speech_dataset_utils
Utility functions for getting samples and forward loop function for different speech datasets.
Functions
Get a dataloader with the dataset name and processor of the target model. |
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Retrieves a list of speech datasets supported. |
- get_speech_dataset_dataloader(dataset_name='peoples_speech', processor=None, batch_size=1, num_samples=512, device=None)
Get a dataloader with the dataset name and processor of the target model.
- Parameters:
dataset_name (str) – Name of the dataset to load.
processor (WhisperProcessor) – 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.
device (str | None) –
- Returns:
An instance of dataloader.
- Return type:
DataLoader
- get_supported_speech_datasets()
Retrieves a list of speech 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_speech_datasets print("Supported datasets:", get_supported_speech_datasets())