Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError Message: The split names could not be parsed from the dataset config. Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 298, in get_dataset_config_info for split_generator in builder._split_generators( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 80, in _split_generators raise ValueError( ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response for split in get_dataset_split_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 352, in get_dataset_split_names info = get_dataset_config_info( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 303, in get_dataset_config_info raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
This page hosts the PGLearn dataset 14_ieee_011025
, containing 1,000,000 samples of ACOPF, DCOPF, and SOCOPF primal and dual solutions for varying loads on the 14_ieee
benchmark from pglib-opf.
The dataset was generated using the OPFGenerator repository; please refer to the documentation therein for more details.
Load vectors are sampled by applying one global Uniform(0.8, 1.2)
factor per sample, then a local Uniform(0.8, 1.2)
factor per load. This corresponds to ScaledUniform(l=0.8, u=1.2, sigma=0.2)
in OPFGenerator. Network data is pre-processed using PowerModels.make_basic_network.
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