Upload handler.py

handler.py

@@ -5,10 +5,10 @@ from diffusers import FluxPipeline, FluxTransformer2DModel, AutoencoderKL, Torch
 from PIL.Image import Image
 import torch
 
-import torch._dynamo
-torch._dynamo.config.suppress_errors = True
+#import torch._dynamo
+#torch._dynamo.config.suppress_errors = True
 
-#from huggingface_inference_toolkit.logging import logger
+from huggingface_inference_toolkit.logging import logger
 
 def compile_pipeline(pipe) -> Any:
     pipe.transformer.fuse_qkv_projections()
@@ -18,7 +18,7 @@ def compile_pipeline(pipe) -> Any:
 
 class EndpointHandler:
     def __init__(self, path="NoMoreCopyright/FLUX.1-dev-test"):
-        is_compile = True
+        is_compile = False
         #repo_id = "camenduru/FLUX.1-dev-diffusers"
         repo_id = "NoMoreCopyright/FLUX.1-dev-test"
         dtype = torch.bfloat16
@@ -31,7 +31,7 @@ class EndpointHandler:
 
     @torch.inference_mode()
     def __call__(self, data: Dict[str, Any]) -> Image:
-        #logger.info(f"Received incoming request with {data=}")
+        logger.info(f"Received incoming request with {data=}")
 
         if "inputs" in data and isinstance(data["inputs"], str):
             prompt = data.pop("inputs")