Update

.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
 }

README.md

@@ -4,7 +4,7 @@ emoji: 📚
 colorFrom: purple
 colorTo: green
 sdk: gradio
-sdk_version: 3.36.1
+sdk_version: 3.44.4
 app_file: app.py
 pinned: false
 license: mit

app.py

@@ -8,37 +8,34 @@ import random
 import gradio as gr
 import numpy as np
 import PIL.Image
+import spaces
 import torch
 from diffusers import DDPMScheduler, DiffusionPipeline
 
-DESCRIPTION = '# Kandinsky 2.1'
+DESCRIPTION = "# Kandinsky 2.1"
 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_SEED = np.iinfo(np.int32).max
-CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv(
-    'CACHE_EXAMPLES') == '1'
-MAX_IMAGE_SIZE = int(os.getenv('MAX_IMAGE_SIZE', '768'))
-USE_TORCH_COMPILE = os.getenv('USE_TORCH_COMPILE') == '1'
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES") == "1"
+MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "768"))
+USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE") == "1"
 
-device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 if torch.cuda.is_available():
     pipe_prior = DiffusionPipeline.from_pretrained(
-        'kandinsky-community/kandinsky-2-1-prior', torch_dtype=torch.float16)
+        "kandinsky-community/kandinsky-2-1-prior", torch_dtype=torch.float16
+    )
     pipe_prior.to(device)
 
-    scheduler = DDPMScheduler.from_pretrained(
-        'kandinsky-community/kandinsky-2-1', subfolder='ddpm_scheduler')
+    scheduler = DDPMScheduler.from_pretrained("kandinsky-community/kandinsky-2-1", subfolder="ddpm_scheduler")
     pipe = DiffusionPipeline.from_pretrained(
-        'kandinsky-community/kandinsky-2-1',
-        scheduler=scheduler,
-        torch_dtype=torch.float16)
+        "kandinsky-community/kandinsky-2-1", scheduler=scheduler, torch_dtype=torch.float16
+    )
     pipe.to(device)
     if USE_TORCH_COMPILE:
         pipe.unet.to(memory_format=torch.channels_last)
-        pipe.unet = torch.compile(pipe.unet,
-                                  mode='reduce-overhead',
-                                  fullgraph=True)
+        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
 else:
     pipe_prior = None
     pipe = None
@@ -50,15 +47,18 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     return seed
 
 
-def generate(prompt: str,
-             negative_prompt: str = 'low quality, bad quality',
-             seed: int = 0,
-             width: int = 768,
-             height: int = 768,
-             guidance_scale_prior: float = 1.0,
-             guidance_scale: float = 4.0,
-             num_inference_steps_prior: int = 50,
-             num_inference_steps: int = 100) -> PIL.Image.Image:
+@spaces.GPU
+def generate(
+    prompt: str,
+    negative_prompt: str = "low quality, bad quality",
+    seed: int = 0,
+    width: int = 768,
+    height: int = 768,
+    guidance_scale_prior: float = 1.0,
+    guidance_scale: float = 4.0,
+    num_inference_steps_prior: int = 50,
+    num_inference_steps: int = 100,
+) -> PIL.Image.Image:
     generator = torch.Generator().manual_seed(seed)
     image_embeds, negative_image_embeds = pipe_prior(
         prompt,
@@ -81,85 +81,98 @@ def generate(prompt: str,
 
 
 examples = [
-    'An astronaut riding a horse',
-    'portrait of a young woman, blue eyes, cinematic',
-    'A alien cheeseburger creature eating itself, claymation, cinematic, moody lighting',
-    'bird eye view shot of a full body woman with cyan light orange magenta makeup, digital art, long braided hair her face separated by makeup in the style of yin Yang surrealism, symmetrical face, real image, contrasting tone, pastel gradient background',
-    'A car exploding into colorful dust',
-    'editorial photography of an organic, almost liquid smoke style armchair',
-    'birds eye view of a quilted paper style alien planet landscape, vibrant colours, Cinematic lighting',
+    "An astronaut riding a horse",
+    "portrait of a young woman, blue eyes, cinematic",
+    "A alien cheeseburger creature eating itself, claymation, cinematic, moody lighting",
+    "bird eye view shot of a full body woman with cyan light orange magenta makeup, digital art, long braided hair her face separated by makeup in the style of yin Yang surrealism, symmetrical face, real image, contrasting tone, pastel gradient background",
+    "A car exploding into colorful dust",
+    "editorial photography of an organic, almost liquid smoke style armchair",
+    "birds eye view of a quilted paper style alien planet landscape, vibrant colours, Cinematic lighting",
 ]
 
-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',
+                label="Prompt",
                 show_label=False,
                 max_lines=1,
-                placeholder='Enter your prompt',
+                placeholder="Enter your prompt",
                 container=False,
             )
-            run_button = gr.Button('Run', scale=0)
-        result = gr.Image(label='Result', show_label=False)
-        with gr.Accordion('Advanced options', open=False):
+            run_button = gr.Button("Run", scale=0)
+        result = gr.Image(label="Result", show_label=False)
+        with gr.Accordion("Advanced options", open=False):
             negative_prompt = gr.Text(
-                label='Negative prompt',
-                value='low quality, bad quality',
+                label="Negative prompt",
+                value="low quality, bad quality",
                 max_lines=1,
-                placeholder='Enter a negative prompt',
+                placeholder="Enter a negative prompt",
+            )
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
             )
-            seed = gr.Slider(label='Seed',
-                             minimum=0,
-                             maximum=MAX_SEED,
-                             step=1,
-                             value=0)
-            randomize_seed = gr.Checkbox(label='Randomize seed', value=True)
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
             width = gr.Slider(
-                label='Width',
+                label="Width",
                 minimum=256,
                 maximum=MAX_IMAGE_SIZE,
                 step=32,
                 value=768,
             )
             height = gr.Slider(
-                label='Height',
+                label="Height",
                 minimum=256,
                 maximum=MAX_IMAGE_SIZE,
                 step=32,
                 value=768,
             )
-            guidance_scale_prior = gr.Slider(label='Guidance scale for prior',
-                                             minimum=1,
-                                             maximum=20,
-                                             step=0.1,
-                                             value=4.0)
-            guidance_scale = gr.Slider(label='Guidance scale',
-                                       minimum=1,
-                                       maximum=20,
-                                       step=0.1,
-                                       value=4.0)
+            guidance_scale_prior = gr.Slider(
+                label="Guidance scale for prior",
+                minimum=1,
+                maximum=20,
+                step=0.1,
+                value=4.0,
+            )
+            guidance_scale = gr.Slider(
+                label="Guidance scale",
+                minimum=1,
+                maximum=20,
+                step=0.1,
+                value=4.0,
+            )
             num_inference_steps_prior = gr.Slider(
-                label='Number of inference steps for prior',
+                label="Number of inference steps for prior",
                 minimum=10,
                 maximum=100,
                 step=1,
-                value=50)
-            num_inference_steps = gr.Slider(label='Number of inference steps',
-                                            minimum=10,
-                                            maximum=150,
-                                            step=1,
-                                            value=100)
-
-    gr.Examples(examples=examples,
-                inputs=prompt,
-                outputs=result,
-                fn=generate,
-                cache_examples=CACHE_EXAMPLES)
+                value=50,
+            )
+            num_inference_steps = gr.Slider(
+                label="Number of inference steps",
+                minimum=10,
+                maximum=150,
+                step=1,
+                value=100,
+            )
+
+    gr.Examples(
+        examples=examples,
+        inputs=prompt,
+        outputs=result,
+        fn=generate,
+        cache_examples=CACHE_EXAMPLES,
+    )
 
     inputs = [
         prompt,
@@ -182,7 +195,7 @@ with gr.Blocks(css='style.css') as demo:
         fn=generate,
         inputs=inputs,
         outputs=result,
-        api_name='run',
+        api_name="run",
     )
     negative_prompt.submit(
         fn=randomize_seed_fn,
@@ -208,4 +221,6 @@ with gr.Blocks(css='style.css') as demo:
         outputs=result,
         api_name=False,
     )
-demo.queue(max_size=20).launch()
+
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()

requirements.txt

@@ -1,6 +1,6 @@
-accelerate==0.20.3
-diffusers==0.18.2
-gradio==3.36.1
-torch==2.0.1
-torchvision==0.15.2
-transformers==4.30.2
+accelerate==0.23.0
+diffusers==0.21.2
+gradio==3.44.4
+torch==2.0.0
+torchvision==0.15.1
+transformers==4.33.2