Upload permutation-groups.py with huggingface_hub

permutation-groups.py

@@ -0,0 +1,130 @@
+import datasets
+import json
+from sympy.combinatorics import Permutation
+from sympy.combinatorics.named_groups import AlternatingGroup, SymmetricGroup
+
+_DESCRIPTION = "A collection of permutation composition datasets for various symmetric and alternating groups."
+_HOMEPAGE = "https://huggingface.co/datasets/BeeGass/permutation-groups"
+_LICENSE = "MIT"
+
+class PermutationGroupsConfig(datasets.BuilderConfig):
+    def __init__(self, *args, group_name=None, group_degree=None, group_order=None, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.group_name = group_name
+        self.group_degree = group_degree
+        self.group_order = group_order
+
+class PermutationGroups(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        PermutationGroupsConfig(
+            name="s3_data",
+            description="Permutation Composition Dataset for the Symmetric Group S3.",
+            group_name="S3",
+            group_degree=3,
+            group_order=6,
+        ),
+        PermutationGroupsConfig(
+            name="s4_data",
+            description="Permutation Composition Dataset for the Symmetric Group S4.",
+            group_name="S4",
+            group_degree=4,
+            group_order=24,
+        ),
+        PermutationGroupsConfig(
+            name="s5_data",
+            description="Permutation Composition Dataset for the Symmetric Group S5.",
+            group_name="S5",
+            group_degree=5,
+            group_order=120,
+        ),
+        PermutationGroupsConfig(
+            name="s6_data",
+            description="Permutation Composition Dataset for the Symmetric Group S6.",
+            group_name="S6",
+            group_degree=6,
+            group_order=720,
+        ),
+        PermutationGroupsConfig(
+            name="s7_data",
+            description="Permutation Composition Dataset for the Symmetric Group S7.",
+            group_name="S7",
+            group_degree=7,
+            group_order=5040,
+        ),
+        PermutationGroupsConfig(
+            name="a5_data",
+            description="Permutation Composition Dataset for the Alternating Group A5.",
+            group_name="A5",
+            group_degree=5,
+            group_order=60,
+        ),
+        PermutationGroupsConfig(
+            name="a6_data",
+            description="Permutation Composition Dataset for the Alternating Group A6.",
+            group_name="A6",
+            group_degree=6,
+            group_order=360,
+        ),
+        PermutationGroupsConfig(
+            name="a7_data",
+            description="Permutation Composition Dataset for the Alternating Group A7.",
+            group_name="A7",
+            group_degree=7,
+            group_order=2520,
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "s5_data"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                "input_sequence": datasets.Value("string"),
+                "target": datasets.Value("string"),
+            }),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            # Add custom metadata to info.metadata
+            metadata=datasets.MetadataDict({
+                "group_name": self.config.group_name,
+                "group_degree": self.config.group_degree,
+                "group_order": self.config.group_order,
+            }),
+        )
+
+    def _split_generators(self, dl_manager):
+        # The data files are already uploaded to the repo in data/<config_name>/
+        # We need to provide the paths relative to the dataset script
+        data_dir = f"data/{self.config.name}"
+        
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "train", "data-*.arrow"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "test", "data-*.arrow"),
+                    "split": "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        # Load the Arrow files directly
+        for i, file in enumerate(dl_manager.iter_files(filepath)):
+            # Assuming each .arrow file contains a table that can be converted to a list of dicts
+            # For simplicity, we'll load it as a Dataset and iterate
+            dataset = datasets.Dataset.from_file(file)
+            for id_, row in enumerate(dataset):
+                yield f"{split}_{i}_{id_}", {
+                    "input_sequence": row["input_sequence"],
+                    "target": row["target"],
+                }