Don't use bare prints in a library (#3991)

src/diffusers/pipelines/stable_diffusion/convert_from_ckpt.py

@@ -391,8 +391,8 @@ def convert_ldm_unet_checkpoint(
 
         # at least a 100 parameters have to start with `model_ema` in order for the checkpoint to be EMA
         if sum(k.startswith("model_ema") for k in keys) > 100 and extract_ema:
-            print(f"Checkpoint {path} has both EMA and non-EMA weights.")
-            print(
+            logger.warning(f"Checkpoint {path} has both EMA and non-EMA weights.")
+            logger.warning(
                 "In this conversion only the EMA weights are extracted. If you want to instead extract the non-EMA"
                 " weights (useful to continue fine-tuning), please make sure to remove the `--extract_ema` flag."
             )
@@ -402,7 +402,7 @@ def convert_ldm_unet_checkpoint(
                     unet_state_dict[key.replace(unet_key, "")] = checkpoint.pop(flat_ema_key)
         else:
             if sum(k.startswith("model_ema") for k in keys) > 100:
-                print(
+                logger.warning(
                     "In this conversion only the non-EMA weights are extracted. If you want to instead extract the EMA"
                     " weights (usually better for inference), please make sure to add the `--extract_ema` flag."
                 )
@@ -1183,7 +1183,7 @@ def download_from_original_stable_diffusion_ckpt(
     if "global_step" in checkpoint:
         global_step = checkpoint["global_step"]
     else:
-        print("global_step key not found in model")
+        logger.warning("global_step key not found in model")
         global_step = None
 
     # NOTE: this while loop isn't great but this controlnet checkpoint has one additional