import datasets import json import os import pyarrow as pa _DESCRIPTION = "A comprehensive collection of permutation composition datasets for various mathematical groups including symmetric, alternating, cyclic, dihedral, and special groups." _HOMEPAGE = "https://huggingface.co/datasets/BeeGass/permutation-groups" _LICENSE = "MIT" class PermutationGroupsConfig(datasets.BuilderConfig): def __init__(self, group_name=None, max_len=512, **kwargs): # Handle the name parameter name = kwargs.get("name", "") # If name is provided, parse it to get group_name and max_len if name: if "_data" in name: # Old style: s5_data group_name = name.replace("_data", "").upper() elif "_len" in name: # Old style: s5_len32 parts = name.split("_len") group_name = parts[0].upper() if "max_len" not in kwargs: # Don't override if explicitly provided max_len = int(parts[1]) else: # New style: just s5 group_name = name.upper() if name != "all" else "All" # Ensure we have a name for the config if "name" not in kwargs: kwargs["name"] = group_name.lower() if group_name else "default" super().__init__(**kwargs) self.group_name = group_name self.max_len = max_len self.data_dir = f"data/{group_name.lower()}_data" if group_name and group_name != "All" else None class PermutationGroups(datasets.ArrowBasedBuilder): """Permutation groups dataset with dynamic length filtering.""" VERSION = datasets.Version("3.0.0") # Define all available groups GROUPS = { # Symmetric Groups "S3": {"type": "Symmetric", "degree": 3, "order": 6}, "S4": {"type": "Symmetric", "degree": 4, "order": 24}, "S5": {"type": "Symmetric", "degree": 5, "order": 120}, "S6": {"type": "Symmetric", "degree": 6, "order": 720}, "S7": {"type": "Symmetric", "degree": 7, "order": 5040}, # Alternating Groups "A3": {"type": "Alternating", "degree": 3, "order": 3}, "A4": {"type": "Alternating", "degree": 4, "order": 12}, "A5": {"type": "Alternating", "degree": 5, "order": 60}, "A6": {"type": "Alternating", "degree": 6, "order": 360}, "A7": {"type": "Alternating", "degree": 7, "order": 2520}, # Cyclic Groups "C3": {"type": "Cyclic", "degree": 3, "order": 3}, "C4": {"type": "Cyclic", "degree": 4, "order": 4}, "C5": {"type": "Cyclic", "degree": 5, "order": 5}, "C6": {"type": "Cyclic", "degree": 6, "order": 6}, "C7": {"type": "Cyclic", "degree": 7, "order": 7}, "C8": {"type": "Cyclic", "degree": 8, "order": 8}, "C10": {"type": "Cyclic", "degree": 10, "order": 10}, "C12": {"type": "Cyclic", "degree": 12, "order": 12}, # Cyclic Groups (Z notation) "Z3": {"type": "Cyclic", "degree": 3, "order": 3}, "Z4": {"type": "Cyclic", "degree": 4, "order": 4}, "Z5": {"type": "Cyclic", "degree": 5, "order": 5}, "Z6": {"type": "Cyclic", "degree": 6, "order": 6}, # Dihedral Groups "D3": {"type": "Dihedral", "degree": 3, "order": 6}, "D4": {"type": "Dihedral", "degree": 4, "order": 8}, "D5": {"type": "Dihedral", "degree": 5, "order": 10}, "D6": {"type": "Dihedral", "degree": 6, "order": 12}, "D7": {"type": "Dihedral", "degree": 7, "order": 14}, "D8": {"type": "Dihedral", "degree": 8, "order": 16}, # Special Groups "PSL25": {"type": "PSL(2,5)", "degree": 6, "order": 60}, "F20": {"type": "Frobenius", "degree": 5, "order": 20}, } BUILDER_CONFIGS = [] # Simple configs - just group names for group_name, info in GROUPS.items(): BUILDER_CONFIGS.append( PermutationGroupsConfig( name=group_name.lower(), description=f"{info['type']} Group {group_name} (order {info['order']}).", group_name=group_name, ) ) # Keep old-style configs for backwards compatibility for group_name, info in GROUPS.items(): BUILDER_CONFIGS.append( PermutationGroupsConfig( name=f"{group_name.lower()}_data", description=f"{info['type']} Group {group_name} (order {info['order']}).", group_name=group_name, ) ) # Add "all" configuration BUILDER_CONFIGS.append( PermutationGroupsConfig( name="all", description="All Permutation Composition Datasets.", group_name="All", ) ) 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, ) def _split_generators(self, dl_manager): # Handle the "all" configurations if self.config.name.startswith("all"): all_configs = [f"{g.lower()}_data" for g in self.GROUPS.keys()] # Download all base datasets train_files = [] test_files = [] for group_lower in all_configs: data_urls = { "train": f"data/{group_lower}/train/data-00000-of-00001.arrow", "test": f"data/{group_lower}/test/data-00000-of-00001.arrow", } try: downloaded = dl_manager.download(data_urls) train_files.append(downloaded["train"]) test_files.append(downloaded["test"]) except: # Skip if dataset doesn't exist pass return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "files": train_files, "max_len": self.config.max_len, }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "files": test_files, "max_len": self.config.max_len, }, ), ] else: # Single configuration - always use base data data_urls = { "train": [f"{self.config.data_dir}/train/data-00000-of-00001.arrow"], "test": [f"{self.config.data_dir}/test/data-00000-of-00001.arrow"], } downloaded_files = dl_manager.download(data_urls) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "files": downloaded_files["train"], "max_len": self.config.max_len, }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "files": downloaded_files["test"], "max_len": self.config.max_len, }, ), ] def _generate_tables(self, files, max_len): """Yield arrow tables with length filtering.""" for file_idx, file in enumerate(files): # Load the dataset dataset = datasets.Dataset.from_file(file) # Filter by sequence length if needed if max_len < 512: def filter_length(example): seq_len = len(example["input_sequence"].split()) return seq_len <= max_len dataset = dataset.filter(filter_length) # Get the underlying Arrow table table = dataset.data.table yield file_idx, table