make app.py lazy

app.py

@@ -14,13 +14,25 @@ def download(filename):
     return "models/" + filename
 
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
+cache = {}
+
+def load(name):
+    if name in cache:
+        return cache[name]
+    else:
+        model_config, model_path = models[name]
+        model = load_model(model_config, model_path, device=device)
+        cache[name] = model
+        return model
+
 models = {
-    "diffusion_db_128ch_1timesteps_openclip_vith14": load_model(get_model_config('ddgan_ddb_v2'), download('diffusion_db_128ch_1timesteps_openclip_vith14.th'), device=device),
-    #"diffusion_db_192ch_2timesteps_openclip_vith14": load_model(get_model_config('ddgan_ddb_v3'), download('diffusion_db_192ch_2timesteps_openclip_vith14.th'), device=device),
+    "diffusion_db_128ch_1timesteps_openclip_vith14": (get_model_config('ddgan_ddb_v2'), download('diffusion_db_128ch_1timesteps_openclip_vith14.th')),
+    "diffusion_db_192ch_2timesteps_openclip_vith14": (get_model_config('ddgan_ddb_v3'), download('diffusion_db_192ch_2timesteps_openclip_vith14.th')),
 }
 default = "diffusion_db_128ch_1timesteps_openclip_vith14"
 
 def gen(md, model_name, md2, text, seed, nb_samples, width, height):
+    model = load(model_name)
     torch.manual_seed(int(seed))
     model = models[model_name]
     nb_samples = int(nb_samples)