Repository: huggingface/diffusers

Issue:
AttributeError: 'Logger' object has no attribute 'warninging'. Did you mean: 'warning'?
### Describe the bug

AttributeError: 'Logger' object has no attribute 'warninging'. Did you mean: 'warning'?

There is a spelling error in the logger object.

### Reproduction

loading a model using .from_single_file() 

### Logs

```shell
Traceback (most recent call last):
  File "/workspace/hbot-backend-anime/src/main.py", line 7, in <module>
    from core import generate_anime_image
  File "/workspace/hbot-backend-anime/src/core.py", line 18, in <module>
    pipe = StableDiffusionPipeline.from_single_file("./anime/anyhentai.safetensors", torch_dtype=torch.float16, safety_checker=None,text_encoder=text_encoder)
  File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
    return fn(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/diffusers/loaders/single_file.py", line 491, in from_single_file
    loaded_sub_model = load_single_file_sub_model(
  File "/usr/local/lib/python3.10/dist-packages/diffusers/loaders/single_file.py", line 100, in load_single_file_sub_model
    loaded_sub_model = load_method(
  File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
    return fn(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/diffusers/loaders/single_file_model.py", line 260, in from_single_file
    diffusers_format_checkpoint = checkpoint_mapping_fn(
  File "/usr/local/lib/python3.10/dist-packages/diffusers/loaders/single_file_utils.py", line 840, in convert_ldm_unet_checkpoint
    logger.warninging(
AttributeError: 'Logger' object has no attribute 'warninging'. Did you mean: 'warning'?
```


### System Info

- 🤗 Diffusers version: 0.28.0.dev0
- Platform: Ubuntu 22.04.2 LTS - Linux-5.4.0-121-generic-x86_64-with-glibc2.35
- Running on a notebook?: No
- Running on Google Colab?: No
- Python version: 3.10.12
- PyTorch version (GPU?): 2.0.1+cu118 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Huggingface_hub version: 0.23.1
- Transformers version: 4.41.0
- Accelerate version: 0.30.1
- PEFT version: 0.11.1
- Bitsandbytes version: not installed
- Safetensors version: 0.4.3
- xFormers version: 0.0.20
- Accelerator: NVIDIA A30, 24576 MiB VRAM
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help?

_No response_


Discussion:

Resolving patch:
diff --git a/src/diffusers/loaders/single_file_utils.py b/src/diffusers/loaders/single_file_utils.py
--- a/src/diffusers/loaders/single_file_utils.py
+++ b/src/diffusers/loaders/single_file_utils.py
@@ -826,8 +826,8 @@ def convert_ldm_unet_checkpoint(checkpoint, config, extract_ema=False, **kwargs)
 
     # 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:
-        logger.warninging("Checkpoint has both EMA and non-EMA weights.")
-        logger.warninging(
+        logger.warning("Checkpoint 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."
         )
@@ -837,7 +837,7 @@ def convert_ldm_unet_checkpoint(checkpoint, config, extract_ema=False, **kwargs)
                 unet_state_dict[key.replace(unet_key, "")] = checkpoint.get(flat_ema_key)
     else:
         if sum(k.startswith("model_ema") for k in keys) > 100:
-            logger.warninging(
+            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."
             )


Test patch: