[Chore] switch to `logger.warning` (#7289)

switch to logger.warning

examples/research_projects/controlnet/train_controlnet_webdataset.py

@@ -407,7 +407,7 @@ def log_validation(vae, unet, controlnet, args, accelerator, weight_dtype, step)
 
             tracker.log({"validation": formatted_images})
         else:
-            logger.warn(f"image logging not implemented for {tracker.name}")
+            logger.warning(f"image logging not implemented for {tracker.name}")
 
         del pipeline
         gc.collect()
@@ -1057,7 +1057,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/research_projects/diffusion_dpo/train_diffusion_dpo.py

@@ -574,7 +574,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/research_projects/diffusion_dpo/train_diffusion_dpo_sdxl.py

@@ -672,7 +672,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/research_projects/instructpix2pix_lora/train_instruct_pix2pix_lora.py

@@ -516,7 +516,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/research_projects/intel_opts/textual_inversion/textual_inversion_bf16.py

@@ -608,7 +608,7 @@ def main():
     # Create the pipeline using using the trained modules and save it.
     if accelerator.is_main_process:
         if args.push_to_hub and args.only_save_embeds:
-            logger.warn("Enabling full model saving because --push_to_hub=True was specified.")
+            logger.warning("Enabling full model saving because --push_to_hub=True was specified.")
             save_full_model = True
         else:
             save_full_model = not args.only_save_embeds

examples/research_projects/lora/train_text_to_image_lora.py

@@ -541,7 +541,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/research_projects/multi_token_textual_inversion/textual_inversion.py

@@ -645,7 +645,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()
@@ -901,7 +901,7 @@ def main():
     accelerator.wait_for_everyone()
     if accelerator.is_main_process:
         if args.push_to_hub and args.only_save_embeds:
-            logger.warn("Enabling full model saving because --push_to_hub=True was specified.")
+            logger.warning("Enabling full model saving because --push_to_hub=True was specified.")
             save_full_model = True
         else:
             save_full_model = not args.only_save_embeds

examples/research_projects/onnxruntime/text_to_image/train_text_to_image.py

@@ -108,7 +108,7 @@ def log_validation(vae, text_encoder, tokenizer, unet, args, accelerator, weight
                 }
             )
         else:
-            logger.warn(f"image logging not implemented for {tracker.name}")
+            logger.warning(f"image logging not implemented for {tracker.name}")
 
     del pipeline
     torch.cuda.empty_cache()
@@ -523,7 +523,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/research_projects/onnxruntime/textual_inversion/textual_inversion.py

@@ -687,7 +687,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()
@@ -916,7 +916,7 @@ def main():
     accelerator.wait_for_everyone()
     if accelerator.is_main_process:
         if args.push_to_hub and not args.save_as_full_pipeline:
-            logger.warn("Enabling full model saving because --push_to_hub=True was specified.")
+            logger.warning("Enabling full model saving because --push_to_hub=True was specified.")
             save_full_model = True
         else:
             save_full_model = args.save_as_full_pipeline

examples/research_projects/onnxruntime/unconditional_image_generation/train_unconditional.py

@@ -410,7 +410,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             model.enable_xformers_memory_efficient_attention()

examples/research_projects/realfill/train_realfill.py

@@ -629,7 +629,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/t2i_adapter/train_t2i_adapter_sdxl.py

@@ -167,7 +167,7 @@ def log_validation(vae, unet, adapter, args, accelerator, weight_dtype, step):
 
             tracker.log({"validation": formatted_images})
         else:
-            logger.warn(f"image logging not implemented for {tracker.name}")
+            logger.warning(f"image logging not implemented for {tracker.name}")
 
         del pipeline
         gc.collect()
@@ -932,7 +932,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/text_to_image/train_text_to_image.py

@@ -183,7 +183,7 @@ def log_validation(vae, text_encoder, tokenizer, unet, args, accelerator, weight
                 }
             )
         else:
-            logger.warn(f"image logging not implemented for {tracker.name}")
+            logger.warning(f"image logging not implemented for {tracker.name}")
 
     del pipeline
     torch.cuda.empty_cache()
@@ -608,7 +608,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/text_to_image/train_text_to_image_lora.py

@@ -497,7 +497,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/text_to_image/train_text_to_image_lora_sdxl.py

@@ -616,7 +616,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/text_to_image/train_text_to_image_sdxl.py

@@ -712,7 +712,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()

examples/textual_inversion/textual_inversion.py

@@ -708,7 +708,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()
@@ -966,7 +966,7 @@ def main():
     accelerator.wait_for_everyone()
     if accelerator.is_main_process:
         if args.push_to_hub and not args.save_as_full_pipeline:
-            logger.warn("Enabling full model saving because --push_to_hub=True was specified.")
+            logger.warning("Enabling full model saving because --push_to_hub=True was specified.")
             save_full_model = True
         else:
             save_full_model = args.save_as_full_pipeline

examples/textual_inversion/textual_inversion_sdxl.py

@@ -711,7 +711,7 @@ def main():
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             unet.enable_xformers_memory_efficient_attention()
@@ -1022,7 +1022,7 @@ def main():
             )
 
         if args.push_to_hub and not args.save_as_full_pipeline:
-            logger.warn("Enabling full model saving because --push_to_hub=True was specified.")
+            logger.warning("Enabling full model saving because --push_to_hub=True was specified.")
             save_full_model = True
         else:
             save_full_model = args.save_as_full_pipeline

examples/unconditional_image_generation/train_unconditional.py

@@ -408,7 +408,7 @@ def main(args):
 
             xformers_version = version.parse(xformers.__version__)
             if xformers_version == version.parse("0.0.16"):
-                logger.warn(
+                logger.warning(
                     "xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details."
                 )
             model.enable_xformers_memory_efficient_attention()

examples/wuerstchen/text_to_image/train_text_to_image_lora_prior.py

@@ -184,7 +184,7 @@ def log_validation(text_encoder, tokenizer, prior, args, accelerator, weight_dty
                 }
             )
         else:
-            logger.warn(f"image logging not implemented for {tracker.name}")
+            logger.warning(f"image logging not implemented for {tracker.name}")
 
     del pipeline
     torch.cuda.empty_cache()