renamed function

app.py

@@ -14,7 +14,7 @@ N = 16
 cvae = ConditionalVariationalAutoEncoder()
 cvae.load_state_dict(torch.load('cvae.pth'))
 
-def greet(class_, species_, gender_):
+def generate(class_, species_, gender_):
     c_i = classes.index(class_)
     s_i = species.index(species_)
     g_i = genders.index(gender_)
@@ -35,7 +35,7 @@ def greet(class_, species_, gender_):
     return Z
 
 demo = gr.Interface(
-    fn=greet,
+    fn=generate,
     inputs=[
         gr.Dropdown(classes),
         gr.Dropdown(species),