vlm_dataset_utils
Utility functions for getting samples and forward loop function for different vlm datasets.
Functions
Retrieves a list of vlm datasets supported. |
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Get a dataloader with the dataset name and processor of the target model. |
- get_supported_vlm_datasets()
Retrieves a list of vlm datasets supported.
- Returns:
A list of strings, where each string is the name of a supported dataset.
- Return type:
list[str]
Example usage:
from modelopt.torch.utils import get_supported_vlm_datasets print("Supported datasets:", get_supported_vlm_datasets())
- get_vlm_dataset_dataloader(dataset_name='scienceqa', processor=None, batch_size=1, num_samples=512)
Get a dataloader with the dataset name and processor of the target model.
- Parameters:
dataset_name (str) – Name of the dataset to load.
processor (MllamaImageProcessor) – Processor used for encoding images and text data.
batch_size (int) – Batch size of the returned dataloader.
num_samples (int) – Number of samples from the dataset.
- Returns:
An instance of dataloader.
- Return type:
DataLoader