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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 3 new columns ({'notes', 'archive_filename', 'archive_status'}) and 4 missing columns ({'status', 'description', 'path', 'kind'}).
This happened while the csv dataset builder was generating data using
hf://datasets/informedxrd/informedxrd-benchmarks/metadata/checkpoint_manifest.csv (at revision 5cf6fe7b116eb403f5dd56468a6eba52c4e2649a), [/tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/MANIFEST.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/MANIFEST.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/checkpoint_manifest.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/checkpoint_manifest.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/dataset_manifest.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/dataset_manifest.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/correct_case_015_Arsenopyrite__R050071-1__6130.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/correct_case_015_Arsenopyrite__R050071-1__6130.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/ext_group_priors.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/ext_group_priors.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/failure_case_000_Actinolite__R050336-1__5330.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/failure_case_000_Actinolite__R050336-1__5330.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/reviewer_case_metadata.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/reviewer_case_metadata.csv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
checkpoint_role: string
archive_status: string
archive_filename: string
expected_local_path: string
notes: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 897
to
{'path': Value('string'), 'kind': Value('string'), 'description': Value('string'), 'status': Value('string'), 'expected_local_path': Value('float64'), 'checkpoint_role': Value('float64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 3 new columns ({'notes', 'archive_filename', 'archive_status'}) and 4 missing columns ({'status', 'description', 'path', 'kind'}).
This happened while the csv dataset builder was generating data using
hf://datasets/informedxrd/informedxrd-benchmarks/metadata/checkpoint_manifest.csv (at revision 5cf6fe7b116eb403f5dd56468a6eba52c4e2649a), [/tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/MANIFEST.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/MANIFEST.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/checkpoint_manifest.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/checkpoint_manifest.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/dataset_manifest.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/metadata/dataset_manifest.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/correct_case_015_Arsenopyrite__R050071-1__6130.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/correct_case_015_Arsenopyrite__R050071-1__6130.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/ext_group_priors.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/ext_group_priors.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/failure_case_000_Actinolite__R050336-1__5330.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/failure_case_000_Actinolite__R050336-1__5330.csv), /tmp/hf-datasets-cache/medium/datasets/11629178688053-config-parquet-and-info-informedxrd-informedxrd-b-c3a473bf/hub/datasets--informedxrd--informedxrd-benchmarks/snapshots/5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/reviewer_case_metadata.csv (origin=hf://datasets/informedxrd/informedxrd-benchmarks@5cf6fe7b116eb403f5dd56468a6eba52c4e2649a/reviewer_subset/reviewer_case_metadata.csv)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
path string | kind string | description string | status string | expected_local_path null | checkpoint_role null |
|---|---|---|---|---|---|
src/paper_ai_diffraction/core/model.py | source | Core model definition | copied | null | null |
src/paper_ai_diffraction/core/dataset.py | source | Dataset loading including mixed dual-source support | copied | null | null |
src/paper_ai_diffraction/core/train.py | source | Training entrypoint | copied | null | null |
src/paper_ai_diffraction/core/inference.py | source | Inference helpers | copied | null | null |
src/paper_ai_diffraction/core/streaming_dataset.py | source | Streaming dataset helper retained because train.py imports it | copied | null | null |
src/paper_ai_diffraction/utils/extinction_multilabel.py | source | Extinction-group multilabel utilities | copied | null | null |
src/paper_ai_diffraction/eval/evaluate_calibration_metrics.py | source | Calibration metrics evaluation | copied | null | null |
src/paper_ai_diffraction/eval/evaluate_split_head_validity.py | source | Split-head validity evaluation | copied | null | null |
src/paper_ai_diffraction/topology/compare_325_failure_modes.py | source | Topology/failure-mode comparison | copied | null | null |
src/paper_ai_diffraction/topology/plot_extinction_topology_flow.py | source | Topology-flow figure generation | copied | null | null |
src/paper_ai_diffraction/topology/analyze_topological_error_distance.py | source | Topology distance summary analysis | copied | null | null |
src/paper_ai_diffraction/topology/plot_topological_error_distance.py | source | Topology distance plotting | copied | null | null |
src/paper_ai_diffraction/eval/plot_calibration_sweep.py | source | Calibration sweep plotting | copied | null | null |
assets/figure_data/stage2c_r325_temp_sweep.json | asset | Compact Stage-2c temperature sweep used for the calibration figure | copied | null | null |
assets/figure_data/physics_pe_curve_82ept35h.json | asset | Compact checkpoint curve used for the physics-PE supplementary figure | copied | null | null |
configs/final_mixed_2500k_dualsource.json | config | Sanitized final champion evaluation config | copied | null | null |
scripts/eval_rruff_325_473.sh | script | Paper-facing benchmark evaluation wrapper | authored | null | null |
scripts/make_topology_flow_figure.sh | script | Paper-facing topology-flow wrapper | authored | null | null |
scripts/make_topology_distance_figure.sh | script | Paper-facing topology-distance wrapper | authored | null | null |
scripts/make_calibration_figure.sh | script | Paper-facing calibration sweep wrapper | authored | null | null |
scripts/make_curriculum_real_holdout.py | script | Paper-facing Figure 2 generator from bundled benchmark values | adapted | null | null |
scripts/make_stage_decoder_tradeoffs_rruff473.py | script | Paper-facing Figure 3 generator from bundled benchmark values | adapted | null | null |
scripts/make_physics_pe_q2_ruler.py | script | Paper-facing S8 generator from bundled checkpoint-curve JSON | authored | null | null |
scripts/reconstruct_rruff_473.py | script | Public algorithm for reconstructing the frozen RRUFF-473 benchmark from upstream manifest and XY data | adapted | null | null |
scripts/build_rruff_325_from_473.py | script | Public deterministic builder for RRUFF-325 from frozen RRUFF-473 | adapted | null | null |
scripts/make_main_tables.py | script | Paper-facing table-generation script | authored | null | null |
results/ | directory | Compact JSON outputs used in paper; generated figures are intentionally excluded from git | copied | null | null |
docs/TRAINING.md | doc | Paper-facing training instructions | authored | null | null |
docs/EVALUATION.md | doc | Paper-facing evaluation instructions | authored | null | null |
docs/FIGURES.md | doc | Paper-facing figure instructions | authored | null | null |
docs/BENCHMARKS.md | doc | Benchmark-construction and non-redistribution notes for RRUFF-473 and RRUFF-325 | authored | null | null |
assets/topology/extinction_group_adjacency.json | asset | Condensed extinction-group topology graph | copied | null | null |
reproducibility/checkpoint_manifest.csv | metadata | Checkpoint linkage manifest | generated | null | null |
reproducibility/dataset_manifest.csv | metadata | Dataset and external-asset manifest | generated | null | null |
results/reviewer/ext_group_priors.json | asset | Compact aggregate extinction-group prior for calibration; rounded probabilities/log-priors and seen-class flags only; no raw ICSD structures or per-structure records | authored | null | null |
results/reviewer/ext_group_priors.csv | asset | CSV form of compact aggregate extinction-group prior for calibration | authored | null | null |
results/reviewer/rruff325_precomputed_inference.json | asset | Compact precomputed RRUFF-325 inference summary for reviewer inspection | authored | null | null |
metadata/croissant_rai.jsonld | metadata | Self-contained Croissant JSON-LD file with core file metadata and minimal Responsible AI fields for the dataset release | authored | null | null |
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End of preview.
InformedXRD Benchmarks
This Hugging Face dataset repository hosts the NeurIPS Evaluations & Datasets artifact release associated with InformedXRD.
Contents
This dataset repo contains:
- the frozen
RRUFF-473benchmark payload - the frozen
RRUFF-325benchmark payload - a small reviewer subset with compact precomputed inference outputs
- a compact aggregate extinction-group prior for calibration
- manifests and metadata needed to reproduce the benchmark definition
It does not contain:
- training code
- the broader PRX archival release
- model checkpoints
- raw ICSD structures, raw diffraction records, or large synthetic training corpora
Why these benchmarks exist
The paper's main benchmark contribution is not raw scale. It is a reproducible, auditable evaluation surface for real PXRD symmetry classification:
RRUFF-473retains hard real-data cases and supports broad robustness analysisRRUFF-325is the cleaner downstream subset used for controlled calibration and error-structure analysis
Both benchmarks are tied to explicit curation logic and frozen artifact manifests.
Intended use
These datasets are intended for:
- extinction-group evaluation on real powder diffraction patterns
- hierarchy-aware rescoring of model predictions
- benchmarking Top-k, prior-baseline, and stratified evaluation claims
The reviewer prior files contain only rounded aggregate extinction-group probabilities/log-priors and seen-class flags. They do not contain raw ICSD structures, formulas, atomic coordinates, raw diffraction records, or per-structure records. The larger trainready corpus used to derive that aggregate prior is not redistributed.
They are not intended as general-purpose training corpora.
Croissant metadata
Hugging Face auto-generates core Croissant metadata for supported dataset repos. Because this artifact is distributed primarily as HDF5 plus CSV/JSON sidecars, the release also includes a self-contained Croissant JSON-LD file with core file metadata and Responsible AI fields at metadata/croissant_rai.jsonld.
Companion assets
The associated code, manifests, and reviewer notebooks live in the separate anonymous GitHub reproducibility repo:
The associated model checkpoints live in the separate Hugging Face model repo:
Release Status
This repository is intended to be a frozen reviewer-facing artifact. Future corrections, if any, should be versioned explicitly rather than silently replacing the submitted benchmark payloads.
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