style: use latest ruff

imaginairy/__init__.py

@@ -1,4 +1,5 @@
 """Pythonic AI generation of images and videos"""
+
 import os
 
 # tells pytorch to allow MPS usage (for Mac M1 compatibility)

imaginairy/api/generate_refiners.py

@@ -271,9 +271,9 @@ def latent_logger(latents):
                             fit_width=prompt.width,
                             fit_height=prompt.height,
                         )
-                        result_images[
-                            f"control-{control_input.mode}"
-                        ] = control_image_disp
+                        result_images[f"control-{control_input.mode}"] = (
+                            control_image_disp
+                        )
                         controlnets.append((controlnet, control_image_t))
 
         for controlnet, control_image_t in controlnets:

imaginairy/cli/unslow_the_cli.py

@@ -5,6 +5,7 @@
 pkg_resources.require() which is called by setuptools to ensure the
 "correct" version of the package is installed.
 """
+
 import os
 
 

imaginairy/enhancers/bool_masker.py

@@ -16,6 +16,7 @@
   fruit{-0.1} OR bowl
 
 """
+
 import operator
 from abc import ABC
 from typing import ClassVar

imaginairy/enhancers/video_interpolation/rife/interpolate.py

@@ -54,9 +54,7 @@ def transfer_audio(sourceVideo, targetVideo):
             f'ffmpeg -y -i "{sourceVideo}" -c:a aac -b:a 160k -vn {tempAudioFileName}'
         )
         os.system(
-            'ffmpeg -y -i "{}" -i {} -c copy "{}"'.format(
-                targetNoAudio, tempAudioFileName, targetVideo
-            )
+            f'ffmpeg -y -i "{targetNoAudio}" -i {tempAudioFileName} -c copy "{targetVideo}"'
         )
         if (
             os.path.getsize(targetVideo) == 0
@@ -159,9 +157,7 @@ def interpolate_video_file(
         fourcc = cv2.VideoWriter_fourcc("m", "p", "4", "v")  # type: ignore
         video_path_wo_ext, ext = os.path.splitext(video_path)
         print(
-            "{}.{}, {} frames in total, {}FPS to {}FPS".format(
-                video_path_wo_ext, output_extension, tot_frame, fps, target_fps
-            )
+            f"{video_path_wo_ext}.{output_extension}, {tot_frame} frames in total, {fps}FPS to {target_fps}FPS"
         )
         if png_out is False and fpsNotAssigned is True:
             print("The audio will be merged after interpolation process")

imaginairy/img_processors/control_modes.py

@@ -1,4 +1,5 @@
 """Functions to create hint images for controlnet."""
+
 from typing import TYPE_CHECKING, Callable, Dict, Union
 
 if TYPE_CHECKING:

imaginairy/modules/diffusion/ddpm.py

@@ -7,6 +7,7 @@
 https://github.com/CompVis/taming-transformers
 -- merci.
 """
+
 import itertools
 import logging
 from contextlib import contextmanager, nullcontext
@@ -1602,9 +1603,9 @@ def log_images(
                     unconditional_conditioning=uc,
                 )
                 x_samples_cfg = self.decode_first_stage(samples_cfg)
-                log[
-                    f"samples_cfg_scale_{unconditional_guidance_scale:.2f}"
-                ] = x_samples_cfg
+                log[f"samples_cfg_scale_{unconditional_guidance_scale:.2f}"] = (
+                    x_samples_cfg
+                )
 
         if inpaint:
             # make a simple center square
@@ -1921,9 +1922,9 @@ def log_images(
                     unconditional_conditioning=uc_full,
                 )
                 x_samples_cfg = self.decode_first_stage(samples_cfg)
-                log[
-                    f"samples_cfg_scale_{unconditional_guidance_scale:.2f}"
-                ] = x_samples_cfg
+                log[f"samples_cfg_scale_{unconditional_guidance_scale:.2f}"] = (
+                    x_samples_cfg
+                )
 
         return log
 

imaginairy/modules/diffusion/util.py

@@ -9,7 +9,6 @@
 #
 # thanks!
 
-
 import logging
 import math
 

imaginairy/modules/midas/api.py

@@ -271,9 +271,7 @@ def load_model(
 
     if "openvino" not in model_type:
         print(
-            "Model loaded, number of parameters = {:.0f}M".format(
-                sum(p.numel() for p in model.parameters()) / 1e6
-            )
+            f"Model loaded, number of parameters = {sum(p.numel() for p in model.parameters()) / 1e6:.0f}M"
         )
     else:
         print("Model loaded, optimized with OpenVINO")

imaginairy/modules/midas/midas/dpt_depth.py

@@ -145,15 +145,9 @@ def forward(self, x):
 
 class DPTDepthModel(DPT):
     def __init__(self, path=None, non_negative=True, **kwargs):
-        features = kwargs["features"] if "features" in kwargs else 256
-        head_features_1 = (
-            kwargs["head_features_1"] if "head_features_1" in kwargs else features
-        )
-        head_features_2 = (
-            kwargs["head_features_2"] if "head_features_2" in kwargs else 32
-        )
-        kwargs.pop("head_features_1", None)
-        kwargs.pop("head_features_2", None)
+        features = kwargs.pop("features", 256)
+        head_features_1 = kwargs.pop("head_features_1", features)
+        head_features_2 = kwargs.pop("head_features_2", 32)
 
         head = nn.Sequential(
             nn.Conv2d(

imaginairy/modules/midas/midas/midas_net.py

@@ -3,6 +3,7 @@
 This file contains code that is adapted from
 https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py.
 """
+
 import torch
 from torch import nn
 

imaginairy/modules/midas/midas/midas_net_custom.py

@@ -3,6 +3,7 @@
 This file contains code that is adapted from
 https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py.
 """
+
 import torch
 from torch import nn
 

imaginairy/modules/midas/utils.py

@@ -1,4 +1,5 @@
 """Utils for monoDepth."""
+
 import re
 import sys
 

imaginairy/modules/sgm/diffusionmodules/sampling.py

@@ -1,8 +1,7 @@
 """
-    Partially ported from https://github.com/crowsonkb/k-diffusion/blob/master/k_diffusion/sampling.py
+Partially ported from https://github.com/crowsonkb/k-diffusion/blob/master/k_diffusion/sampling.py
 """
 
-
 from typing import Dict, Union
 
 import torch

imaginairy/modules/sgm/diffusionmodules/wrappers.py

@@ -30,7 +30,7 @@ def forward(
         return self.diffusion_model(
             x,
             timesteps=t,
-            context=c.get("crossattn", None),
-            y=c.get("vector", None),
+            context=c.get("crossattn"),
+            y=c.get("vector"),
             **kwargs,
         )

imaginairy/samplers/editing.py

@@ -3,6 +3,7 @@
 
 modified from https://github.com/timothybrooks/instruct-pix2pix/blob/main/edit_cli.py
 """
+
 import torch
 from einops import einops
 from torch import nn

imaginairy/utils/animations.py

@@ -1,4 +1,5 @@
 """Functions for creating animations from images."""
+
 import logging
 import os.path
 from typing import TYPE_CHECKING, List, Sequence

imaginairy/utils/feather_tile.py

@@ -159,7 +159,7 @@ def add_tiles(tiles, base_img, tile_coords, tile_size, overlap):
             t += 1
             column += 1
 
-        row += 1
+        row += 1  # noqa
         # if row >= 2:
         #     exit()
         column = 0

imaginairy/utils/img_utils.py

@@ -9,6 +9,7 @@
 Torch       (B), C, H, W    R, G, B             -1.0-1.0        torch.Tensor
 
 """
+
 from typing import Sequence
 
 import numpy as np

imaginairy/utils/paths.py

@@ -1,4 +1,5 @@
 """Code for defining package root path"""
+
 import os
 
 PKG_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))

imaginairy/weight_management/translators.py

@@ -118,9 +118,9 @@ def translate_weights(
                 new_key = f"Parallel.CLIPTextEncoderL.{k}"
                 new_sd[new_key] = text_encoder_l_weights.pop(k)
 
-        new_sd[
-            "Parallel.TextEncoderWithPooling.Parallel.Chain.Linear.weight"
-        ] = text_encoder_g_weights.pop("Linear.weight")
+        new_sd["Parallel.TextEncoderWithPooling.Parallel.Chain.Linear.weight"] = (
+            text_encoder_g_weights.pop("Linear.weight")
+        )
         for k in list(text_encoder_g_weights.keys()):
             if k.startswith("TransformerLayer_32"):
                 new_key = f"Parallel.TextEncoderWithPooling.Parallel.Chain.CLIPTextEncoderG.TransformerLayer{k[19:]}"

requirements-dev.in

@@ -5,6 +5,7 @@ mkdocs-click
 mkdocstrings[python]
 mypy
 ruff
+pip-tools
 pytest
 pytest-asyncio
 pytest-randomly