---
tags:
- MotionData
---

# MotionDiff Loader
## Documentation
- Class name: `MotionDiffLoader`
- Category: `MotionDiff`
- Output node: `False`

The MotionDiffLoader node is designed to load and initialize the Motion Diffusion Model (MDM) and its associated CLIP wrapper based on a specified model dataset. This node plays a crucial role in preparing the motion generation models for subsequent processing or inference tasks, ensuring they are correctly configured with the necessary dataset information.
## Input types
### Required
- **`model_dataset`**
    - Specifies the dataset model to be loaded. This selection determines the configuration of the Motion Diffusion Model and its CLIP wrapper, impacting the behavior and performance of motion generation.
    - Comfy dtype: `COMBO[STRING]`
    - Python dtype: `str`
## Output types
- **`md_model`**
    - Comfy dtype: `MD_MODEL`
    - Returns a wrapped instance of the Motion Diffusion Model, ready for motion generation tasks.
    - Python dtype: `MotionDiffModelWrapper`
- **`md_clip`**
    - Comfy dtype: `MD_CLIP`
    - Returns a CLIP wrapper configured for the loaded Motion Diffusion Model, facilitating text-conditioned motion generation.
    - Python dtype: `MotionDiffCLIPWrapper`
## Usage tips
- Infra type: `GPU`
- Common nodes: unknown


## Source code
```python
class MotionDiffLoader:
    @classmethod
    def INPUT_TYPES(s):
        global model_dataset_dict
        model_dataset_dict = get_model_dataset_dict()
        return {
            "required": {
                "model_dataset": (
                    list(model_dataset_dict.keys()), 
                    { "default": "-human_ml3d" }
                )
            },
        }

    RETURN_TYPES = ("MD_MODEL", "MD_CLIP")
    CATEGORY = "MotionDiff"
    FUNCTION = "load_mdm"

    def load_mdm(self, model_dataset):
        global model_dataset_dict
        if model_dataset_dict is None:
            model_dataset_dict = get_model_dataset_dict() #In case of API users
        model_config = model_dataset_dict[model_dataset]()
        mdm = create_mdm_model(model_config)
        return (MotionDiffModelWrapper(mdm, dataset=model_config.dataset), MotionDiffCLIPWrapper(mdm))

```