Migrate from yapf to black

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.2.0
+  rev: v4.4.0
   hooks:
   - id: check-executables-have-shebangs
   - id: check-json
@@ -8,29 +8,43 @@ repos:
   - id: check-shebang-scripts-are-executable
   - id: check-toml
   - id: check-yaml
-  - id: double-quote-string-fixer
   - id: end-of-file-fixer
   - id: mixed-line-ending
-    args: ['--fix=lf']
+    args: ["--fix=lf"]
   - id: requirements-txt-fixer
   - id: trailing-whitespace
 - repo: https://github.com/myint/docformatter
-  rev: v1.4
+  rev: v1.7.5
   hooks:
   - id: docformatter
-    args: ['--in-place']
+    args: ["--in-place"]
 - repo: https://github.com/pycqa/isort
   rev: 5.12.0
   hooks:
     - id: isort
+      args: ["--profile", "black"]
 - repo: https://github.com/pre-commit/mirrors-mypy
-  rev: v0.991
+  rev: v1.5.1
   hooks:
     - id: mypy
-      args: ['--ignore-missing-imports']
-      additional_dependencies: ['types-python-slugify']
-- repo: https://github.com/google/yapf
-  rev: v0.32.0
+      args: ["--ignore-missing-imports"]
+      additional_dependencies: ["types-python-slugify", "types-requests", "types-PyYAML"]
+- repo: https://github.com/psf/black
+  rev: 23.9.1
   hooks:
-  - id: yapf
-    args: ['--parallel', '--in-place']
+    - id: black
+      language_version: python3.10
+      args: ["--line-length", "119"]
+- repo: https://github.com/kynan/nbstripout
+  rev: 0.6.1
+  hooks:
+    - id: nbstripout
+      args: ["--extra-keys", "metadata.interpreter metadata.kernelspec cell.metadata.pycharm"]
+- repo: https://github.com/nbQA-dev/nbQA
+  rev: 1.7.0
+  hooks:
+    - id: nbqa-black
+    - id: nbqa-pyupgrade
+      args: ["--py37-plus"]
+    - id: nbqa-isort
+      args: ["--float-to-top"]

.style.yapf

@@ -1,5 +0,0 @@
-[style]
-based_on_style = pep8
-blank_line_before_nested_class_or_def = false
-spaces_before_comment = 2
-split_before_logical_operator = true

.vscode/settings.json

@@ -1,18 +1,21 @@
 {
-    "python.linting.enabled": true,
-    "python.linting.flake8Enabled": true,
-    "python.linting.pylintEnabled": false,
-    "python.linting.lintOnSave": true,
-    "python.formatting.provider": "yapf",
-    "python.formatting.yapfArgs": [
-        "--style={based_on_style: pep8, indent_width: 4, blank_line_before_nested_class_or_def: false, spaces_before_comment: 2, split_before_logical_operator: true}"
-    ],
     "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter",
         "editor.formatOnType": true,
         "editor.codeActionsOnSave": {
             "source.organizeImports": true
         }
     },
+    "black-formatter.args": [
+        "--line-length=119"
+    ],
+    "isort.args": ["--profile", "black"],
+    "flake8.args": [
+        "--max-line-length=119"
+    ],
+    "ruff.args": [
+        "--line-length=119"
+    ],
     "editor.formatOnSave": true,
     "files.insertFinalNewline": true
 }

app.py

@@ -13,25 +13,22 @@ import spaces
 import torch
 from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
 
-DESCRIPTION = '# zeroscope v2'
+DESCRIPTION = "# zeroscope v2"
 if not torch.cuda.is_available():
-    DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>'
+    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
 
-MAX_NUM_FRAMES = int(os.getenv('MAX_NUM_FRAMES', '200'))
-DEFAULT_NUM_FRAMES = min(MAX_NUM_FRAMES,
-                         int(os.getenv('DEFAULT_NUM_FRAMES', '24')))
+MAX_NUM_FRAMES = int(os.getenv("MAX_NUM_FRAMES", "200"))
+DEFAULT_NUM_FRAMES = min(MAX_NUM_FRAMES, int(os.getenv("DEFAULT_NUM_FRAMES", "24")))
 MAX_SEED = np.iinfo(np.int32).max
-CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv(
-    'CACHE_EXAMPLES') == '1'
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES") == "1"
 
 if torch.cuda.is_available():
-    pipe = DiffusionPipeline.from_pretrained('cerspense/zeroscope_v2_576w',
-                                             torch_dtype=torch.float16)
+    pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", torch_dtype=torch.float16)
+    pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
     pipe.enable_model_cpu_offload()
+    pipe.enable_vae_slicing()
 else:
-    pipe = DiffusionPipeline.from_pretrained('cerspense/zeroscope_v2_576w')
-pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
-pipe.enable_vae_slicing()
+    pipe = None
 
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
@@ -41,8 +38,8 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
 
 
 def to_video(frames: list[np.ndarray], fps: int) -> str:
-    out_file = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False)
-    writer = imageio.get_writer(out_file.name, format='FFMPEG', fps=fps)
+    out_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
+    writer = imageio.get_writer(out_file.name, format="FFMPEG", fps=fps)
     for frame in frames:
         writer.append_data(frame)
     writer.close()
@@ -50,59 +47,72 @@ def to_video(frames: list[np.ndarray], fps: int) -> str:
 
 
 @spaces.GPU
-def generate(prompt: str, seed: int, num_frames: int,
-             num_inference_steps: int) -> str:
+def generate(
+    prompt: str,
+    seed: int,
+    num_frames: int,
+    num_inference_steps: int,
+) -> str:
     generator = torch.Generator().manual_seed(seed)
-    frames = pipe(prompt,
-                  num_inference_steps=num_inference_steps,
-                  num_frames=num_frames,
-                  width=576,
-                  height=320,
-                  generator=generator).frames
+    frames = pipe(
+        prompt,
+        num_inference_steps=num_inference_steps,
+        num_frames=num_frames,
+        width=576,
+        height=320,
+        generator=generator,
+    ).frames
     return to_video(frames, 8)
 
 
 examples = [
-    ['An astronaut riding a horse', 0, 24, 25],
-    ['A panda eating bamboo on a rock', 0, 24, 25],
-    ['Spiderman is surfing', 0, 24, 25],
+    ["An astronaut riding a horse", 0, 24, 25],
+    ["A panda eating bamboo on a rock", 0, 24, 25],
+    ["Spiderman is surfing", 0, 24, 25],
 ]
 
-with gr.Blocks(css='style.css') as demo:
+with gr.Blocks(css="style.css") as demo:
     gr.Markdown(DESCRIPTION)
-    gr.DuplicateButton(value='Duplicate Space for private use',
-                       elem_id='duplicate-button',
-                       visible=os.getenv('SHOW_DUPLICATE_BUTTON') == '1')
+    gr.DuplicateButton(
+        value="Duplicate Space for private use",
+        elem_id="duplicate-button",
+        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
+    )
     with gr.Box():
         with gr.Row():
-            prompt = gr.Text(label='Prompt',
-                             show_label=False,
-                             max_lines=1,
-                             placeholder='Enter your prompt',
-                             container=False)
-            run_button = gr.Button('Generate video', scale=0)
-        result = gr.Video(label='Result', show_label=False)
-        with gr.Accordion('Advanced options', open=False):
-            seed = gr.Slider(label='Seed',
-                             minimum=0,
-                             maximum=MAX_SEED,
-                             step=1,
-                             value=0)
-            randomize_seed = gr.Checkbox(label='Randomize seed', value=True)
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt",
+                container=False,
+            )
+            run_button = gr.Button("Generate video", scale=0)
+        result = gr.Video(label="Result", show_label=False)
+        with gr.Accordion("Advanced options", open=False):
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
             num_frames = gr.Slider(
-                label='Number of frames',
+                label="Number of frames",
                 minimum=24,
                 maximum=MAX_NUM_FRAMES,
                 step=1,
                 value=24,
-                info=
-                'Note that the content of the video also changes when you change the number of frames.'
+                info="Note that the content of the video also changes when you change the number of frames.",
+            )
+            num_inference_steps = gr.Slider(
+                label="Number of inference steps",
+                minimum=10,
+                maximum=50,
+                step=1,
+                value=25,
             )
-            num_inference_steps = gr.Slider(label='Number of inference steps',
-                                            minimum=10,
-                                            maximum=50,
-                                            step=1,
-                                            value=25)
 
     inputs = [
         prompt,
@@ -110,11 +120,13 @@ with gr.Blocks(css='style.css') as demo:
         num_frames,
         num_inference_steps,
     ]
-    gr.Examples(examples=examples,
-                inputs=inputs,
-                outputs=result,
-                fn=generate,
-                cache_examples=CACHE_EXAMPLES)
+    gr.Examples(
+        examples=examples,
+        inputs=inputs,
+        outputs=result,
+        fn=generate,
+        cache_examples=CACHE_EXAMPLES,
+    )
 
     prompt.submit(
         fn=randomize_seed_fn,
@@ -126,7 +138,7 @@ with gr.Blocks(css='style.css') as demo:
         fn=generate,
         inputs=inputs,
         outputs=result,
-        api_name='run',
+        api_name="run",
     )
     run_button.click(
         fn=randomize_seed_fn,
@@ -140,4 +152,6 @@ with gr.Blocks(css='style.css') as demo:
         outputs=result,
         api_name=False,
     )
-demo.queue(max_size=10).launch()
+
+if __name__ == "__main__":
+    demo.queue(max_size=10).launch()