make seed take a string

app.py

@@ -14,8 +14,8 @@ import torch
 import torch.nn as nn
 from huggingface_hub import hf_hub_download
 
-if os.environ.get('SYSTEM') == 'spaces':
-    subprocess.call('git apply ../patch'.split(), cwd='stylegan2-pytorch')
+#if os.environ.get('SYSTEM') == 'spaces':
+#    subprocess.call('git apply ../patch'.split(), cwd='stylegan2-pytorch')
 
 sys.path.insert(0, 'stylegan2-pytorch')
 
@@ -27,11 +27,7 @@ The model used here is the one converted from the model provided in [this site](
 
 Expected execution time on Hugging Face Spaces: 4s
 
-Related Apps:
-- [TADNE Image Viewer](https://huggingface.co/spaces/hysts/TADNE-image-viewer)
-- [TADNE Image Selector](https://huggingface.co/spaces/hysts/TADNE-image-selector)
-- [TADNE Interpolation](https://huggingface.co/spaces/hysts/TADNE-interpolation)
-- [TADNE Image Search with DeepDanbooru](https://huggingface.co/spaces/hysts/TADNE-image-search-with-DeepDanbooru)
+Based off of [hysts/TADNE](https://huggingface.co/spaces/hysts/TADNE)
 '''
 SAMPLE_IMAGE_DIR = 'https://huggingface.co/spaces/hysts/TADNE/resolve/main/samples'
 ARTICLE = f'''## Generated images
@@ -40,7 +36,6 @@ ARTICLE = f'''## Generated images
 - seed: 0-99
 ![samples]({SAMPLE_IMAGE_DIR}/sample.jpg)
 
-<center><img src="https://visitor-badge.glitch.me/badge?page_id=hysts.tadne" alt="visitor badge"/></center>
 '''
 
 TOKEN = os.environ['TOKEN']
@@ -82,11 +77,15 @@ def generate_z(z_dim: int, seed: int, device: torch.device) -> torch.Tensor:
 
 
 @torch.inference_mode()
-def generate_image(seed: int, truncation_psi: float, randomize_noise: bool,
+def generate_image(seed: str, truncation_psi: float, randomize_noise: bool,
                    model: nn.Module, device: torch.device) -> np.ndarray:
     seed = int(np.clip(seed, 0, np.iinfo(np.uint32).max))
 
-    z = generate_z(model.style_dim, seed, device)
+    arr=bytearray.fromhex(seed[2:])
+    z = np.random.RandomState(arr).randn(n_sample, inputSize).astype("float32")
+
+    #z = generate_z(model.style_dim, seed, device)
+    
     out, _ = model([z],
                    truncation=truncation_psi,
                    truncation_latent=model.latent_avg,
@@ -107,7 +106,7 @@ def main():
     gr.Interface(
         func,
         [
-            gr.inputs.Number(default=55376, label='Seed'),
+            gr.inputs.String(default="0x1f9840a85d5aF5bf1D1762F925BDADdC4201F984", label='Seed'),
             gr.inputs.Slider(
                 0, 2, step=0.05, default=0.7, label='Truncation psi'),
             gr.inputs.Checkbox(default=False, label='Randomize Noise'),