Update handler.py

handler.py

@@ -15,7 +15,7 @@ torch.set_float32_matmul_precision("high")
 
 import torch._dynamo
 torch._dynamo.config.suppress_errors = False # for debugging
-record=0
+
 class EndpointHandler:
     def __init__(self, path=""):
         self.pipe = FluxPipeline.from_pretrained(
@@ -47,6 +47,7 @@ class EndpointHandler:
         end_time = time.time()
         time_taken = end_time - start_time
         print(f"Time taken: {time_taken:.2f} seconds")
+        self.record=0
 
     def __call__(self, data: Dict[str, Any]) -> Union[Image.Image, None]:
         try:
@@ -62,7 +63,7 @@ class EndpointHandler:
                     " prompt to use for the image generation, and it needs to be a non-empty string."
                 )
             if prompt=="get_queue":
-                return record
+                return self.record
             parameters = data.pop("parameters", {})
 
             num_inference_steps = parameters.get("num_inference_steps", 28)
@@ -74,7 +75,7 @@ class EndpointHandler:
             # seed generator (seed cannot be provided as is but via a generator)
             seed = parameters.get("seed", 0)
             generator = torch.manual_seed(seed)
-            record+=1
+            self.record+=1
             start_time = time.time()
             result = self.pipe(  # type: ignore
                 prompt,
@@ -87,7 +88,7 @@ class EndpointHandler:
             end_time = time.time()
             time_taken = end_time - start_time
             print(f"Time taken: {time_taken:.2f} seconds")
-            record-=1
+            self.record-=1
 
             return result
         except Exception as e: