Feat pre commit lint

.github/ISSUE_TEMPLATE/bug_report.md

@@ -11,7 +11,7 @@ assignees: strint
 #### A clear and concise description of what the bug is.
 
 ### Your environment
-#### OS 
+#### OS
 
 #### OneDiff git commit id
 

.github/workflows/examples.yml

@@ -242,7 +242,7 @@ jobs:
           SDXL_BASE: ${{ env.SDXL_BASE }}
           UNET_INT8: ${{ env.UNET_INT8 }}
           SILICON_ONEDIFF_LICENSE_KEY: ${{ secrets.SILICON_ONEDIFF_LICENSE_KEY }}
-          
+
       - name: Setup docker for WebUI Test
         if: matrix.test-suite == 'webui'
         run: |
@@ -351,7 +351,7 @@ jobs:
         run: |
           docker exec -w /src/onediff ${{ env.CONTAINER_NAME }} python3 onediff_diffusers_extensions/examples/text_to_image_sd_enterprise.py  --model /share_nfs/hf_models/stable-diffusion-v1-5-int8 --width 512 --height 512 --saved_image /src/onediff/output_enterprise_sd.png
           docker exec -w /src/onediff ${{ env.CONTAINER_NAME }} python3 tests/test_quantitative_quality.py
-      
+
       - name: Install Requirements for WebUI
         if: matrix.test-suite == 'webui'
         run: |

.pre-commit-config.yaml

@@ -0,0 +1,30 @@
+exclude: '((generator.py)|(generated/.*))$'
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.0.1
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-docstring-first
+      - id: check-toml
+      - id: check-yaml
+        exclude: packaging/.*
+        args:
+          - --allow-multiple-documents
+      - id: mixed-line-ending
+        args: [--fix=lf]
+      - id: end-of-file-fixer
+
+  - repo: https://github.com/omnilib/ufmt
+    rev: v1.3.3
+    hooks:
+      - id: ufmt
+        additional_dependencies:
+          - black == 22.3.0
+          - usort == 1.0.2
+
+#   - repo: https://github.com/PyCQA/pydocstyle
+#     rev: 6.1.1
+#     hooks:
+#       - id: pydocstyle
+#

README.md

@@ -60,7 +60,7 @@ For example:
     + [onediff Enterprise Edition](#onediff-enterprise-edition)
 <!-- tocstop -->
 
-## Documentation 
+## Documentation
 onediff is the abbreviation of "**one** line of code to accelerate **diff**usion models".
 
 ### Use with HF diffusers and ComfyUI
@@ -180,8 +180,20 @@ python3 -m pip install --pre onediff
 - From source
 ```
 git clone https://github.com/siliconflow/onediff.git
+```
+```
 cd onediff && python3 -m pip install -e .
 ```
+Or install for development:
+```
+# install for dev
+cd onediff && python3 -m pip install -e '.[dev]'
+
+# code formatting and linting
+pip3 install pre-commit
+pre-commit install
+pre-commit run --all-files
+```
 
 > **_NOTE:_** If you intend to utilize plugins for ComfyUI/StableDiffusion-WebUI, we highly recommend installing OneDiff from the source rather than PyPI. This is necessary as you'll need to manually copy (or create a soft link) for the relevant code into the extension folder of these UIs/Libs.
 

README_ENTERPRISE.md

@@ -122,7 +122,7 @@ Ensure that you have installed [OneDiff ComfyUI Nodes](onediff_comfy_nodes/READM
 
   For more information and to **access the model files and Workflow below**, please visit [Hugging Face - stable-diffusion-v1-5-onediff-enterprise-v1](https://huggingface.co/siliconflow/stable-diffusion-v1-5-onediff-comfy-enterprise-v1/tree/main).
 
-<details> 
+<details>
 <summary> Download the required model files </summary>
 
 1. Download the [`v1-5-pruned.safetensors`](https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned.safetensors) file and place it in the `ComfyUI/models/checkpoints/` directory:
@@ -149,7 +149,7 @@ Click the links below to view the workflow images, or load them directly into Co
 
   For more information and to **access the model files and Workflow below**, please visit [Hugging Face - stable-diffusion-v2-1-onediff-enterprise](https://huggingface.co/siliconflow/stable-diffusion-v2-1-onediff-comfy-enterprise/tree/main).
 
-<details> 
+<details>
 <summary> Download the required model files </summary>
 
 1. Download the [`v2-1_768-ema-pruned.zip`](https://huggingface.co/siliconflow/stable-diffusion-v2-1-onediff-comfy-enterprise/blob/main/v2-1_768-ema-pruned.zip) file and unzip ,then place the .safetensors in the `ComfyUI/models/checkpoints/` directory:
@@ -166,15 +166,15 @@ wget https://huggingface.co/siliconflow/stable-diffusion-v2-1-onediff-comfy-ente
 
 </details>
 
-Click the links below to view the workflow images, or load them directly into ComfyUI. 
+Click the links below to view the workflow images, or load them directly into ComfyUI.
 
   - Workflow: [SD 2.1](https://huggingface.co/siliconflow/stable-diffusion-v2-1-onediff-comfy-enterprise/blob/main/onediff_stable_diffusion_2_1.png)
 
 ### ComfyUI SDXL
 
   For model details and to **access the model files and Workflow below**, please  visit [Hugging Face - sdxl-base-1.0-onediff-comfy-enterprise-v1](https://huggingface.co/siliconflow/sdxl-base-1.0-onediff-comfy-enterprise-v1/tree/main).
 
-<details> 
+<details>
 <summary> Download the required model files </summary>
 
 1. Download the [`sd_xl_base_1.0.safetensors`](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors) file and place it in the `ComfyUI/models/checkpoints/` directory:
@@ -373,20 +373,20 @@ To download the necessary models, please visit the [siliconflow/stable-video-dif
 Run [image_to_video.py](benchmarks/image_to_video.py):
 
 ```bash
-python3 benchmarks/image_to_video.py \     
-  --model $model_path \    
-  --input-image path/to/input_image.jpg \     
-  --output-video path/to/output_image.mp4   
+python3 benchmarks/image_to_video.py \
+  --model $model_path \
+  --input-image path/to/input_image.jpg \
+  --output-video path/to/output_image.mp4
 ```
 
 #### SVD + DeepCache
 
 ```bash
-python3 benchmarks/image_to_video.py \     
-  --model $model_path \     
-  --deepcache \     
-  --input-image path/to/input_image.jpg \     
-  --output-video path/to/output_image.mp4 
+python3 benchmarks/image_to_video.py \
+  --model $model_path \
+  --deepcache \
+  --input-image path/to/input_image.jpg \
+  --output-video path/to/output_image.mp4
 ```
 
 ## Quantitative model

benchmarks/docker/_utils.py

@@ -1,12 +1,13 @@
 import hashlib
 import os
 import subprocess
-import yaml
 
-from git import Repo
+import yaml
 
 from _logger import logger
 
+from git import Repo
+
 
 def load_yaml(*, file):
     if not os.path.exists(file):

benchmarks/docker/main.py

@@ -1,35 +1,44 @@
 import argparse
-from datetime import datetime
 import os
 import sys
+from datetime import datetime
 from pathlib import Path
 
 ONEDIFFBOX_ROOT = Path(os.path.abspath(__file__)).parents[0]
 sys.path.insert(0, str(ONEDIFFBOX_ROOT))
 
+from _logger import logger
 from _utils import (
-    calculate_sha256,
-    setup_repo,
-    load_yaml,
-    generate_docker_file,
     build_image,
+    calculate_sha256,
     gen_docker_compose_yaml,
+    generate_docker_file,
+    load_yaml,
+    setup_repo,
 )
-from _logger import logger
 
 
 def parse_args():
     parser = argparse.ArgumentParser(description="Build OneDiff Box")
     formatted_datetime = datetime.now().strftime("%Y%m%d-%H%M")
 
     parser.add_argument(
-        "-y", "--yaml", type=str, default="config/community-default.yaml",
+        "-y",
+        "--yaml",
+        type=str,
+        default="config/community-default.yaml",
     )
     parser.add_argument(
-        "-i", "--image", type=str, default="onediff",
+        "-i",
+        "--image",
+        type=str,
+        default="onediff",
     )
     parser.add_argument(
-        "-t", "--tag", type=str, default=f"benchmark",
+        "-t",
+        "--tag",
+        type=str,
+        default=f"benchmark",
     )
     parser.add_argument(
         "-o",
@@ -39,10 +48,17 @@ def parse_args():
         help="the output directory of Dockerfile and Docker-compose file",
     )
     parser.add_argument(
-        "-c", "--context", type=str, default=".", help="the path to build context",
+        "-c",
+        "--context",
+        type=str,
+        default=".",
+        help="the path to build context",
     )
     parser.add_argument(
-        "-q", "--quiet", action="store_true", help="quiet mode",
+        "-q",
+        "--quiet",
+        action="store_true",
+        help="quiet mode",
     )
     args = parser.parse_args()
     return args
@@ -77,7 +93,10 @@ def parse_args():
 
     envs = image_config.pop("envs", [])
     volumes = image_config.pop(
-        "volumes", ["$BENCHMARK_MODEL_PATH:/benchmark_model:ro",],
+        "volumes",
+        [
+            "$BENCHMARK_MODEL_PATH:/benchmark_model:ro",
+        ],
     )
     compose_file, run_command = gen_docker_compose_yaml(
         f"onediff-benchmark-{version}", image_name, envs, volumes, args.output

benchmarks/image_to_video.py

@@ -30,19 +30,20 @@
 CACHE_INTERVAL = 3
 CACHE_BRANCH = 0
 
-import os
+import argparse
 import importlib
 import inspect
-import argparse
-import time
 import json
+import os
 import random
+import time
+
 from PIL import Image, ImageDraw
 
-import oneflow as flow
+import oneflow as flow  # usort: skip
 import torch
-from onediffx import compile_pipe, OneflowCompileOptions 
-from diffusers.utils import load_image, export_to_video
+from diffusers.utils import export_to_video, load_image
+from onediffx import compile_pipe, OneflowCompileOptions
 
 
 def parse_args():
@@ -84,10 +85,14 @@ def parse_args():
         default=ATTENTION_FP16_SCORE_ACCUM_MAX_M,
     )
     parser.add_argument(
-        "--alter-height", type=int, default=ALTER_HEIGHT,
+        "--alter-height",
+        type=int,
+        default=ALTER_HEIGHT,
     )
     parser.add_argument(
-        "--alter-width", type=int, default=ALTER_WIDTH,
+        "--alter-width",
+        type=int,
+        default=ALTER_WIDTH,
     )
     return parser.parse_args()
 
@@ -110,7 +115,8 @@ def load_pipe(
         from diffusers import ControlNetModel
 
         controlnet = ControlNetModel.from_pretrained(
-            controlnet, torch_dtype=torch.float16,
+            controlnet,
+            torch_dtype=torch.float16,
         )
         extra_kwargs["controlnet"] = controlnet
     if os.path.exists(os.path.join(model_name, "calibrate_info.txt")):
@@ -218,7 +224,12 @@ def main():
                 control_image = Image.new("RGB", (width, height))
                 draw = ImageDraw.Draw(control_image)
                 draw.ellipse(
-                    (width // 4, height // 4, width // 4 * 3, height // 4 * 3,),
+                    (
+                        width // 4,
+                        height // 4,
+                        width // 4 * 3,
+                        height // 4 * 3,
+                    ),
                     fill=(255, 255, 255),
                 )
                 del draw

benchmarks/instant_id.py

@@ -26,22 +26,23 @@
 CACHE_LAYER_ID = 0
 CACHE_BLOCK_ID = 0
 
-import sys
-import os
+import argparse
 import importlib
 import inspect
-import argparse
-import time
 import json
-import torch
-from PIL import Image, ImageDraw
-import numpy as np
+import os
+import sys
+import time
+
 import cv2
-from huggingface_hub import snapshot_download
+import numpy as np
+import torch
 from diffusers.utils import load_image
+from huggingface_hub import snapshot_download
 from insightface.app import FaceAnalysis
+from PIL import Image, ImageDraw
 
-import oneflow as flow
+import oneflow as flow  # usort: skip
 from onediffx import compile_pipe
 
 
@@ -97,7 +98,8 @@ def load_pipe(
         from diffusers import ControlNetModel
 
         controlnet = ControlNetModel.from_pretrained(
-            controlnet, torch_dtype=torch.float16,
+            controlnet,
+            torch_dtype=torch.float16,
         )
         extra_kwargs["controlnet"] = controlnet
     if os.path.exists(os.path.join(model_name, "calibrate_info.txt")):
@@ -183,13 +185,14 @@ def main():
     if args.repo is None:
         custom_pipeline = args.custom_pipeline
         from diffusers import DiffusionPipeline
+
         pipeline_cls = DiffusionPipeline
     else:
         sys.path.insert(0, args.repo)
 
         from pipeline_stable_diffusion_xl_instantid import (
-            StableDiffusionXLInstantIDPipeline as pipeline_cls,
             draw_kps,
+            StableDiffusionXLInstantIDPipeline as pipeline_cls,
         )
 
     if os.path.exists(args.controlnet):