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permutation-groups.py

@@ -105,19 +105,22 @@ class PermutationGroups(datasets.GeneratorBasedBuilder):
             all_configs = ["s3_data", "s4_data", "s5_data", "s6_data", "s7_data", 
                           "a5_data", "a6_data", "a7_data"]
             
+            # For "all" config, we need to download each dataset's arrow files
+            # Use glob pattern to match any arrow files in the directories
             data_files = {
-                "train": [f"data/{config}/train/*.arrow" for config in all_configs],
-                "test": [f"data/{config}/test/*.arrow" for config in all_configs],
+                "train": [f"data/{config}/train/data-*-of-*.arrow" for config in all_configs],
+                "test": [f"data/{config}/test/data-*-of-*.arrow" for config in all_configs],
             }
         else:
             # The data is stored in nested folders: data/{config_name}/train and data/{config_name}/test
+            # Use glob pattern to match any arrow files
             data_files = {
-                "train": f"data/{self.config.name}/train/*.arrow",
-                "test": f"data/{self.config.name}/test/*.arrow",
+                "train": f"data/{self.config.name}/train/data-*-of-*.arrow",
+                "test": f"data/{self.config.name}/test/data-*-of-*.arrow",
             }
         
-        # Download the files
-        downloaded_files = dl_manager.download(data_files)
+        # Download and resolve the files
+        downloaded_files = dl_manager.download_and_extract(data_files)
         
         return [
             datasets.SplitGenerator(
@@ -137,26 +140,35 @@ class PermutationGroups(datasets.GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, filepaths, split):
-        # Handle both single file path and list of file paths
-        if isinstance(filepaths, str):
+        # Flatten the list if it's a list of lists (happens with "all" config)
+        if isinstance(filepaths, list) and len(filepaths) > 0 and isinstance(filepaths[0], list):
+            # Flatten nested lists
+            flat_filepaths = []
+            for sublist in filepaths:
+                if isinstance(sublist, list):
+                    flat_filepaths.extend(sublist)
+                else:
+                    flat_filepaths.append(sublist)
+            filepaths = flat_filepaths
+        elif isinstance(filepaths, str):
             filepaths = [filepaths]
         
         # Generate examples from all arrow files
         example_id = 0
         for filepath in filepaths:
-            # Handle glob patterns
-            if "*" in filepath:
-                files = glob.glob(filepath)
-            else:
-                files = [filepath]
-            
-            for file in files:
-                if os.path.exists(file):
-                    # Load the Arrow file
-                    dataset = datasets.Dataset.from_file(file)
-                    for row in dataset:
-                        yield example_id, {
-                            "input_sequence": row["input_sequence"],
-                            "target": row["target"],
-                        }
-                        example_id += 1
+            # Skip if filepath is None or empty
+            if not filepath:
+                continue
+                
+            # Load the Arrow file
+            try:
+                dataset = datasets.Dataset.from_file(filepath)
+                for row in dataset:
+                    yield example_id, {
+                        "input_sequence": row["input_sequence"],
+                        "target": row["target"],
+                    }
+                    example_id += 1
+            except Exception as e:
+                print(f"Warning: Could not load file {filepath}: {e}")
+                continue