Update src/pipeline.py

src/pipeline.py

@@ -55,7 +55,7 @@ os.environ["TOKENIZERS_PARALLELISM"] = "True"
 torch._dynamo.config.suppress_errors = True
 
 Pipeline = None
-ids = "black-forest-labs/FLUX.1-schnell"
+Ids = "black-forest-labs/FLUX.1-schnell"
 Revision = "741f7c3ce8b383c54771c7003378a50191e9efe9"
 ckpt_id = "manbeast3b/Flux.1.schnell-quant2"
 ckpt_revision = "44eb293715147878512da10bf3bc47cd14ec8c55"
@@ -938,7 +938,8 @@ def aot_compile(name, model, **sample_kwargs):
 #         inductor_configs=options,
 #     )
 
-
+Ids = "black-forest-labs/FLUX.1-schnell"
+Revision = "741f7c3ce8b383c54771c7003378a50191e9efe9"
     
 @torch.no_grad()
 def f(model, **kwargs):
@@ -978,7 +979,7 @@ def load_pipeline() -> Pipeline:
     # print(f"{time=} seconds.")
     
     # pipeline = FluxPipeline.from_pretrained(ckpt_id, revision=ckpt_revision, transformer=None, local_files_only=True, torch_dtype=torch.bfloat16,)
-    pipeline = FluxPipeline.from_pretrained(ids, revision=Revision,  local_files_only=True, torch_dtype=torch.bfloat16,) # transformer=None,
+    pipeline = FluxPipeline.from_pretrained(Ids, revision=Revision,  local_files_only=True, torch_dtype=torch.bfloat16,) # transformer=None,
     pipeline.to("cuda")
     pipeline.to(memory_format=torch.channels_last)
     # pipeline.transformer = compiled_func