Upload permutation-groups.py with huggingface_hub

permutation-groups.py

@@ -1,6 +1,7 @@
 import datasets
 import json
 import os
+import pyarrow as pa
 
 _DESCRIPTION = "A collection of permutation composition datasets for various symmetric and alternating groups."
 _HOMEPAGE = "https://huggingface.co/datasets/BeeGass/permutation-groups"
@@ -14,7 +15,9 @@ class PermutationGroupsConfig(datasets.BuilderConfig):
         self.group_order = group_order
         self.data_dir = data_dir
 
-class PermutationGroups(datasets.GeneratorBasedBuilder):
+class PermutationGroups(datasets.ArrowBasedBuilder):
+    """Use ArrowBasedBuilder for better performance with Arrow files."""
+    
     VERSION = datasets.Version("1.0.0")
 
     BUILDER_CONFIGS = [
@@ -58,6 +61,22 @@ class PermutationGroups(datasets.GeneratorBasedBuilder):
             group_order=5040,
             data_dir="data/s7_data",
         ),
+        PermutationGroupsConfig(
+            name="a3_data",
+            description="Permutation Composition Dataset for the Alternating Group A3.",
+            group_name="A3",
+            group_degree=3,
+            group_order=3,
+            data_dir="data/a3_data",
+        ),
+        PermutationGroupsConfig(
+            name="a4_data",
+            description="Permutation Composition Dataset for the Alternating Group A4.",
+            group_name="A4",
+            group_degree=4,
+            group_order=12,
+            data_dir="data/a4_data",
+        ),
         PermutationGroupsConfig(
             name="a5_data",
             description="Permutation Composition Dataset for the Alternating Group A5.",
@@ -84,7 +103,7 @@ class PermutationGroups(datasets.GeneratorBasedBuilder):
         ),
         PermutationGroupsConfig(
             name="all",
-            description="All Permutation Composition Datasets (S3-S7 and A5-A7).",
+            description="All Permutation Composition Datasets (S3-S7 and A3-A7).",
             group_name="All",
             group_degree=None,
             group_order=None,
@@ -110,7 +129,7 @@ class PermutationGroups(datasets.GeneratorBasedBuilder):
         if self.config.name == "all":
             # Get all individual dataset configurations
             all_configs = ["s3_data", "s4_data", "s5_data", "s6_data", "s7_data", 
-                          "a5_data", "a6_data", "a7_data"]
+                          "a3_data", "a4_data", "a5_data", "a6_data", "a7_data"]
             
             # Download all arrow files
             train_files = []
@@ -129,24 +148,18 @@ class PermutationGroups(datasets.GeneratorBasedBuilder):
                 datasets.SplitGenerator(
                     name=datasets.Split.TRAIN,
                     gen_kwargs={
-                        "filepaths": train_files,
-                        "split": "train",
+                        "files": train_files,
                     },
                 ),
                 datasets.SplitGenerator(
                     name=datasets.Split.TEST,
                     gen_kwargs={
-                        "filepaths": test_files,
-                        "split": "test",
+                        "files": test_files,
                     },
                 ),
             ]
         else:
             # Single configuration
-            # Download the dataset_dict.json to understand the structure
-            dataset_dict_url = f"{self.config.data_dir}/dataset_dict.json"
-            dataset_dict_path = dl_manager.download(dataset_dict_url)
-            
             # Download the actual data files
             data_urls = {
                 "train": f"{self.config.data_dir}/train/data-00000-of-00001.arrow",
@@ -159,34 +172,22 @@ class PermutationGroups(datasets.GeneratorBasedBuilder):
                 datasets.SplitGenerator(
                     name=datasets.Split.TRAIN,
                     gen_kwargs={
-                        "filepaths": [downloaded_files["train"]],
-                        "split": "train",
+                        "files": [downloaded_files["train"]],
                     },
                 ),
                 datasets.SplitGenerator(
                     name=datasets.Split.TEST,
                     gen_kwargs={
-                        "filepaths": [downloaded_files["test"]],
-                        "split": "test",
+                        "files": [downloaded_files["test"]],
                     },
                 ),
             ]
 
-    def _generate_examples(self, filepaths, split):
-        # Load the Arrow files and yield examples
-        # Handle both single filepath and list of filepaths
-        if isinstance(filepaths, str):
-            filepaths = [filepaths]
-        
-        example_id = 0
-        for filepath in filepaths:
-            # Load the arrow file using datasets library
-            dataset = datasets.Dataset.from_file(filepath)
-            
-            # Yield each row as an example
-            for row in dataset:
-                yield example_id, {
-                    "input_sequence": row["input_sequence"],
-                    "target": row["target"],
-                }
-                example_id += 1
+    def _generate_tables(self, files):
+        """Yield arrow tables directly for better performance."""
+        for file_idx, file in enumerate(files):
+            # Load the dataset using the datasets library format
+            dataset = datasets.Dataset.from_file(file)
+            # Get the underlying Arrow table
+            table = dataset.data.table
+            yield file_idx, table