Lint unused import (comfyanonymous#5973)

* Lint unused import

* nit

* Remove unused imports

* revert fix_torch import

* nit

Author: huchenlei

.pylintrc

@@ -1,3 +1,3 @@
 [MESSAGES CONTROL]
 disable=all
-enable=eval-used
+enable=eval-used, unused-import

comfy/cldm/cldm.py

@@ -2,11 +2,9 @@
 #and modified
 
 import torch
-import torch as th
 import torch.nn as nn
 
 from ..ldm.modules.diffusionmodules.util import (
-    zero_module,
     timestep_embedding,
 )
 

comfy/cldm/dit_embedder.py

@@ -1,10 +1,8 @@
 import math
 from typing import List, Optional, Tuple
 
-import numpy as np
 import torch
 import torch.nn as nn
-from einops import rearrange
 from torch import Tensor
 
 from comfy.ldm.modules.diffusionmodules.mmdit import DismantledBlock, PatchEmbed, VectorEmbedder, TimestepEmbedder, get_2d_sincos_pos_embed_torch

comfy/cldm/mmdit.py

@@ -1,5 +1,5 @@
 import torch
-from typing import Dict, Optional
+from typing import Optional
 import comfy.ldm.modules.diffusionmodules.mmdit
 
 class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT):

comfy/extra_samplers/uni_pc.py

@@ -1,10 +1,9 @@
 #code taken from: https://github.com/wl-zhao/UniPC and modified
 
 import torch
-import torch.nn.functional as F
 import math
 
-from tqdm.auto import trange, tqdm
+from tqdm.auto import trange
 
 
 class NoiseScheduleVP:

comfy/ldm/audio/autoencoder.py

@@ -2,7 +2,7 @@
 
 import torch
 from torch import nn
-from typing import Literal, Dict, Any
+from typing import Literal
 import math
 import comfy.ops
 ops = comfy.ops.disable_weight_init

comfy/ldm/audio/embedders.py

@@ -2,8 +2,8 @@
 
 import torch
 import torch.nn as nn
-from torch import Tensor, einsum
-from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, TypeVar, Union
+from torch import Tensor
+from typing import List, Union
 from einops import rearrange
 import math
 import comfy.ops

comfy/ldm/cascade/controlnet.py

@@ -16,7 +16,6 @@
     along with this program.  If not, see <https://www.gnu.org/licenses/>.
 """
 
-import torch
 import torchvision
 from torch import nn
 from .common import LayerNorm2d_op

comfy/ldm/flux/controlnet.py

@@ -6,9 +6,7 @@
 from torch import Tensor, nn
 from einops import rearrange, repeat
 
-from .layers import (DoubleStreamBlock, EmbedND, LastLayer,
-                                 MLPEmbedder, SingleStreamBlock,
-                                 timestep_embedding)
+from .layers import (timestep_embedding)
 
 from .model import Flux
 import comfy.ldm.common_dit

comfy/ldm/genmo/joint_model/utils.py

@@ -1,7 +1,7 @@
 #original code from https://github.com/genmoai/models under apache 2.0 license
 #adapted to ComfyUI
 
-from typing import Optional, Tuple
+from typing import Optional
 
 import torch
 import torch.nn as nn

comfy/ldm/genmo/vae/model.py

@@ -1,7 +1,7 @@
 #original code from https://github.com/genmoai/models under apache 2.0 license
 #adapted to ComfyUI
 
-from typing import Callable, List, Optional, Tuple, Union
+from typing import List, Optional, Tuple, Union
 from functools import partial
 import math
 

comfy/ldm/hydit/controlnet.py

@@ -1,24 +1,17 @@
-from typing import Any, Optional
 
 import torch
 import torch.nn as nn
-import torch.nn.functional as F
 
-from torch.utils import checkpoint
 
 from comfy.ldm.modules.diffusionmodules.mmdit import (
-    Mlp,
     TimestepEmbedder,
     PatchEmbed,
-    RMSNorm,
 )
-from comfy.ldm.modules.diffusionmodules.util import timestep_embedding
 from .poolers import AttentionPool
 
 import comfy.latent_formats
 from .models import HunYuanDiTBlock, calc_rope
 
-from .posemb_layers import get_2d_rotary_pos_embed, get_fill_resize_and_crop
 
 
 class HunYuanControlNet(nn.Module):

comfy/ldm/hydit/models.py

@@ -1,8 +1,6 @@
-from typing import Any
 
 import torch
 import torch.nn as nn
-import torch.nn.functional as F
 
 import comfy.ops
 from comfy.ldm.modules.diffusionmodules.mmdit import Mlp, TimestepEmbedder, PatchEmbed, RMSNorm

comfy/ldm/hydit/poolers.py

@@ -1,6 +1,5 @@
 import torch
 import torch.nn as nn
-import torch.nn.functional as F
 from comfy.ldm.modules.attention import optimized_attention
 import comfy.ops
 

comfy/ldm/lightricks/vae/causal_video_autoencoder.py

@@ -3,7 +3,7 @@
 from functools import partial
 import math
 from einops import rearrange
-from typing import Any, Mapping, Optional, Tuple, Union, List
+from typing import Optional, Tuple, Union
 from .conv_nd_factory import make_conv_nd, make_linear_nd
 from .pixel_norm import PixelNorm
 

comfy/ldm/lightricks/vae/conv_nd_factory.py

@@ -1,6 +1,5 @@
 from typing import Tuple, Union
 
-import torch
 
 from .dual_conv3d import DualConv3d
 from .causal_conv3d import CausalConv3d

comfy/ldm/models/autoencoder.py

@@ -1,6 +1,6 @@
 import torch
 from contextlib import contextmanager
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, Dict, Tuple, Union
 
 from comfy.ldm.modules.distributions.distributions import DiagonalGaussianDistribution
 

comfy/ldm/modules/diffusionmodules/mmdit.py

@@ -1,5 +1,3 @@
-import logging
-import math
 from typing import Dict, Optional, List
 
 import numpy as np

comfy/ldm/modules/diffusionmodules/model.py

@@ -3,7 +3,6 @@
 import torch
 import torch.nn as nn
 import numpy as np
-from typing import Optional, Any
 import logging
 
 from comfy import model_management

comfy/ldm/modules/diffusionmodules/openaimodel.py

@@ -9,7 +9,6 @@
 from .util import (
     checkpoint,
     avg_pool_nd,
-    zero_module,
     timestep_embedding,
     AlphaBlender,
 )

comfy/ldm/modules/diffusionmodules/upscaling.py

@@ -4,7 +4,6 @@
 from functools import partial
 
 from .util import extract_into_tensor, make_beta_schedule
-from comfy.ldm.util import default
 
 
 class AbstractLowScaleModel(nn.Module):

comfy/ldm/modules/diffusionmodules/util.py

@@ -8,7 +8,6 @@
 # thanks!
 
 
-import os
 import math
 import torch
 import torch.nn as nn

comfy/ldm/modules/temporal_ae.py

@@ -1,5 +1,5 @@
 import functools
-from typing import Callable, Iterable, Union
+from typing import Iterable, Union
 
 import torch
 from einops import rearrange, repeat

comfy/sampler_helpers.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 import uuid
-import torch
 import comfy.model_management
 import comfy.conds
 import comfy.utils

comfy/text_encoders/spiece_tokenizer.py

@@ -1,4 +1,3 @@
-import os
 import torch
 
 class SPieceTokenizer:

comfy_extras/nodes_advanced_samplers.py

@@ -2,8 +2,7 @@
 import comfy.utils
 import torch
 import numpy as np
-from tqdm.auto import trange, tqdm
-import math
+from tqdm.auto import trange
 
 
 @torch.no_grad()

comfy_extras/nodes_clip_sdxl.py

@@ -1,4 +1,3 @@
-import torch
 from nodes import MAX_RESOLUTION
 
 class CLIPTextEncodeSDXLRefiner:

comfy_extras/nodes_compositing.py

@@ -1,4 +1,3 @@
-import numpy as np
 import torch
 import comfy.utils
 from enum import Enum

comfy_extras/nodes_hooks.py

@@ -4,7 +4,6 @@
 from collections.abc import Iterable
 
 if TYPE_CHECKING:
-    from comfy.model_patcher import ModelPatcher
     from comfy.sd import CLIP
 
 import comfy.hooks

comfy_extras/nodes_model_advanced.py

@@ -1,4 +1,3 @@
-import folder_paths
 import comfy.sd
 import comfy.model_sampling
 import comfy.latent_formats

comfy_extras/nodes_model_downscale.py

@@ -1,4 +1,3 @@
-import torch
 import comfy.utils
 
 class PatchModelAddDownscale:

comfy_extras/nodes_upscale_model.py

@@ -1,4 +1,3 @@
-import os
 import logging
 from spandrel import ModelLoader, ImageModelDescriptor
 from comfy import model_management

custom_nodes/websocket_image_save.py

@@ -1,7 +1,5 @@
-from PIL import Image, ImageOps
-from io import BytesIO
+from PIL import Image
 import numpy as np
-import struct
 import comfy.utils
 import time
 

execution.py

@@ -17,7 +17,6 @@
 from comfy_execution.graph_utils import is_link, GraphBuilder
 from comfy_execution.caching import HierarchicalCache, LRUCache, CacheKeySetInputSignature, CacheKeySetID
 from comfy_execution.validation import validate_node_input
-from comfy.cli_args import args
 
 class ExecutionResult(Enum):
     SUCCESS = 0

fix_torch.py

@@ -5,20 +5,24 @@
 import logging
 
 
-torch_spec = importlib.util.find_spec("torch")
-for folder in torch_spec.submodule_search_locations:
-    lib_folder = os.path.join(folder, "lib")
-    test_file = os.path.join(lib_folder, "fbgemm.dll")
-    dest = os.path.join(lib_folder, "libomp140.x86_64.dll")
-    if os.path.exists(dest):
-        break
-
-    with open(test_file, 'rb') as f:
-        contents = f.read()
-        if b"libomp140.x86_64.dll" not in contents:
+def fix_pytorch_libomp():
+    """
+    Fix PyTorch libomp DLL issue on Windows by copying the correct DLL file if needed.
+    """
+    torch_spec = importlib.util.find_spec("torch")
+    for folder in torch_spec.submodule_search_locations:
+        lib_folder = os.path.join(folder, "lib")
+        test_file = os.path.join(lib_folder, "fbgemm.dll")
+        dest = os.path.join(lib_folder, "libomp140.x86_64.dll")
+        if os.path.exists(dest):
             break
-    try:
-        mydll = ctypes.cdll.LoadLibrary(test_file)
-    except FileNotFoundError as e:
-        logging.warning("Detected pytorch version with libomp issue, patching.")
-        shutil.copyfile(os.path.join(lib_folder, "libiomp5md.dll"), dest)
+
+        with open(test_file, "rb") as f:
+            contents = f.read()
+            if b"libomp140.x86_64.dll" not in contents:
+                break
+        try:
+            mydll = ctypes.cdll.LoadLibrary(test_file)
+        except FileNotFoundError as e:
+            logging.warning("Detected pytorch version with libomp issue, patching.")
+            shutil.copyfile(os.path.join(lib_folder, "libiomp5md.dll"), dest)

folder_paths.py

@@ -4,7 +4,7 @@
 import time
 import mimetypes
 import logging
-from typing import Set, List, Dict, Tuple, Literal
+from typing import Literal
 from collections.abc import Collection
 
 supported_pt_extensions: set[str] = {'.ckpt', '.pt', '.bin', '.pth', '.safetensors', '.pkl', '.sft'}
@@ -133,7 +133,7 @@ def get_directory_by_type(type_name: str) -> str | None:
         return get_input_directory()
     return None
 
-def filter_files_content_types(files: List[str], content_types: Literal["image", "video", "audio"]) -> List[str]:
+def filter_files_content_types(files: list[str], content_types: Literal["image", "video", "audio"]) -> list[str]:
     """
     Example:
         files = os.listdir(folder_paths.get_input_directory())

latent_preview.py

@@ -1,7 +1,5 @@
 import torch
 from PIL import Image
-import struct
-import numpy as np
 from comfy.cli_args import args, LatentPreviewMethod
 from comfy.taesd.taesd import TAESD
 import comfy.model_management

main.py

@@ -87,7 +87,8 @@ def execute_script(script_path):
 
 if args.windows_standalone_build:
     try:
-        import fix_torch
+        from fix_torch import fix_pytorch_libomp
+        fix_pytorch_libomp()
     except:
         pass
 

script_examples/basic_api_example.py

@@ -1,6 +1,5 @@
 import json
-from urllib import request, parse
-import random
+from urllib import request
 
 #This is the ComfyUI api prompt format.
 

tests/inference/test_inference.py

@@ -1,6 +1,5 @@
 from copy import deepcopy
 from io import BytesIO
-from urllib import request
 import numpy
 import os
 from PIL import Image