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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
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/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1393, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1571, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
lp.gz unknown | __key__ string | __url__ string |
|---|---|---|
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48... | instances/instance_200 | hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/raw.tar |
"bWF4aW1pemUKT0JKOiArMTA0LjkzMDE4OTM5OTQ3MzcgeDEgKzE2OS42NDgxMjkyNjcyNjM0NCB4MiArMTQwLjIzMzM5NzA4OTc(...TRUNCATED) | instances/instance_201 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArNDQuNTc4NzA0NjU5ODAyNjA0IHgxICs1NDMuNzc0NjUyMDUzNTI4NSB4MiArNjc5LjM5MTI5MTY0ODk(...TRUNCATED) | instances/instance_202 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArMjc5LjU3NzY1NTE4MzM5NTkgeDEgKzQwOS45MzI2MzI3MTM4MDQ0IHgyICsyOTUuNjY4MzcwNzk4Mjc(...TRUNCATED) | instances/instance_203 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArMTE3LjAwOTIyMTM1MTQxNzMgeDEgKzE3MS4wNDY5OTc3NjU5OTAwMyB4MiArMjE1LjE0NzU5ODk3OTM(...TRUNCATED) | instances/instance_204 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArMTg3LjM3MzUzOTYyMzg4MDU2IHgxICsyMzUuOTg2MzAzNzgyMzUzOSB4MiArNDMuMjgxMzk5NTg5Mjk(...TRUNCATED) | instances/instance_205 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArMTA5LjQxMjQzNzQwMjM1MDE1IHgxICsyNjQuNDI4OTM5MDM3ODE3NSB4MiArMjU0LjM0NTc5Njc2OTY(...TRUNCATED) | instances/instance_206 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArMjQ1LjcxODM0MTc5MjI3NTg1IHgxICszMzguOTYxNTQzMDk3MjA1MiB4MiArMzI5LjM2NzE3MzMwOTg(...TRUNCATED) | instances/instance_207 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArMTkzLjE2MDE4NTYxNTU4NTEgeDEgKzI0OS45NTcwODg3MDAxMDMzNiB4MiArMTk1Ljc3NTc5NDAwOTI(...TRUNCATED) | instances/instance_208 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
"bWF4aW1pemUKT0JKOiArNTQxLjY4MTkyMjA0OTI4MDYgeDEgKzU3Mi4zMzQxMjUyNTk0NDUzIHgyICs1MzIuNzY4MTE1NTA1ODM(...TRUNCATED) | instances/instance_209 | "hf://datasets/orailix/remilp-data@75aa27e447285c4d6eecddcb16eddc6ed905a479/dmiplib/CA/easy/train/ra(...TRUNCATED) |
End of preview.
ReMILP dataset
MILP instances as bipartite variable-constraint graphs, with the labels of the downstream tasks of the ReMILP paper.
| directory | instances | splits | labels |
|---|---|---|---|
milp_evolve/ |
42,193 | pretrain/{train,val}, gap/{train,val,test} |
integrality gap |
dmiplib/<CLASS>/<difficulty>/ |
300 per pair (23 pairs) | train, val, test = 200 / 50 / 50 |
solution pool |
Pairs, from Distributional MIPLIB: CA and IS easy/medium; SC, VC and GISP easy/medium/hard; MMCN medium-BI, hard-BI and medium-BC; CFLP easy/medium; OTS easy/medium/hard; NNV easy; LB hard.
Layout
<source>/manifest.json {"source", "processing", "entries": [{"id", "split", "num_nodes", "num_edges"}, ...]}
<source>/<split>/graphs/<id>.pt.zst a torch_geometric HeteroData, zstd-compressed
<source>/<split>/raw.tar instances/<id>.(mps|lp).gz and labels/<id>.json.gz
Labels
milp_evolve:lp_ip_gap = min(1, |IP - LP| / (max(|IP|, |LP|) + 1e-5)).dmiplib: a pool of up to 300 solutions per instance (Gurobi, one hour per instance).solution_probsandactive_probsare softmax-over-objective weighted averages over the pool of each binary variable's value and of each constraint's tightness.
Use
hf download orailix/remilp-data --repo-type dataset --local-dir data --exclude "*/raw.tar"
Attribution
D-MIPLIB instances are redistributed under their own licenses. Refer to D-MIPLIB. milp_evolve comes from
MILP-Evolve.
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