suppress waning for scheduler args #748

sdxl_gen_img.py

@@ -1309,7 +1309,10 @@ def main(args):
 
     # schedulerを用意する
     sched_init_args = {}
+    has_steps_offset = True
+    has_clip_sample = True
     scheduler_num_noises_per_step = 1
+
     if args.sampler == "ddim":
         scheduler_cls = DDIMScheduler
         scheduler_module = diffusers.schedulers.scheduling_ddim
@@ -1319,32 +1322,48 @@ def main(args):
     elif args.sampler == "pndm":
         scheduler_cls = PNDMScheduler
         scheduler_module = diffusers.schedulers.scheduling_pndm
+        has_clip_sample = False
     elif args.sampler == "lms" or args.sampler == "k_lms":
         scheduler_cls = LMSDiscreteScheduler
         scheduler_module = diffusers.schedulers.scheduling_lms_discrete
+        has_clip_sample = False
     elif args.sampler == "euler" or args.sampler == "k_euler":
         scheduler_cls = EulerDiscreteScheduler
         scheduler_module = diffusers.schedulers.scheduling_euler_discrete
+        has_clip_sample = False
     elif args.sampler == "euler_a" or args.sampler == "k_euler_a":
         scheduler_cls = EulerAncestralDiscreteScheduler
         scheduler_module = diffusers.schedulers.scheduling_euler_ancestral_discrete
+        has_clip_sample = False
     elif args.sampler == "dpmsolver" or args.sampler == "dpmsolver++":
         scheduler_cls = DPMSolverMultistepScheduler
         sched_init_args["algorithm_type"] = args.sampler
         scheduler_module = diffusers.schedulers.scheduling_dpmsolver_multistep
+        has_clip_sample = False
     elif args.sampler == "dpmsingle":
         scheduler_cls = DPMSolverSinglestepScheduler
         scheduler_module = diffusers.schedulers.scheduling_dpmsolver_singlestep
+        has_clip_sample = False
+        has_steps_offset = False
     elif args.sampler == "heun":
         scheduler_cls = HeunDiscreteScheduler
         scheduler_module = diffusers.schedulers.scheduling_heun_discrete
+        has_clip_sample = False
     elif args.sampler == "dpm_2" or args.sampler == "k_dpm_2":
         scheduler_cls = KDPM2DiscreteScheduler
         scheduler_module = diffusers.schedulers.scheduling_k_dpm_2_discrete
+        has_clip_sample = False
     elif args.sampler == "dpm_2_a" or args.sampler == "k_dpm_2_a":
         scheduler_cls = KDPM2AncestralDiscreteScheduler
         scheduler_module = diffusers.schedulers.scheduling_k_dpm_2_ancestral_discrete
         scheduler_num_noises_per_step = 2
+        has_clip_sample = False
+
+    # 警告を出さないようにする
+    if has_steps_offset:
+        sched_init_args["steps_offset"] = 1
+    if has_clip_sample:
+        sched_init_args["clip_sample"] = False
 
     # samplerの乱数をあらかじめ指定するための処理
 
@@ -1397,10 +1416,11 @@ def main(args):
         **sched_init_args,
     )
 
-    # clip_sample=Trueにする
+    # ↓以下は結局PipeでFalseに設定されるので意味がなかった
-    if hasattr(scheduler.config, "clip_sample") and scheduler.config.clip_sample is False:
+    # # clip_sample=Trueにする
-        print("set clip_sample to True")
+    # if hasattr(scheduler.config, "clip_sample") and scheduler.config.clip_sample is False:
-        scheduler.config.clip_sample = True
+    #     print("set clip_sample to True")
+    #     scheduler.config.clip_sample = True
 
     # deviceを決定する
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")  # "mps"を考量してない