Add read_custom_data to DocumentDataset #574
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Signed-off-by: Praateek <[email protected]>
sarahyurick
reviewed
Feb 26, 2025
| @@ -155,6 +155,73 @@ def read_pickle( | |||
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| @classmethod | |||
| def read_custom_data( | |||
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Suggested change
| def read_custom_data( | |
| def read_custom( |
to more closely match read_json, read_parquet, read_pickle?
| expected_df[["embedding", "id"]], # because we sort columns by name, | ||
| ) | ||
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| # Test multiple files per partition |
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Description
We need an ability to read arbitrary datasets using a user defined function.
The UDF should accept
- files: A list of file paths.
- file_type: The type of the file to read (in case you want to handle different file types differently).
- backend: pd / cudf
- add_filename: True / False / str in which case they can use
from nemo_curator.utils.distributed_utils import _resolve_filename_col- columns: Can use this to define set of cols to return (output is always sorted columns)
- input_meta: Can use this for typecasting if eneded
Usage
# Add snippet demonstrating usageChecklist