| # Data processing | |
| ## pre-processing | |
| Instructions are here: | |
| https://github.com/NVIDIA/Megatron-LM/#data-preprocessing | |
| ## Merging multiple pre-processed indexed datasets | |
| TODO: Need to write a script that merges existing indices - this is needed for situation when we either: | |
| 1. don't have enough SLURM hours to complete pre-processing when the input is huge | |
| 2. already have sub-datasets preprocessed and we want to re-use those, rather than pre-processing everything from scratch | |
| Direction using `merge_file_` | |
| https://github.com/NVIDIA/Megatron-LM/blob/90e0a0dd08159e1c95f4f9d99bb8687f327d36c3/megatron/data/indexed_dataset.py#L294 | |
| It looks like you have to create a new builder, and merge all already processed documents to it. | |
| The other option is to split your dataset up into multiple smaller datasets and use `BlendedDataset` that is mentioned below. | |
| ## Sampling from multiple datasets | |
| Note also that Megatron has a BlendedDataset that can take multiple datasets and sample from them. This is mostly useful so that you can weigh different datasets differently. If part of your dataset is small and high quality, you might want to go through that 3-4 times but only go through a big lower quality dataset once, for example. | |