Convert dataset to Parquet (part 00007-of-00008) (#8)

- Convert dataset to Parquet (part 00007-of-00008) (b164a70d68b8bb00eb6294f6a232c17b67119bc6)
- Delete loading script (3964e2a31c4b285389986c559e0de7ee1ea8f12b)

1354_pegase/test-00035-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c0d30fd9f48836eed4a18b358b3a6def7931d05e3a42ef5a4361db3cfc8ecf0f
+size 515371314

1354_pegase/test-00036-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:51d60290911f0625663883f83a8c3f165aafe3c16294c22469744b16b668455c
+size 515246510

1354_pegase/test-00037-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:015424c1d17a3e546e8b40cb5216da4357963337c11f3b70d74472a07ea202a8
+size 515191735

1354_pegase/test-00038-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:139ffb82d394a11d6a18951d42b2825876c2dffe23133fedbd9521e9c9dcb590
+size 515128893

1354_pegase/test-00039-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4eb5cedb2e36a69045bd7e6789a6d6a6372e313e8b95f2626e9c33bf6521d960
+size 515053360

1354_pegase/test-00040-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:db771072732beb382559ddeb657975feb7c8513a5c6641c32481b4a3b5f2b77c
+size 515156618

1354_pegase/test-00041-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b16862adbcfde57593df642b13ac515f9be56456cb8cc1f27ada37a9a871f3e8
+size 515248539

1354_pegase/test-00042-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8495680f5ed63f371d28bcf202c35aa5d24552ae6ff99904748e72479d8247ab
+size 515104333

1354_pegase/test-00043-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:97da3436f84fd99bcd5b88d68ead623f33626e5f52b4023c4e88c432fa617105
+size 515260787

1354_pegase/test-00044-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a0c1ccaa740ffe4b8a8d499cd5c41e8f179a800fd635dc20795a8c7fab4e3fe1
+size 515273076

1354_pegase/test-00045-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:868518e86d9e8256bda8bb4d954950666d88af13e059285b24aace49f19c41e4
+size 515160072

1354_pegase/test-00046-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:78481736b86c75bfc4601322c2d9cf3a9267cad167d1672e0307819d06357317
+size 515351205

1354_pegase/test-00047-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8dd6e59e82e16e2da37a14f42c2017a53da816e8b73b9032f1a0b60cec65a6b2
+size 515237781

1354_pegase/test-00048-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d45af06cf76919fe97bd3e8ea635fb108bb7b565bf9459d1a91294be73f92539
+size 515320473

1354_pegase/test-00049-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3b47077dcb3433789bc53faea185a31850511158e22442eb461085e74a49ba1a
+size 515212002

1354_pegase/test-00050-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fc32c918892d94f1480174c38a076ead5ea81bf2089a2c1a92cfaf754ef695ba
+size 515193159

1354_pegase/test-00051-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:379009bddd00927bcd0ae73fe4a0becff3e191f5df573ea7b089f2c8e9ba90b4
+size 515350298

1354_pegase/test-00052-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b3c602e74e786bec0cb602e184d62b4d3ad441bab9dd07593bbec8a8ebde60fe
+size 515349389

1354_pegase/test-00053-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:21ff689e188b368677fc5efd80e3eb9f7dc3ab8ff7492efc7af38e80bdf01fe2
+size 515131899

1354_pegase/test-00054-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d76ca00cfe4399beb92c08b7582f59495744b55c70520d3e523ad90c79a726cf
+size 515264800

1354_pegase/test-00055-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:929b544ebe4e16907d27cc6868ec6c3998929091d398e57e967566b0f52a51f1
+size 515140784

1354_pegase/test-00056-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8cd9f86ef822bc75ed8eb57ed5fc7e2b15dbc06117063ddef4b6178c0e50df3a
+size 515352793

1354_pegase/test-00057-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:93f35018dc3bc652e575becf90280ab8bf66fe24dcf4cfeb855f34a51c19e399
+size 515083113

1354_pegase/test-00058-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5089c3e454d206591a2817f9ce2e13b3bbb8635f192b24e7a00d1d7e36a2d115
+size 515447004

1354_pegase/test-00059-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4d50765104f3f64be0eb4785b70edb11f28a56e7fd5da21ed51db83758ff5d8d
+size 515401442

1354_pegase/test-00060-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c205bd2f213e0bd93f7fa929cc3f61e3d9795d4753f6dc350f75f4f10bb14bd
+size 515189738

1354_pegase/test-00061-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e857aceae246eded28dea71fafa9be1bf6eb0abe518de32734419bfb8369eef1
+size 515058118

1354_pegase/test-00062-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e59a0a2ff5eb617d1faaf292de1b10b15f583d735f6b7fcb704a5636b2f29474
+size 515244098

1354_pegase/test-00063-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b20c5e91a3ff0bb0333aa432a2398df1ff8e0346b503a427bfdf5ae1fbb3baa9
+size 515174836

1354_pegase/test-00064-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:833536cc75ea6c0ccd8543942db11942b7d1c7ae1c1e7662c7ef599a29b7410b
+size 515387277

1354_pegase/test-00065-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6c7625fc150df40e80b10b35d3bbe6726e418030c20c70089cb5c073de6d4849
+size 515238618

1354_pegase/test-00066-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08a7efe5985d587b4865607228f09f00f191f5c4420877b6c34fc09d6567f435
+size 515207221

1354_pegase/test-00067-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34aba13071f01e00d668fadd08ce5efc2669f2eb79725643a735a36fe4879669
+size 515272338

1354_pegase/test-00068-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:35aeb23c6c47494214ded322e95320cd6d971fe66b89e64e37bf4c2fb0804d89
+size 515265151

1354_pegase/test-00069-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:828c8b058db03182d7d2c51e904a1a470ba05e045590c838a69bafd6282d2bca
+size 515224054

1354_pegase/test-00070-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5b936196db9ab3fb1927866f50e8b87ab956ca7ee9282a77e8704e789afc93df
+size 515114321

1354_pegase/test-00071-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:192964643337a42b2c29013896deffdcfa8bedc1e48a21a4dbc4abbb8442018b
+size 514728749

1354_pegase/test-00072-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8d580a0c4df0d8a4836d101e0e3f5affbb3e6a8d50f43e6dbc306e15a95bc4aa
+size 514638138

1354_pegase/test-00073-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d8a62948cd1a588b1401cb43e09be4d70eba40abf1d2ffbefb43fcadc4486b5c
+size 514820889

1354_pegase/test-00074-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:75460bb5b82a02d7bc511c778866130cc6f891f848cfcd4d3a64202b982ed7b3
+size 514648251

1354_pegase/test-00075-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:54d844122a981fbd65bca6056055198371668f29487d8216648062b57a78f385
+size 514668478

1354_pegase/test-00076-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe3db19508221cd523c92c95f7cac9522086f5c2d76a1e348cd93867970f5325
+size 514628077

1354_pegase/test-00077-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ee6f84dd3119269e15a49909e2a95bb17835b7d1cf537bb1cbf774eea84cd2c3
+size 514515861

1354_pegase/test-00078-of-00079.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:620ca53d0652ff4953c4c699072df0c80ca894aa907cb87ac1976fec9fccab52
+size 514690265

PGLearn-Medium-1354_pegase.py

@@ -1,429 +0,0 @@
-from __future__ import annotations
-from dataclasses import dataclass
-from pathlib import Path
-import json
-import shutil
-
-import datasets as hfd
-import h5py
-import pgzip as gzip
-import pyarrow as pa
-
-# ┌──────────────┐
-# │   Metadata   │
-# └──────────────┘
-
-@dataclass
-class CaseSizes:
-    n_bus:    int
-    n_load:   int
-    n_gen:    int
-    n_branch: int
-
-CASENAME = "1354_pegase"
-SIZES = CaseSizes(n_bus=1354, n_load=673, n_gen=260, n_branch=1991)
-NUM_TRAIN = 355464
-NUM_TEST = 88867
-NUM_INFEASIBLE = 55669
-SPLITFILES = {
-    "train/SOCOPF/dual.h5.gz": ["train/SOCOPF/dual/xaa", "train/SOCOPF/dual/xab"],
-}
-
-URL = "https://huggingface.co/datasets/PGLearn/PGLearn-Medium-1354_pegase"
-DESCRIPTION = """\
-The 1354_pegase PGLearn optimal power flow dataset, part of the PGLearn-Medium collection. \
-"""
-VERSION = hfd.Version("1.0.0")
-DEFAULT_CONFIG_DESCRIPTION="""\
-This configuration contains feasible input, primal solution, and dual solution data \
-for the ACOPF, DCOPF, and SOCOPF formulations on the {case} system. For case data, \
-download the case.json.gz file from the `script` branch of the repository. \
-https://huggingface.co/datasets/PGLearn/PGLearn-Medium-1354_pegase/blob/script/case.json.gz
-"""
-USE_ML4OPF_WARNING = """
-================================================================================================
-  Loading PGLearn-Medium-1354_pegase through the `datasets.load_dataset` function may be slow.
-
-  Consider using ML4OPF to directly convert to `torch.Tensor`; for more info see:
-    https://github.com/AI4OPT/ML4OPF?tab=readme-ov-file#manually-loading-data
-
-  Or, use `huggingface_hub.snapshot_download` and an HDF5 reader; for more info see:
-    https://huggingface.co/datasets/PGLearn/PGLearn-Medium-1354_pegase#downloading-individual-files
-================================================================================================
-"""
-CITATION = """\
-@article{klamkinpglearn,
-  title={{PGLearn - An Open-Source Learning Toolkit for Optimal Power Flow}},
-  author={Klamkin, Michael and Tanneau, Mathieu and Van Hentenryck, Pascal},
-  year={2025},
-}\
-"""
-
-IS_COMPRESSED = True
-
-# ┌──────────────────┐
-# │   Formulations   │
-# └──────────────────┘
-
-def acopf_features(sizes: CaseSizes, primal: bool, dual: bool, meta: bool):
-    features = {}
-    if primal: features.update(acopf_primal_features(sizes))
-    if dual:   features.update(acopf_dual_features(sizes))
-    if meta:   features.update({f"ACOPF/{k}": v for k, v in META_FEATURES.items()})
-    return features
-
-def dcopf_features(sizes: CaseSizes, primal: bool, dual: bool, meta: bool):
-    features = {}
-    if primal: features.update(dcopf_primal_features(sizes))
-    if dual:   features.update(dcopf_dual_features(sizes))
-    if meta:   features.update({f"DCOPF/{k}": v for k, v in META_FEATURES.items()})
-    return features
-
-def socopf_features(sizes: CaseSizes, primal: bool, dual: bool, meta: bool):
-    features = {}
-    if primal: features.update(socopf_primal_features(sizes))
-    if dual:   features.update(socopf_dual_features(sizes))
-    if meta:   features.update({f"SOCOPF/{k}": v for k, v in META_FEATURES.items()})
-    return features
-
-FORMULATIONS_TO_FEATURES = {
-    "ACOPF": acopf_features,
-    "DCOPF": dcopf_features,
-    "SOCOPF": socopf_features,
-}
-
-# ┌───────────────────┐
-# │   BuilderConfig   │
-# └───────────────────┘
-
-class PGLearnMedium1354_pegaseConfig(hfd.BuilderConfig):
-    """BuilderConfig for PGLearn-Medium-1354_pegase. 
-    By default, primal solution data, metadata, input, casejson, are included for the train and test splits.
-
-    To modify the default configuration, pass attributes of this class to `datasets.load_dataset`:
-    
-    Attributes:
-        formulations (list[str]): The formulation(s) to include, e.g. ["ACOPF", "DCOPF"]
-        primal (bool, optional): Include primal solution data. Defaults to True.
-        dual (bool, optional): Include dual solution data. Defaults to False.
-        meta (bool, optional): Include metadata. Defaults to True.
-        input (bool, optional): Include input data. Defaults to True.
-        casejson (bool, optional): Include case.json data. Defaults to True.
-        train (bool, optional): Include training samples. Defaults to True.
-        test (bool, optional): Include testing samples. Defaults to True.
-        infeasible (bool, optional): Include infeasible samples. Defaults to False.
-    """
-    def __init__(self,
-            formulations: list[str],
-            primal: bool=True, dual: bool=False, meta: bool=True, input: bool = True, casejson: bool=True,
-            train: bool=True, test: bool=True, infeasible: bool=False,
-            compressed: bool=IS_COMPRESSED, **kwargs
-        ):
-        super(PGLearnMedium1354_pegaseConfig, self).__init__(version=VERSION, **kwargs)
-
-        self.case = CASENAME
-        self.formulations = formulations
-
-        self.primal = primal
-        self.dual = dual
-        self.meta = meta
-        self.input = input
-        self.casejson = casejson
-
-        self.train = train
-        self.test = test
-        self.infeasible = infeasible
-
-        self.gz_ext = ".gz" if compressed else ""
-
-    @property
-    def size(self):
-        return SIZES
-
-    @property
-    def features(self):
-        features = {}
-        if self.casejson: features.update(case_features())
-        if self.input: features.update(input_features(SIZES))
-        for formulation in self.formulations:
-            features.update(FORMULATIONS_TO_FEATURES[formulation](SIZES, self.primal, self.dual, self.meta))
-        return hfd.Features(features)
-    
-    @property
-    def splits(self):
-        splits: dict[hfd.Split, dict[str, str | int]] = {}
-        if self.train:
-            splits[hfd.Split.TRAIN] = {
-                "name": "train",
-                "num_examples": NUM_TRAIN
-            }
-        if self.test:
-            splits[hfd.Split.TEST] = {
-                "name": "test",
-                "num_examples": NUM_TEST
-            }
-        if self.infeasible:
-            splits[hfd.Split("infeasible")] = {
-                "name": "infeasible",
-                "num_examples": NUM_INFEASIBLE
-            }
-        return splits
-    
-    @property
-    def urls(self):
-        urls: dict[str, None | str | list] = {
-            "case": None, "train": [], "test": [], "infeasible": [],
-        }
-
-        if self.casejson:
-            urls["case"] = f"case.json" + self.gz_ext
-        else:
-            urls.pop("case")
-
-        split_names = []
-        if self.train: split_names.append("train")
-        if self.test:  split_names.append("test")
-        if self.infeasible: split_names.append("infeasible")
-
-        for split in split_names:
-            if self.input: urls[split].append(f"{split}/input.h5" + self.gz_ext)
-            for formulation in self.formulations:
-                if self.primal:
-                    filename = f"{split}/{formulation}/primal.h5" + self.gz_ext
-                    if filename in SPLITFILES: urls[split].append(SPLITFILES[filename])
-                    else: urls[split].append(filename)
-                if self.dual:
-                    filename = f"{split}/{formulation}/dual.h5" + self.gz_ext
-                    if filename in SPLITFILES: urls[split].append(SPLITFILES[filename])
-                    else: urls[split].append(filename)
-                if self.meta:
-                    filename = f"{split}/{formulation}/meta.h5" + self.gz_ext
-                    if filename in SPLITFILES: urls[split].append(SPLITFILES[filename])
-                    else: urls[split].append(filename)
-        return urls
-
-# ┌────────────────────┐
-# │   DatasetBuilder   │
-# └────────────────────┘
-
-class PGLearnMedium1354_pegase(hfd.ArrowBasedBuilder):
-    """DatasetBuilder for PGLearn-Medium-1354_pegase.
-    The main interface is `datasets.load_dataset` with `trust_remote_code=True`, e.g.
-
-    ```python
-    from datasets import load_dataset
-    ds = load_dataset("PGLearn/PGLearn-Medium-1354_pegase", trust_remote_code=True,
-        # modify the default configuration by passing kwargs
-        formulations=["DCOPF"],
-        dual=False,
-        meta=False,
-    )
-    ```
-    """
-
-    DEFAULT_WRITER_BATCH_SIZE = 10000
-    BUILDER_CONFIG_CLASS = PGLearnMedium1354_pegaseConfig
-    DEFAULT_CONFIG_NAME=CASENAME
-    BUILDER_CONFIGS = [
-        PGLearnMedium1354_pegaseConfig(
-            name=CASENAME, description=DEFAULT_CONFIG_DESCRIPTION.format(case=CASENAME),
-            formulations=list(FORMULATIONS_TO_FEATURES.keys()),
-            primal=True, dual=True, meta=True, input=True, casejson=False,
-            train=True, test=True, infeasible=False,
-        )
-    ]
-
-    def _info(self):
-        return hfd.DatasetInfo(
-            features=self.config.features, splits=self.config.splits,
-            description=DESCRIPTION + self.config.description,
-            homepage=URL, citation=CITATION,
-        )
-
-    def _split_generators(self, dl_manager: hfd.DownloadManager):
-        hfd.logging.get_logger().warning(USE_ML4OPF_WARNING)
-
-        filepaths = dl_manager.download_and_extract(self.config.urls)
-
-        splits: list[hfd.SplitGenerator] = []
-        if self.config.train:
-            splits.append(hfd.SplitGenerator(
-                name=hfd.Split.TRAIN,
-                gen_kwargs=dict(case_file=filepaths.get("case", None), data_files=tuple(filepaths["train"]), n_samples=NUM_TRAIN),
-            ))
-        if self.config.test:
-            splits.append(hfd.SplitGenerator(
-                name=hfd.Split.TEST,
-                gen_kwargs=dict(case_file=filepaths.get("case", None), data_files=tuple(filepaths["test"]), n_samples=NUM_TEST),
-            ))
-        if self.config.infeasible:
-            splits.append(hfd.SplitGenerator(
-                name=hfd.Split("infeasible"),
-                gen_kwargs=dict(case_file=filepaths.get("case", None), data_files=tuple(filepaths["infeasible"]), n_samples=NUM_INFEASIBLE),
-            ))
-        return splits
-
-    def _generate_tables(self, case_file: str | None, data_files: tuple[hfd.utils.track.tracked_str | list[hfd.utils.track.tracked_str]], n_samples: int):
-        case_data: str | None = json.dumps(json.load(open_maybe_gzip_cat(case_file))) if case_file is not None else None
-        data: dict[str, h5py.File] = {}
-        for file in data_files:
-            v = h5py.File(open_maybe_gzip_cat(file), "r")
-            if isinstance(file, list):
-                k = "/".join(Path(file[0].get_origin()).parts[-3:-1]).split(".")[0]
-            else:
-                k = "/".join(Path(file.get_origin()).parts[-2:]).split(".")[0]
-            data[k] = v
-        for k in list(data.keys()):
-            if "/input" in k: data[k.split("/", 1)[1]] = data.pop(k)
-
-        batch_size = self._writer_batch_size or self.DEFAULT_WRITER_BATCH_SIZE
-        for i in range(0, n_samples, batch_size):
-            effective_batch_size = min(batch_size, n_samples - i)
-
-            sample_data = {
-                f"{dk}/{k}":
-                hfd.features.features.numpy_to_pyarrow_listarray(v[i:i + effective_batch_size, ...])
-                for dk, d in data.items() for k, v in d.items() if f"{dk}/{k}" in self.config.features
-            }
-
-            if case_data is not None:
-                sample_data["case/json"] = pa.array([case_data] * effective_batch_size)
-
-            yield i, pa.Table.from_pydict(sample_data)
-
-        for f in data.values():
-            f.close()
-
-# ┌──────────────┐
-# │   Features   │
-# └──────────────┘
-
-FLOAT_TYPE = "float32"
-INT_TYPE = "int64"
-BOOL_TYPE = "bool"
-STRING_TYPE = "string"
-
-def case_features():
-    # FIXME: better way to share schema of case data -- need to treat jagged arrays
-    return {
-        "case/json": hfd.Value(STRING_TYPE),
-    }
-
-META_FEATURES = {
-    "meta/seed":                   hfd.Value(dtype=INT_TYPE),
-    "meta/formulation":            hfd.Value(dtype=STRING_TYPE),
-    "meta/primal_objective_value": hfd.Value(dtype=FLOAT_TYPE),
-    "meta/dual_objective_value":   hfd.Value(dtype=FLOAT_TYPE),
-    "meta/primal_status":          hfd.Value(dtype=STRING_TYPE),
-    "meta/dual_status":            hfd.Value(dtype=STRING_TYPE),
-    "meta/termination_status":     hfd.Value(dtype=STRING_TYPE),
-    "meta/build_time":             hfd.Value(dtype=FLOAT_TYPE),
-    "meta/extract_time":           hfd.Value(dtype=FLOAT_TYPE),
-    "meta/solve_time":             hfd.Value(dtype=FLOAT_TYPE),
-}
-
-def input_features(sizes: CaseSizes):
-    return {
-        "input/pd":            hfd.Sequence(length=sizes.n_load,   feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "input/qd":            hfd.Sequence(length=sizes.n_load,   feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "input/gen_status":    hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=BOOL_TYPE)),
-        "input/branch_status": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=BOOL_TYPE)),
-        "input/seed":          hfd.Value(dtype=INT_TYPE),
-    }
-
-def acopf_primal_features(sizes: CaseSizes):
-    return {
-        "ACOPF/primal/vm": hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/primal/va": hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/primal/pg": hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/primal/qg": hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/primal/pf": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/primal/pt": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/primal/qf": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/primal/qt": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-    }
-def acopf_dual_features(sizes: CaseSizes):
-    return {
-        "ACOPF/dual/kcl_p":     hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/kcl_q":     hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/vm":        hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/pg":        hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/qg":        hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/ohm_pf":    hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/ohm_pt":    hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/ohm_qf":    hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/ohm_qt":    hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/pf":        hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/pt":        hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/qf":        hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/qt":        hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/va_diff":   hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/sm_fr":     hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/sm_to":     hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "ACOPF/dual/slack_bus": hfd.Value(dtype=FLOAT_TYPE),
-    }
-def dcopf_primal_features(sizes: CaseSizes):
-    return {
-        "DCOPF/primal/va": hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "DCOPF/primal/pg": hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "DCOPF/primal/pf": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-    }
-def dcopf_dual_features(sizes: CaseSizes):
-    return {
-        "DCOPF/dual/kcl_p":     hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "DCOPF/dual/pg":        hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "DCOPF/dual/ohm_pf":    hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "DCOPF/dual/pf":        hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "DCOPF/dual/va_diff":   hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "DCOPF/dual/slack_bus": hfd.Value(dtype=FLOAT_TYPE),
-    }
-def socopf_primal_features(sizes: CaseSizes):
-    return {
-        "SOCOPF/primal/w":  hfd.Sequence(length=sizes.n_bus,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/pg": hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/qg": hfd.Sequence(length=sizes.n_gen,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/pf": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/pt": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/qf": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/qt": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/wr": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/primal/wi": hfd.Sequence(length=sizes.n_branch, feature=hfd.Value(dtype=FLOAT_TYPE)),
-    }
-def socopf_dual_features(sizes: CaseSizes):
-    return {
-        "SOCOPF/dual/kcl_p":   hfd.Sequence(length=sizes.n_bus,       feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/kcl_q":   hfd.Sequence(length=sizes.n_bus,       feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/w":       hfd.Sequence(length=sizes.n_bus,       feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/pg":      hfd.Sequence(length=sizes.n_gen,       feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/qg":      hfd.Sequence(length=sizes.n_gen,       feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/ohm_pf":  hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/ohm_pt":  hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/ohm_qf":  hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/ohm_qt":  hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/jabr":    hfd.Array2D(shape=(sizes.n_branch, 4), dtype=FLOAT_TYPE),
-        "SOCOPF/dual/sm_fr":   hfd.Array2D(shape=(sizes.n_branch, 3), dtype=FLOAT_TYPE),
-        "SOCOPF/dual/sm_to":   hfd.Array2D(shape=(sizes.n_branch, 3), dtype=FLOAT_TYPE),
-        "SOCOPF/dual/va_diff": hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/wr":      hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/wi":      hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/pf":      hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/pt":      hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/qf":      hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-        "SOCOPF/dual/qt":      hfd.Sequence(length=sizes.n_branch,    feature=hfd.Value(dtype=FLOAT_TYPE)),
-    }
-
-# ┌───────────────┐
-# │   Utilities   │
-# └───────────────┘
-
-def open_maybe_gzip_cat(path: str | list):
-    if isinstance(path, list):
-        dest = Path(path[0]).parent.with_suffix(".h5")
-        if not dest.exists():
-            with open(dest, "wb") as dest_f:
-                for piece in path:
-                    with open(piece, "rb") as piece_f:
-                        shutil.copyfileobj(piece_f, dest_f)
-            shutil.rmtree(Path(piece).parent)
-        path = dest.as_posix()
-    return gzip.open(path, "rb") if path.endswith(".gz") else open(path, "rb")

README.md

@@ -0,0 +1,292 @@
+---
+dataset_info:
+  config_name: 1354_pegase
+  features:
+  - name: input/pd
+    sequence: float32
+    length: 673
+  - name: input/qd
+    sequence: float32
+    length: 673
+  - name: input/gen_status
+    sequence: bool
+    length: 260
+  - name: input/branch_status
+    sequence: bool
+    length: 1991
+  - name: input/seed
+    dtype: int64
+  - name: ACOPF/primal/vm
+    sequence: float32
+    length: 1354
+  - name: ACOPF/primal/va
+    sequence: float32
+    length: 1354
+  - name: ACOPF/primal/pg
+    sequence: float32
+    length: 260
+  - name: ACOPF/primal/qg
+    sequence: float32
+    length: 260
+  - name: ACOPF/primal/pf
+    sequence: float32
+    length: 1991
+  - name: ACOPF/primal/pt
+    sequence: float32
+    length: 1991
+  - name: ACOPF/primal/qf
+    sequence: float32
+    length: 1991
+  - name: ACOPF/primal/qt
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/kcl_p
+    sequence: float32
+    length: 1354
+  - name: ACOPF/dual/kcl_q
+    sequence: float32
+    length: 1354
+  - name: ACOPF/dual/vm
+    sequence: float32
+    length: 1354
+  - name: ACOPF/dual/pg
+    sequence: float32
+    length: 260
+  - name: ACOPF/dual/qg
+    sequence: float32
+    length: 260
+  - name: ACOPF/dual/ohm_pf
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/ohm_pt
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/ohm_qf
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/ohm_qt
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/pf
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/pt
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/qf
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/qt
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/va_diff
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/sm_fr
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/sm_to
+    sequence: float32
+    length: 1991
+  - name: ACOPF/dual/slack_bus
+    dtype: float32
+  - name: ACOPF/meta/seed
+    dtype: int64
+  - name: ACOPF/meta/formulation
+    dtype: string
+  - name: ACOPF/meta/primal_objective_value
+    dtype: float32
+  - name: ACOPF/meta/dual_objective_value
+    dtype: float32
+  - name: ACOPF/meta/primal_status
+    dtype: string
+  - name: ACOPF/meta/dual_status
+    dtype: string
+  - name: ACOPF/meta/termination_status
+    dtype: string
+  - name: ACOPF/meta/build_time
+    dtype: float32
+  - name: ACOPF/meta/extract_time
+    dtype: float32
+  - name: ACOPF/meta/solve_time
+    dtype: float32
+  - name: DCOPF/primal/va
+    sequence: float32
+    length: 1354
+  - name: DCOPF/primal/pg
+    sequence: float32
+    length: 260
+  - name: DCOPF/primal/pf
+    sequence: float32
+    length: 1991
+  - name: DCOPF/dual/kcl_p
+    sequence: float32
+    length: 1354
+  - name: DCOPF/dual/pg
+    sequence: float32
+    length: 260
+  - name: DCOPF/dual/ohm_pf
+    sequence: float32
+    length: 1991
+  - name: DCOPF/dual/pf
+    sequence: float32
+    length: 1991
+  - name: DCOPF/dual/va_diff
+    sequence: float32
+    length: 1991
+  - name: DCOPF/dual/slack_bus
+    dtype: float32
+  - name: DCOPF/meta/seed
+    dtype: int64
+  - name: DCOPF/meta/formulation
+    dtype: string
+  - name: DCOPF/meta/primal_objective_value
+    dtype: float32
+  - name: DCOPF/meta/dual_objective_value
+    dtype: float32
+  - name: DCOPF/meta/primal_status
+    dtype: string
+  - name: DCOPF/meta/dual_status
+    dtype: string
+  - name: DCOPF/meta/termination_status
+    dtype: string
+  - name: DCOPF/meta/build_time
+    dtype: float32
+  - name: DCOPF/meta/extract_time
+    dtype: float32
+  - name: DCOPF/meta/solve_time
+    dtype: float32
+  - name: SOCOPF/primal/w
+    sequence: float32
+    length: 1354
+  - name: SOCOPF/primal/pg
+    sequence: float32
+    length: 260
+  - name: SOCOPF/primal/qg
+    sequence: float32
+    length: 260
+  - name: SOCOPF/primal/pf
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/primal/pt
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/primal/qf
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/primal/qt
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/primal/wr
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/primal/wi
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/kcl_p
+    sequence: float32
+    length: 1354
+  - name: SOCOPF/dual/kcl_q
+    sequence: float32
+    length: 1354
+  - name: SOCOPF/dual/w
+    sequence: float32
+    length: 1354
+  - name: SOCOPF/dual/pg
+    sequence: float32
+    length: 260
+  - name: SOCOPF/dual/qg
+    sequence: float32
+    length: 260
+  - name: SOCOPF/dual/ohm_pf
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/ohm_pt
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/ohm_qf
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/ohm_qt
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/jabr
+    dtype:
+      array2_d:
+        shape:
+        - 1991
+        - 4
+        dtype: float32
+  - name: SOCOPF/dual/sm_fr
+    dtype:
+      array2_d:
+        shape:
+        - 1991
+        - 3
+        dtype: float32
+  - name: SOCOPF/dual/sm_to
+    dtype:
+      array2_d:
+        shape:
+        - 1991
+        - 3
+        dtype: float32
+  - name: SOCOPF/dual/va_diff
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/wr
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/wi
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/pf
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/pt
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/qf
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/dual/qt
+    sequence: float32
+    length: 1991
+  - name: SOCOPF/meta/seed
+    dtype: int64
+  - name: SOCOPF/meta/formulation
+    dtype: string
+  - name: SOCOPF/meta/primal_objective_value
+    dtype: float32
+  - name: SOCOPF/meta/dual_objective_value
+    dtype: float32
+  - name: SOCOPF/meta/primal_status
+    dtype: string
+  - name: SOCOPF/meta/dual_status
+    dtype: string
+  - name: SOCOPF/meta/termination_status
+    dtype: string
+  - name: SOCOPF/meta/build_time
+    dtype: float32
+  - name: SOCOPF/meta/extract_time
+    dtype: float32
+  - name: SOCOPF/meta/solve_time
+    dtype: float32
+  splits:
+  - name: train
+    num_bytes: 157235012667
+    num_examples: 355464
+  - name: test
+    num_bytes: 39309195505
+    num_examples: 88867
+  download_size: 203615755876
+  dataset_size: 196544208172
+configs:
+- config_name: 1354_pegase
+  data_files:
+  - split: train
+    path: 1354_pegase/train-*
+  - split: test
+    path: 1354_pegase/test-*
+  default: true
+---