Update app.py

app.py

@@ -28,14 +28,19 @@ def port_inc():
     else:
         os.environ["CUSTOM_PORT"]=str(int(env)+1)
 
-def init_pool():
+def init_pool(_1,_2):
+    global infer1
+    global infer2
+    infer1 = _1
+    infer2 = _2
     port_inc()
 
 #pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16, 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)
 #pipe2.unet = torch.compile(pipe2.unet, mode="reduce-overhead", fullgraph=True)
 
-PIPE = None
+pp1=pipe_t2i()
+pp2=pipe_i2i()
 
 def pipe_t2i():
     global PIPE
@@ -96,7 +101,7 @@ def generate_random_string(length):
     return ''.join(random.choice(characters) for _ in range(length))
 
 @spaces.GPU(duration=55)
-def Piper(pipe,_do):
+def Piper1(pipe,_do):
     pipe = pipe_t2i()
     try:
         retu = pipe(
@@ -139,7 +144,7 @@ def main(p1,p2,*result):
     rng = list(range(ln))
     arr = [p for _ in rng]
     out = None
-    with Pool(ln, initializer=init_pool) as pool:
+    with Pool(ln, initializer=init_pool, initargs=(pp1,pp2)) as pool:
         out = pool.imap(infer,arr)
     return list(out)
 
@@ -155,7 +160,7 @@ def infer(p):
         neg = _dont
     else:
         neg = None
-    output = Piper(pipe_t2i(),'A '+" ".join(_do))
+    output = Piper1(infer1,'A '+" ".join(_do))
     if output == None:
         return None
     else:
@@ -163,7 +168,7 @@ def infer(p):
     if neg == None:
         return name
     img = load_image(name).convert("RGB")
-    output2 = Piper2(pipe_i2i(),img,p1,neg)
+    output2 = Piper2(infer2,img,p1,neg)
     if output2 == None:
         return None
     else: