Update app.py

app.py

@@ -31,7 +31,6 @@ def init_pool(q):
 _dynamo.config.suppress_errors = True
 
 mp.set_start_method("fork", force=True)
-b=mp.Queue()
 
 #pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16, revision="refs/pr/1", token=os.getenv("hf_token")).to(device)
 #pipe2 = StableDiffusionXLImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True).to(device)
@@ -139,16 +138,15 @@ def main(p1,p2):
     p = {"a":p1_en,"b":p2_en}
     ln = len(result)
     rng = list(range(ln))
-    for _ in rng:
-        b.put(p)
-    with mp.Pool(ln, initializer=init_pool, initargs=(b,)) as pool:
-        out = pool.map(infer,rng)
+    arr = [p for _ in rng]
+    with mp.Pool(ln, initializer=init_pool as pool:
+        out = pool.imap(infer,arr)
         pool.clear()
         return list(out.get())
 
-def infer(_):
-    p1 = b["a"]
-    p2 = b["b"]
+def infer(p):
+    p1 = p["a"]
+    p2 = p["b"]
     name = generate_random_string(12)+".png"
     _do = ['beautiful', 'playful', 'photographed', 'realistic', 'dynamic poze', 'deep field', 'reasonable coloring', 'rough texture', 'best quality', 'focused']
     if p1 != "":