Update

.pre-commit-config.yaml

@@ -1,35 +1,60 @@
 repos:
-- repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.2.0
-  hooks:
-  - id: check-executables-have-shebangs
-  - id: check-json
-  - id: check-merge-conflict
-  - 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']
-  - id: requirements-txt-fixer
-  - id: trailing-whitespace
-- repo: https://github.com/myint/docformatter
-  rev: v1.4
-  hooks:
-  - id: docformatter
-    args: ['--in-place']
-- repo: https://github.com/pycqa/isort
-  rev: 5.12.0
-  hooks:
-    - id: isort
-- repo: https://github.com/pre-commit/mirrors-mypy
-  rev: v0.991
-  hooks:
-    - id: mypy
-      args: ['--ignore-missing-imports']
-- repo: https://github.com/google/yapf
-  rev: v0.32.0
-  hooks:
-  - id: yapf
-    args: ['--parallel', '--in-place']
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.6.0
+    hooks:
+      - id: check-executables-have-shebangs
+      - id: check-json
+      - id: check-merge-conflict
+      - id: check-shebang-scripts-are-executable
+      - id: check-toml
+      - id: check-yaml
+      - id: end-of-file-fixer
+      - id: mixed-line-ending
+        args: ["--fix=lf"]
+      - id: requirements-txt-fixer
+      - id: trailing-whitespace
+  - repo: https://github.com/myint/docformatter
+    rev: v1.7.5
+    hooks:
+      - id: docformatter
+        args: ["--in-place"]
+  - repo: https://github.com/pycqa/isort
+    rev: 5.13.2
+    hooks:
+      - id: isort
+        args: ["--profile", "black"]
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v1.10.0
+    hooks:
+      - id: mypy
+        args: ["--ignore-missing-imports"]
+        additional_dependencies:
+          [
+            "types-python-slugify",
+            "types-requests",
+            "types-PyYAML",
+            "types-pytz",
+          ]
+  - repo: https://github.com/psf/black
+    rev: 24.4.2
+    hooks:
+      - id: black
+        language_version: python3.10
+        args: ["--line-length", "119"]
+  - repo: https://github.com/kynan/nbstripout
+    rev: 0.7.1
+    hooks:
+      - id: nbstripout
+        args:
+          [
+            "--extra-keys",
+            "metadata.interpreter metadata.kernelspec cell.metadata.pycharm",
+          ]
+  - repo: https://github.com/nbQA-dev/nbQA
+    rev: 1.8.5
+    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

@@ -0,0 +1,30 @@
+{
+    "editor.formatOnSave": true,
+    "files.insertFinalNewline": false,
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.formatOnType": true,
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
+    },
+    "[jupyter]": {
+        "files.insertFinalNewline": false
+    },
+    "black-formatter.args": [
+        "--line-length=119"
+    ],
+    "isort.args": ["--profile", "black"],
+    "flake8.args": [
+        "--max-line-length=119"
+    ],
+    "ruff.lint.args": [
+        "--line-length=119"
+    ],
+    "notebook.output.scrolling": true,
+    "notebook.formatOnCellExecution": true,
+    "notebook.formatOnSave.enabled": true,
+        "notebook.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
+}

README.md

@@ -4,7 +4,7 @@ emoji: 📚
 colorFrom: indigo
 colorTo: pink
 sdk: gradio
-sdk_version: 3.36.1
+sdk_version: 4.33.0
 app_file: app.py
 pinned: false
 suggested_hardware: t4-small

app.py

@@ -12,25 +12,25 @@ from huggingface_hub import hf_hub_download
 
 from model import Model
 
-DESCRIPTION = '# [MobileStyleGAN](https://github.com/bes-dev/MobileStyleGAN.pytorch)'
-SAMPLE_IMAGE_DIR = 'https://huggingface.co/spaces/hysts/MobileStyleGAN/resolve/main/samples'
-ARTICLE = f'''## Generated images
+DESCRIPTION = "# [MobileStyleGAN](https://github.com/bes-dev/MobileStyleGAN.pytorch)"
+SAMPLE_IMAGE_DIR = "https://huggingface.co/spaces/hysts/MobileStyleGAN/resolve/main/samples"
+ARTICLE = f"""## Generated images
 ### FFHQ
 - size: 1024x1024
 - seed: 0-99
 - truncation: 1.0
 ![FFHQ]({SAMPLE_IMAGE_DIR}/ffhq.jpg)
-'''
+"""
 
 
 def generate_z(z_dim: int, seed: int, device: torch.device) -> torch.Tensor:
-    return torch.from_numpy(np.random.RandomState(seed).randn(
-        1, z_dim)).to(device).float()
+    return torch.from_numpy(np.random.RandomState(seed).randn(1, z_dim)).to(device).float()
 
 
 @torch.inference_mode()
-def generate_image(seed: int, truncation_psi: float, generator: str,
-                   model: nn.Module, device: torch.device) -> np.ndarray:
+def generate_image(
+    seed: int, truncation_psi: float, generator: str, model: nn.Module, device: torch.device
+) -> np.ndarray:
     seed = int(np.clip(seed, 0, np.iinfo(np.uint32).max))
 
     z = generate_z(model.mapping_net.style_dim, seed, device)
@@ -41,11 +41,10 @@ def generate_image(seed: int, truncation_psi: float, generator: str,
 
 
 def load_model(device: torch.device) -> nn.Module:
-    path = hf_hub_download('public-data/MobileStyleGAN',
-                           'models/mobilestylegan_ffhq_v2.pth')
+    path = hf_hub_download("public-data/MobileStyleGAN", "models/mobilestylegan_ffhq_v2.pth")
     ckpt = torch.load(path)
     model = Model()
-    model.load_state_dict(ckpt['state_dict'], strict=False)
+    model.load_state_dict(ckpt["state_dict"], strict=False)
     model.eval()
     model.to(device)
     with torch.inference_mode():
@@ -54,36 +53,30 @@ def load_model(device: torch.device) -> nn.Module:
     return model
 
 
-device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 model = load_model(device)
 
 fn = functools.partial(generate_image, model=model, device=device)
 
-with gr.Blocks(css='style.css') as demo:
+with gr.Blocks(css="style.css") as demo:
     gr.Markdown(DESCRIPTION)
     with gr.Row():
         with gr.Column():
             with gr.Group():
-                seed = gr.Slider(label='Seed',
-                                 minimum=0,
-                                 maximum=100000,
-                                 step=1,
-                                 value=0,
-                                 randomize=True)
-                psi = gr.Slider(label='Truncation psi',
-                                minimum=0,
-                                maximum=2,
-                                step=0.05,
-                                value=1.0)
-                generator = gr.Radio(label='Generator',
-                                     choices=['student', 'teacher'],
-                                     type='value',
-                                     value='student')
-                run_button = gr.Button('Run')
+                seed = gr.Slider(label="Seed", minimum=0, maximum=100000, step=1, value=0, randomize=True)
+                psi = gr.Slider(label="Truncation psi", minimum=0, maximum=2, step=0.05, value=1.0)
+                generator = gr.Radio(label="Generator", choices=["student", "teacher"], type="value", value="student")
+                run_button = gr.Button("Run")
         with gr.Column():
-            result = gr.Image(label='Output', type='numpy')
+            result = gr.Image(label="Output", type="numpy")
     with gr.Row():
         gr.Markdown(ARTICLE)
 
-    run_button.click(fn=fn, inputs=[seed, psi, generator], outputs=result)
-demo.queue(max_size=10).launch()
+    run_button.click(
+        fn=fn,
+        inputs=[seed, psi, generator],
+        outputs=result,
+    )
+
+if __name__ == "__main__":
+    demo.queue(max_size=10).launch()

model.py

@@ -3,7 +3,7 @@ import sys
 import torch
 import torch.nn as nn
 
-sys.path.insert(0, 'MobileStyleGAN.pytorch')
+sys.path.insert(0, "MobileStyleGAN.pytorch")
 
 from core.models.mapping_network import MappingNetwork
 from core.models.mobile_synthesis_network import MobileSynthesisNetwork
@@ -14,33 +14,29 @@ class Model(nn.Module):
     def __init__(self):
         super().__init__()
         # teacher model
-        mapping_net_params = {'style_dim': 512, 'n_layers': 8, 'lr_mlp': 0.01}
+        mapping_net_params = {"style_dim": 512, "n_layers": 8, "lr_mlp": 0.01}
         synthesis_net_params = {
-            'size': 1024,
-            'style_dim': 512,
-            'blur_kernel': [1, 3, 3, 1],
-            'channels': [512, 512, 512, 512, 512, 256, 128, 64, 32]
+            "size": 1024,
+            "style_dim": 512,
+            "blur_kernel": [1, 3, 3, 1],
+            "channels": [512, 512, 512, 512, 512, 256, 128, 64, 32],
         }
         self.mapping_net = MappingNetwork(**mapping_net_params).eval()
         self.synthesis_net = SynthesisNetwork(**synthesis_net_params).eval()
         # student network
         self.student = MobileSynthesisNetwork(
-            style_dim=self.mapping_net.style_dim,
-            channels=synthesis_net_params['channels'][:-1])
+            style_dim=self.mapping_net.style_dim, channels=synthesis_net_params["channels"][:-1]
+        )
 
-        self.style_mean = nn.Parameter(torch.zeros((1, 512)),
-                                       requires_grad=False)
+        self.style_mean = nn.Parameter(torch.zeros((1, 512)), requires_grad=False)
 
-    def forward(self,
-                var: torch.Tensor,
-                truncation_psi: float = 0.5,
-                generator: str = 'student') -> torch.Tensor:
+    def forward(self, var: torch.Tensor, truncation_psi: float = 0.5, generator: str = "student") -> torch.Tensor:
         style = self.mapping_net(var)
         style = self.style_mean + truncation_psi * (style - self.style_mean)
-        if generator == 'student':
-            img = self.student(style)['img']
-        elif generator == 'teacher':
-            img = self.synthesis_net(style)['img']
+        if generator == "student":
+            img = self.student(style)["img"]
+        elif generator == "teacher":
+            img = self.synthesis_net(style)["img"]
         else:
             raise ValueError
         return img

requirements.txt

@@ -1,8 +1,8 @@
 git+https://github.com/fbcotter/pytorch_wavelets.git
-numpy==1.23.5
-Pillow==10.0.0
+numpy==1.26.4
+Pillow==10.3.0
 piq==0.6.0
 PyWavelets==1.2.0
-scipy==1.10.1
+scipy==1.13.1
 torch==2.0.1
 torchvision==0.15.2

style.css

@@ -1,3 +1,11 @@
 h1 {
   text-align: center;
+  display: block;
+}
+
+#duplicate-button {
+  margin: auto;
+  color: #fff;
+  background: #1565c0;
+  border-radius: 100vh;
 }