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run_xl_ediffi.py

@@ -21,29 +21,13 @@ start_time = time.time()
 random_generator = torch.Generator()
 random_generator.manual_seed(12345)
 
-scheduler = DPMSolverMultistepScheduler(
-    beta_start=0.00085,
-    beta_end=0.012,
-    beta_schedule="scaled_linear",
-    prediction_type="epsilon",
-    num_train_timesteps=1000,
-    trained_betas=None,
-    thresholding=False,
-    algorithm_type="dpmsolver++",
-    solver_type="midpoint",
-    lower_order_final=True,
-    use_karras_sigmas=True,
-)
-
 model_id = "stabilityai/stable-diffusion-xl-base-0.9"
 pipe_high_noise = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16", use_safetensors=True, local_files_only=True)
-# pipe_high_noise.scheduler = EulerDiscreteScheduler.from_config(pipe_high_noise.scheduler.config)
-pipe_high_noise.scheduler = scheduler
+pipe_high_noise.scheduler = DPMSolverMultistepScheduler.from_config(pipe_high_noise.scheduler.config)
 pipe_high_noise.to("cuda")
 
 pipe_low_noise = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
-# pipe_low_noise.scheduler = EulerDiscreteScheduler.from_config(pipe_low_noise.scheduler.config)
-pipe_low_noise.scheduler = scheduler
+pipe_low_noise.scheduler = pipe_high_noise.scheduler
 pipe_low_noise.to("cuda")
 
 prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"