -71,7 +71,7 @@ def count_params(model, verbose=False):
 
 
 def instantiate_from_config(config):
-    if not "target" in config:
+    if "target" not in config:
         if config == '__is_first_stage__':
             return None
         elif config == "__is_unconditional__":

comfy/model_management.py

@@ -1542,6 +1542,10 @@ def soft_empty_cache(force=False):
 def unload_all_models():
     free_memory(1e30, get_torch_device())
 
+def debug_memory_summary():
+    if is_amd() or is_nvidia():
+        return torch.cuda.memory.memory_summary()
+    return ""
 
 #TODO: might be cleaner to put this somewhere else
 import threading

comfy/taesd/taehv.py

@@ -154,7 +154,8 @@ class TAEHV(nn.Module):
             self._show_progress_bar = value
 
     def encode(self, x, **kwargs):
-        if self.patch_size > 1: x = F.pixel_unshuffle(x, self.patch_size)
+        if self.patch_size > 1:
+            x = F.pixel_unshuffle(x, self.patch_size)
         x = x.movedim(2, 1)  # [B, C, T, H, W] -> [B, T, C, H, W]
         if x.shape[1] % 4 != 0:
             # pad at end to multiple of 4
@@ -167,5 +168,6 @@ class TAEHV(nn.Module):
     def decode(self, x, **kwargs):
         x = self.process_in(x).movedim(2, 1)  # [B, C, T, H, W] -> [B, T, C, H, W]
         x = apply_model_with_memblocks(self.decoder, x, self.parallel, self.show_progress_bar)
-        if self.patch_size > 1: x = F.pixel_shuffle(x, self.patch_size)
+        if self.patch_size > 1:
+            x = F.pixel_shuffle(x, self.patch_size)
         return x[:, self.frames_to_trim:].movedim(2, 1)

comfy/text_encoders/llama.py

@@ -8,7 +8,6 @@ from comfy.ldm.modules.attention import optimized_attention_for_device
 import comfy.model_management
 import comfy.ldm.common_dit
 
-import comfy.model_management
 from . import qwen_vl
 
 @dataclass

comfy/utils.py

@@ -1259,6 +1259,8 @@ def convert_old_quants(state_dict, model_prefix="", metadata={}):
             out_sd = {}
             layers = {}
             for k in list(state_dict.keys()):
+                if k == scaled_fp8_key:
+                    continue
                 if not k.startswith(model_prefix):
                     out_sd[k] = state_dict[k]
                     continue

comfy_api_nodes/nodes_kling.py

@@ -807,6 +807,7 @@ class OmniProTextToVideoNode(IO.ComfyNode):
                 ),
                 IO.Combo.Input("aspect_ratio", options=["16:9", "9:16", "1:1"]),
                 IO.Combo.Input("duration", options=[5, 10]),
+                IO.Combo.Input("resolution", options=["1080p", "720p"], optional=True),
             ],
             outputs=[
                 IO.Video.Output(),
@@ -826,6 +827,7 @@ class OmniProTextToVideoNode(IO.ComfyNode):
         prompt: str,
         aspect_ratio: str,
         duration: int,
+        resolution: str = "1080p",
     ) -> IO.NodeOutput:
         validate_string(prompt, min_length=1, max_length=2500)
         response = await sync_op(
@@ -837,6 +839,7 @@ class OmniProTextToVideoNode(IO.ComfyNode):
                 prompt=prompt,
                 aspect_ratio=aspect_ratio,
                 duration=str(duration),
+                mode="pro" if resolution == "1080p" else "std",
             ),
         )
         return await finish_omni_video_task(cls, response)
@@ -872,6 +875,7 @@ class OmniProFirstLastFrameNode(IO.ComfyNode):
                     optional=True,
                     tooltip="Up to 6 additional reference images.",
                 ),
+                IO.Combo.Input("resolution", options=["1080p", "720p"], optional=True),
             ],
             outputs=[
                 IO.Video.Output(),
@@ -893,6 +897,7 @@ class OmniProFirstLastFrameNode(IO.ComfyNode):
         first_frame: Input.Image,
         end_frame: Input.Image | None = None,
         reference_images: Input.Image | None = None,
+        resolution: str = "1080p",
     ) -> IO.NodeOutput:
         prompt = normalize_omni_prompt_references(prompt)
         validate_string(prompt, min_length=1, max_length=2500)
@@ -936,6 +941,7 @@ class OmniProFirstLastFrameNode(IO.ComfyNode):
                 prompt=prompt,
                 duration=str(duration),
                 image_list=image_list,
+                mode="pro" if resolution == "1080p" else "std",
             ),
         )
         return await finish_omni_video_task(cls, response)
@@ -964,6 +970,7 @@ class OmniProImageToVideoNode(IO.ComfyNode):
                     "reference_images",
                     tooltip="Up to 7 reference images.",
                 ),
+                IO.Combo.Input("resolution", options=["1080p", "720p"], optional=True),
             ],
             outputs=[
                 IO.Video.Output(),
@@ -984,6 +991,7 @@ class OmniProImageToVideoNode(IO.ComfyNode):
         aspect_ratio: str,
         duration: int,
         reference_images: Input.Image,
+        resolution: str = "1080p",
     ) -> IO.NodeOutput:
         prompt = normalize_omni_prompt_references(prompt)
         validate_string(prompt, min_length=1, max_length=2500)
@@ -1005,6 +1013,7 @@ class OmniProImageToVideoNode(IO.ComfyNode):
                 aspect_ratio=aspect_ratio,
                 duration=str(duration),
                 image_list=image_list,
+                mode="pro" if resolution == "1080p" else "std",
             ),
         )
         return await finish_omni_video_task(cls, response)
@@ -1036,6 +1045,7 @@ class OmniProVideoToVideoNode(IO.ComfyNode):
                     tooltip="Up to 4 additional reference images.",
                     optional=True,
                 ),
+                IO.Combo.Input("resolution", options=["1080p", "720p"], optional=True),
             ],
             outputs=[
                 IO.Video.Output(),
@@ -1058,6 +1068,7 @@ class OmniProVideoToVideoNode(IO.ComfyNode):
         reference_video: Input.Video,
         keep_original_sound: bool,
         reference_images: Input.Image | None = None,
+        resolution: str = "1080p",
     ) -> IO.NodeOutput:
         prompt = normalize_omni_prompt_references(prompt)
         validate_string(prompt, min_length=1, max_length=2500)
@@ -1090,6 +1101,7 @@ class OmniProVideoToVideoNode(IO.ComfyNode):
                 duration=str(duration),
                 image_list=image_list if image_list else None,
                 video_list=video_list,
+                mode="pro" if resolution == "1080p" else "std",
             ),
         )
         return await finish_omni_video_task(cls, response)
@@ -1119,6 +1131,7 @@ class OmniProEditVideoNode(IO.ComfyNode):
                     tooltip="Up to 4 additional reference images.",
                     optional=True,
                 ),
+                IO.Combo.Input("resolution", options=["1080p", "720p"], optional=True),
             ],
             outputs=[
                 IO.Video.Output(),
@@ -1139,6 +1152,7 @@ class OmniProEditVideoNode(IO.ComfyNode):
         video: Input.Video,
         keep_original_sound: bool,
         reference_images: Input.Image | None = None,
+        resolution: str = "1080p",
     ) -> IO.NodeOutput:
         prompt = normalize_omni_prompt_references(prompt)
         validate_string(prompt, min_length=1, max_length=2500)
@@ -1171,6 +1185,7 @@ class OmniProEditVideoNode(IO.ComfyNode):
                 duration=None,
                 image_list=image_list if image_list else None,
                 video_list=video_list,
+                mode="pro" if resolution == "1080p" else "std",
             ),
         )
         return await finish_omni_video_task(cls, response)

comfy_api_nodes/nodes_tripo.py

@@ -155,7 +155,7 @@ class TripoTextToModelNode(IO.ComfyNode):
                 model_seed=model_seed,
                 texture_seed=texture_seed,
                 texture_quality=texture_quality,
-                face_limit=face_limit,
+                face_limit=face_limit if face_limit != -1 else None,
                 geometry_quality=geometry_quality,
                 auto_size=True,
                 quad=quad,
@@ -255,7 +255,7 @@ class TripoImageToModelNode(IO.ComfyNode):
                 texture_alignment=texture_alignment,
                 texture_seed=texture_seed,
                 texture_quality=texture_quality,
-                face_limit=face_limit,
+                face_limit=face_limit if face_limit != -1 else None,
                 auto_size=True,
                 quad=quad,
             ),
@@ -369,7 +369,7 @@ class TripoMultiviewToModelNode(IO.ComfyNode):
                 texture_quality=texture_quality,
                 geometry_quality=geometry_quality,
                 texture_alignment=texture_alignment,
-                face_limit=face_limit,
+                face_limit=face_limit if face_limit != -1 else None,
                 quad=quad,
             ),
         )

comfy_execution/graph.py

@@ -207,15 +207,15 @@ class ExecutionList(TopologicalSort):
         return self.output_cache.get(node_id) is not None
 
     def cache_link(self, from_node_id, to_node_id):
-        if not to_node_id in self.execution_cache:
+        if to_node_id not in self.execution_cache:
             self.execution_cache[to_node_id] = {}
         self.execution_cache[to_node_id][from_node_id] = self.output_cache.get(from_node_id)
-        if not from_node_id in self.execution_cache_listeners:
+        if from_node_id not in self.execution_cache_listeners:
             self.execution_cache_listeners[from_node_id] = set()
         self.execution_cache_listeners[from_node_id].add(to_node_id)
 
     def get_cache(self, from_node_id, to_node_id):
-        if not to_node_id in self.execution_cache:
+        if to_node_id not in self.execution_cache:
             return None
         value = self.execution_cache[to_node_id].get(from_node_id)
         if value is None:

comfy_extras/nodes_apg.py

@@ -55,7 +55,8 @@ class APG(io.ComfyNode):
         def pre_cfg_function(args):
             nonlocal running_avg, prev_sigma
 
-            if len(args["conds_out"]) == 1: return args["conds_out"]
+            if len(args["conds_out"]) == 1:
+                return args["conds_out"]
 
             cond = args["conds_out"][0]
             uncond = args["conds_out"][1]

comfy_extras/nodes_mahiro.py

@@ -10,7 +10,7 @@ class Mahiro(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="Mahiro",
-            display_name="Mahiro is so cute that she deserves a better guidance function!! (。・ω・。)",
+            display_name="Mahiro CFG",
             category="_for_testing",
             description="Modify the guidance to scale more on the 'direction' of the positive prompt rather than the difference between the negative prompt.",
             inputs=[

comfy_extras/nodes_upscale_model.py

@@ -78,18 +78,20 @@ class ImageUpscaleWithModel(io.ComfyNode):
         overlap = 32
 
         oom = True
-        while oom:
-            try:
-                steps = in_img.shape[0] * comfy.utils.get_tiled_scale_steps(in_img.shape[3], in_img.shape[2], tile_x=tile, tile_y=tile, overlap=overlap)
-                pbar = comfy.utils.ProgressBar(steps)
-                s = comfy.utils.tiled_scale(in_img, lambda a: upscale_model(a), tile_x=tile, tile_y=tile, overlap=overlap, upscale_amount=upscale_model.scale, pbar=pbar)
-                oom = False
-            except model_management.OOM_EXCEPTION as e:
-                tile //= 2
-                if tile < 128:
-                    raise e
+        try:
+            while oom:
+                try:
+                    steps = in_img.shape[0] * comfy.utils.get_tiled_scale_steps(in_img.shape[3], in_img.shape[2], tile_x=tile, tile_y=tile, overlap=overlap)
+                    pbar = comfy.utils.ProgressBar(steps)
+                    s = comfy.utils.tiled_scale(in_img, lambda a: upscale_model(a), tile_x=tile, tile_y=tile, overlap=overlap, upscale_amount=upscale_model.scale, pbar=pbar)
+                    oom = False
+                except model_management.OOM_EXCEPTION as e:
+                    tile //= 2
+                    if tile < 128:
+                        raise e
+        finally:
+            upscale_model.to("cpu")
 
-        upscale_model.to("cpu")
         s = torch.clamp(s.movedim(-3,-1), min=0, max=1.0)
         return io.NodeOutput(s)
 

comfy_extras/nodes_wan.py

@@ -817,7 +817,7 @@ def get_sample_indices(original_fps,
     if required_duration > total_frames / original_fps:
         raise ValueError("required_duration must be less than video length")
 
-    if not fixed_start is None and fixed_start >= 0:
+    if fixed_start is not None and fixed_start >= 0:
         start_frame = fixed_start
     else:
         max_start = total_frames - required_origin_frames

execution.py

@@ -601,6 +601,7 @@ async def execute(server, dynprompt, caches, current_item, extra_data, executed,
 
         if isinstance(ex, comfy.model_management.OOM_EXCEPTION):
             tips = "This error means you ran out of memory on your GPU.\n\nTIPS: If the workflow worked before you might have accidentally set the batch_size to a large number."
+            logging.info("Memory summary: {}".format(comfy.model_management.debug_memory_summary()))
             logging.error("Got an OOM, unloading all loaded models.")
             comfy.model_management.unload_all_models()
 

nodes.py

@@ -1663,8 +1663,6 @@ class LoadImage:
         output_masks = []
         w, h = None, None
 
-        excluded_formats = ['MPO']
-
         for i in ImageSequence.Iterator(img):
             i = node_helpers.pillow(ImageOps.exif_transpose, i)
 
@@ -1692,7 +1690,10 @@ class LoadImage:
             output_images.append(image)
             output_masks.append(mask.unsqueeze(0))
 
-        if len(output_images) > 1 and img.format not in excluded_formats:
+            if img.format == "MPO":
+                break  # ignore all frames except the first one for MPO format
+
+        if len(output_images) > 1:
             output_image = torch.cat(output_images, dim=0)
             output_mask = torch.cat(output_masks, dim=0)
         else:
@@ -2242,8 +2243,10 @@ async def init_external_custom_nodes():
 
         for possible_module in possible_modules:
             module_path = os.path.join(custom_node_path, possible_module)
-            if os.path.isfile(module_path) and os.path.splitext(module_path)[1] != ".py": continue
-            if module_path.endswith(".disabled"): continue
+            if os.path.isfile(module_path) and os.path.splitext(module_path)[1] != ".py":
+                continue
+            if module_path.endswith(".disabled"):
+                continue
             if args.disable_all_custom_nodes and possible_module not in args.whitelist_custom_nodes:
                 logging.info(f"Skipping {possible_module} due to disable_all_custom_nodes and whitelist_custom_nodes")
                 continue

pyproject.toml

@@ -15,12 +15,16 @@ lint.select = [
   "N805", # invalid-first-argument-name-for-method
   "S307", # suspicious-eval-usage
   "S102", # exec
+  "E",
   "T",    # print-usage
   "W",
   # The "F" series in Ruff stands for "Pyflakes" rules, which catch various Python syntax errors and undefined names.
   # See all rules here: https://docs.astral.sh/ruff/rules/#pyflakes-f
   "F",
 ]
+
+lint.ignore = ["E501", "E722", "E731", "E712", "E402", "E741"]
+
 exclude = ["*.ipynb", "**/generated/*.pyi"]
 
 [tool.pylint]

server.py

@@ -324,7 +324,7 @@ class PromptServer():
         @routes.get("/models/{folder}")
         async def get_models(request):
             folder = request.match_info.get("folder", None)
-            if not folder in folder_paths.folder_names_and_paths:
+            if folder not in folder_paths.folder_names_and_paths:
                 return web.Response(status=404)
             files = folder_paths.get_filename_list(folder)
             return web.json_response(files)
@@ -579,7 +579,7 @@ class PromptServer():
             folder_name = request.match_info.get("folder_name", None)
             if folder_name is None:
                 return web.Response(status=404)
-            if not "filename" in request.rel_url.query:
+            if "filename" not in request.rel_url.query:
                 return web.Response(status=404)
 
             filename = request.rel_url.query["filename"]
@@ -593,7 +593,7 @@ class PromptServer():
             if out is None:
                 return web.Response(status=404)
             dt = json.loads(out)
-            if not "__metadata__" in dt:
+            if "__metadata__" not in dt:
                 return web.Response(status=404)
             return web.json_response(dt["__metadata__"])