Update app.py

app.py

@@ -1,5 +1,3 @@
-import functools as ft
-
 import gradio as gr
 import torch
 import random
@@ -17,7 +15,6 @@ tokenizer = T5Tokenizer.from_pretrained("roborovski/superprompt-v1")
 model = T5ForConditionalGeneration.from_pretrained("roborovski/superprompt-v1", torch_dtype=torch.float16)
 model.to(device)
 
-@ft.lru_cache(maxsize=1024)
 def generate(your_prompt, max_new_tokens, repetition_penalty, temperature, model_precision_type, top_p, top_k, seed):
     if seed == 0:
         seed = random.randint(1, 2**32-1)
@@ -30,22 +27,21 @@ def generate(your_prompt, max_new_tokens, repetition_penalty, temperature, model
 
     model.to(dtype)
 
-    with torch.inference_mode():
-        input_text = f"Expand the following prompt to add more detail: {your_prompt}"
-        input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
+    input_text = f"Expand the following prompt to add more detail: {your_prompt}"
+    input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
         
-        outputs = model.generate(
-           input_ids,
-            max_new_tokens=max_new_tokens,
-            repetition_penalty=repetition_penalty,
-            do_sample=True,
-            temperature=temperature,
-            top_p=top_p,
-            top_k=top_k,
-        )
+    outputs = model.generate(
+        input_ids,
+        max_new_tokens=max_new_tokens,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        temperature=temperature,
+        top_p=top_p,
+        top_k=top_k,
+    )
         
-        better_prompt = tokenizer.decode(outputs[0], skip_special_tokens=True)
-        return better_prompt
+    better_prompt = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return better_prompt
 
 
 your_prompt = gr.Textbox(label="Your Prompt", interactive=True)
@@ -62,7 +58,7 @@ top_p = gr.Slider(value=1, minimum=0, maximum=2, step=0.05, interactive=True, la
 
 top_k = gr.Slider(value=1, minimum=1, maximum=100, step=1, interactive=True, label="Top K", info="Higher k means more diverse outputs by considering a range of tokens")
 
-seed = gr.Number(value=42, interactive=True, label="Seed", info="A starting point to initiate the generation process, put 0 for a random one")
+seed = gr.Slider(value=42, minimum=0, maximum=2**32-1, interactive=True, label="Seed", info="A starting point to initiate the generation process, put 0 for a random one")
 
 examples = [
     ["A storefront with 'Text to Image' written on it.", 512, 1.2, 0.5, "fp16", 1, 50, 42]