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: 23.7.0
   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"]

.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

@@ -9,21 +9,23 @@ from app_image_to_3d import create_demo as create_demo_image_to_3d
 from app_text_to_3d import create_demo as create_demo_text_to_3d
 from model import Model
 
-DESCRIPTION = '# [Shap-E](https://github.com/openai/shap-e)'
+DESCRIPTION = "# [Shap-E](https://github.com/openai/shap-e)"
 
 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>"
 
 model = Model()
 
-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.Tabs():
-        with gr.Tab(label='Text to 3D'):
+        with gr.Tab(label="Text to 3D"):
             create_demo_text_to_3d(model)
-        with gr.Tab(label='Image to 3D'):
+        with gr.Tab(label="Image to 3D"):
             create_demo_image_to_3d(model)
 demo.queue(max_size=10).launch()

app_image_to_3d.py

@@ -12,46 +12,53 @@ from utils import randomize_seed_fn
 
 
 def create_demo(model: Model) -> gr.Blocks:
-    if not pathlib.Path('corgi.png').exists():
+    if not pathlib.Path("corgi.png").exists():
         subprocess.run(
             shlex.split(
-                'wget https://raw.githubusercontent.com/openai/shap-e/d99cedaea18e0989e340163dbaeb4b109fa9e8ec/shap_e/examples/example_data/corgi.png -O corgi.png'
-            ))
-    examples = ['corgi.png']
+                "wget https://raw.githubusercontent.com/openai/shap-e/d99cedaea18e0989e340163dbaeb4b109fa9e8ec/shap_e/examples/example_data/corgi.png -O corgi.png"
+            )
+        )
+    examples = ["corgi.png"]
 
     def process_example_fn(image_path: str) -> str:
         return model.run_image(image_path)
 
     with gr.Blocks() as demo:
         with gr.Box():
-            image = gr.Image(label='Input image', show_label=False, type='pil')
-            run_button = gr.Button('Run')
-            result = gr.Model3D(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)
-                guidance_scale = gr.Slider(label='Guidance scale',
-                                           minimum=1,
-                                           maximum=20,
-                                           step=0.1,
-                                           value=3.0)
+            image = gr.Image(label="Input image", show_label=False, type="pil")
+            run_button = gr.Button("Run")
+            result = gr.Model3D(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)
+                guidance_scale = gr.Slider(
+                    label="Guidance scale",
+                    minimum=1,
+                    maximum=20,
+                    step=0.1,
+                    value=3.0,
+                )
                 num_inference_steps = gr.Slider(
-                    label='Number of inference steps',
+                    label="Number of inference steps",
                     minimum=1,
                     maximum=100,
                     step=1,
-                    value=64)
+                    value=64,
+                )
 
-        gr.Examples(examples=examples,
-                    inputs=image,
-                    outputs=result,
-                    fn=process_example_fn,
-                    cache_examples=CACHE_EXAMPLES)
+        gr.Examples(
+            examples=examples,
+            inputs=image,
+            outputs=result,
+            fn=process_example_fn,
+            cache_examples=CACHE_EXAMPLES,
+        )
 
         inputs = [
             image,
@@ -65,10 +72,11 @@ def create_demo(model: Model) -> gr.Blocks:
             inputs=[seed, randomize_seed],
             outputs=seed,
             queue=False,
+            api_name=False,
         ).then(
             fn=model.run_image,
             inputs=inputs,
             outputs=result,
-            api_name='image-to-3d',
+            api_name="image-to-3d",
         )
     return demo

app_text_to_3d.py

@@ -9,15 +9,15 @@ from utils import randomize_seed_fn
 
 def create_demo(model: Model) -> gr.Blocks:
     examples = [
-        'A chair that looks like an avocado',
-        'An airplane that looks like a banana',
-        'A spaceship',
-        'A birthday cupcake',
-        'A chair that looks like a tree',
-        'A green boot',
-        'A penguin',
-        'Ube ice cream cone',
-        'A bowl of vegetables',
+        "A chair that looks like an avocado",
+        "An airplane that looks like a banana",
+        "A spaceship",
+        "A birthday cupcake",
+        "A chair that looks like a tree",
+        "A green boot",
+        "A penguin",
+        "Ube ice cream cone",
+        "A bowl of vegetables",
     ]
 
     def process_example_fn(prompt: str) -> str:
@@ -25,39 +25,47 @@ def create_demo(model: Model) -> gr.Blocks:
 
     with gr.Blocks() as demo:
         with gr.Box():
-            with gr.Row(elem_id='prompt-container'):
-                prompt = gr.Text(label='Prompt',
-                                 show_label=False,
-                                 max_lines=1,
-                                 placeholder='Enter your prompt',
-                                 container=False)
-                run_button = gr.Button('Run', scale=0)
-            result = gr.Model3D(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)
-                guidance_scale = gr.Slider(label='Guidance scale',
-                                           minimum=1,
-                                           maximum=20,
-                                           step=0.1,
-                                           value=15.0)
+            with gr.Row(elem_id="prompt-container"):
+                prompt = gr.Text(
+                    label="Prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    container=False,
+                )
+                run_button = gr.Button("Run", scale=0)
+            result = gr.Model3D(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)
+                guidance_scale = gr.Slider(
+                    label="Guidance scale",
+                    minimum=1,
+                    maximum=20,
+                    step=0.1,
+                    value=15.0,
+                )
                 num_inference_steps = gr.Slider(
-                    label='Number of inference steps',
+                    label="Number of inference steps",
                     minimum=1,
                     maximum=100,
                     step=1,
-                    value=64)
+                    value=64,
+                )
 
-        gr.Examples(examples=examples,
-                    inputs=prompt,
-                    outputs=result,
-                    fn=process_example_fn,
-                    cache_examples=CACHE_EXAMPLES)
+        gr.Examples(
+            examples=examples,
+            inputs=prompt,
+            outputs=result,
+            fn=process_example_fn,
+            cache_examples=CACHE_EXAMPLES,
+        )
 
         inputs = [
             prompt,
@@ -70,20 +78,23 @@ def create_demo(model: Model) -> gr.Blocks:
             inputs=[seed, randomize_seed],
             outputs=seed,
             queue=False,
+            api_name=False,
         ).then(
             fn=model.run_text,
             inputs=inputs,
             outputs=result,
+            api_name=False,
         )
         run_button.click(
             fn=randomize_seed_fn,
             inputs=[seed, randomize_seed],
             outputs=seed,
             queue=False,
+            api_name=False,
         ).then(
             fn=model.run_text,
             inputs=inputs,
             outputs=result,
-            api_name='text-to-3d',
+            api_name="text-to-3d",
         )
     return demo

model.py

@@ -10,14 +10,11 @@ from diffusers.utils import export_to_ply
 
 class Model:
     def __init__(self):
-        self.device = torch.device(
-            'cuda' if torch.cuda.is_available() else 'cpu')
-        self.pipe = ShapEPipeline.from_pretrained('openai/shap-e',
-                                                  torch_dtype=torch.float16)
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        self.pipe = ShapEPipeline.from_pretrained("openai/shap-e", torch_dtype=torch.float16)
         self.pipe.to(self.device)
 
-        self.pipe_img = ShapEImg2ImgPipeline.from_pretrained(
-            'openai/shap-e-img2img', torch_dtype=torch.float16)
+        self.pipe_img = ShapEImg2ImgPipeline.from_pretrained("openai/shap-e-img2img", torch_dtype=torch.float16)
         self.pipe_img.to(self.device)
 
     def to_glb(self, ply_path: str) -> str:
@@ -26,40 +23,34 @@ class Model:
         mesh = mesh.apply_transform(rot)
         rot = trimesh.transformations.rotation_matrix(np.pi, [0, 1, 0])
         mesh = mesh.apply_transform(rot)
-        mesh_path = tempfile.NamedTemporaryFile(suffix='.glb', delete=False)
-        mesh.export(mesh_path.name, file_type='glb')
+        mesh_path = tempfile.NamedTemporaryFile(suffix=".glb", delete=False)
+        mesh.export(mesh_path.name, file_type="glb")
         return mesh_path.name
 
-    def run_text(self,
-                 prompt: str,
-                 seed: int = 0,
-                 guidance_scale: float = 15.0,
-                 num_steps: int = 64) -> str:
+    def run_text(self, prompt: str, seed: int = 0, guidance_scale: float = 15.0, num_steps: int = 64) -> str:
         generator = torch.Generator(device=self.device).manual_seed(seed)
-        images = self.pipe(prompt,
-                           generator=generator,
-                           guidance_scale=guidance_scale,
-                           num_inference_steps=num_steps,
-                           output_type='mesh').images
-        ply_path = tempfile.NamedTemporaryFile(suffix='.ply',
-                                               delete=False,
-                                               mode='w+b')
+        images = self.pipe(
+            prompt,
+            generator=generator,
+            guidance_scale=guidance_scale,
+            num_inference_steps=num_steps,
+            output_type="mesh",
+        ).images
+        ply_path = tempfile.NamedTemporaryFile(suffix=".ply", delete=False, mode="w+b")
         export_to_ply(images[0], ply_path.name)
         return self.to_glb(ply_path.name)
 
-    def run_image(self,
-                  image: PIL.Image.Image,
-                  seed: int = 0,
-                  guidance_scale: float = 3.0,
-                  num_steps: int = 64) -> str:
+    def run_image(
+        self, image: PIL.Image.Image, seed: int = 0, guidance_scale: float = 3.0, num_steps: int = 64
+    ) -> str:
         generator = torch.Generator(device=self.device).manual_seed(seed)
-        images = self.pipe_img(image,
-                               generator=generator,
-                               guidance_scale=guidance_scale,
-                               num_inference_steps=num_steps,
-                               output_type='mesh').images
-        ply_path = tempfile.NamedTemporaryFile(suffix='.ply',
-                                               delete=False,
-                                               mode='w+b')
+        images = self.pipe_img(
+            image,
+            generator=generator,
+            guidance_scale=guidance_scale,
+            num_inference_steps=num_steps,
+            output_type="mesh",
+        ).images
+        ply_path = tempfile.NamedTemporaryFile(suffix=".ply", delete=False, mode="w+b")
         export_to_ply(images[0], ply_path.name)
         return self.to_glb(ply_path.name)

settings.py

@@ -2,6 +2,6 @@ import os
 
 import numpy as np
 
-CACHE_EXAMPLES = os.getenv('CACHE_EXAMPLES') == '1'
+CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1"
 
 MAX_SEED = np.iinfo(np.int32).max