> ## Documentation Index
> Fetch the complete documentation index at: https://dripart-feat-openapi-i18n.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LoadTrainingDataset - ComfyUI Built-in Node Documentation

> Complete documentation for the LoadTrainingDataset node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node loads an encoded training dataset that has been previously saved to disk. It searches for and reads all data shard files from a specified folder within the ComfyUI output directory, then returns the combined latent vectors and conditioning data for use in training workflows.

## Inputs

| Parameter     | Description                                                                                                                  | Data Type | Required | Range |
| ------------- | ---------------------------------------------------------------------------------------------------------------------------- | --------- | -------- | ----- |
| `folder_name` | Name of the folder containing the saved dataset, located inside the ComfyUI output directory (default: "training\_dataset"). | STRING    | Yes      | N/A   |

## Outputs

| Output Name    | Description                                                                                                | Data Type    |
| -------------- | ---------------------------------------------------------------------------------------------------------- | ------------ |
| `latents`      | A list of latent dictionaries, where each dictionary contains a `"samples"` key with a tensor.             | LATENT       |
| `conditioning` | A list of conditioning lists, where each inner list contains conditioning data for a corresponding sample. | CONDITIONING |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/LoadTrainingDataset/en.md)

***

**Source fingerprint (SHA-256):** `1d074685317b5bd53d9fb7596126b0f579de6c67b5615717b1a16ba01fc01efd`