Fix loader path for HF dataset

isonetpp_loader.py

@@ -7,41 +7,75 @@ from huggingface_hub import hf_hub_download
 from subiso_dataset import (
     SubgraphIsomorphismDataset,
     TRAIN_MODE, VAL_MODE, TEST_MODE, BROAD_TEST_MODE,
-    GMN_DATA_TYPE, PYG_DATA_TYPE
 )
 
-# Normalize names users pass ("aids" or "aids240k" → stored names are aids240k)
-def _normalize_name(name: str) -> str:
-    if name.endswith("240k") or name.endswith("80k"):
-        return name
-    # assume large dataset default = 240k
-    return name + "240k"
+# ----------------------------
+# Helpers
+# ----------------------------
 
-def _folder(dataset_size: str) -> str:
+def _pairs_for_size(dataset_size: str) -> str:
+    return "80k" if dataset_size == "small" else "240k"
+
+def _folder_for_size(dataset_size: str) -> str:
     return "small_dataset" if dataset_size == "small" else "large_dataset"
 
+def _normalize_name(base_name: str, dataset_size: str) -> str:
+    """
+    Accepts 'aids' or 'aids240k'.
+    If user passes bare name, append pairs; if they already passed '...80k/240k', keep as-is.
+    """
+    pairs = _pairs_for_size(dataset_size)
+    if base_name.endswith(("80k", "240k")):
+        return base_name
+    return f"{base_name}{pairs}"
+
+def _mode_prefix_and_dir(mode: str) -> tuple[str, str]:
+    """
+    File prefix uses 'test' when mode contains 'test' (your repo convention).
+    Directory only has train/val/test. Map Extra_test_300 => 'test'.
+    """
+    prefix = "test" if "test" in mode.lower() else mode
+    mode_dir = "test" if "test" in mode.lower() else mode  # maps Extra_test_300 -> test
+    return prefix, mode_dir
+
+# ----------------------------
+# Path resolution + downloads
+# ----------------------------
+
 def _ensure_paths(
     repo_id: str,
     mode: str,
-    dataset_name: str,
-    dataset_size: str,
+    dataset_name: str,      # can be 'aids' or 'aids240k'
+    dataset_size: str,      # 'small' | 'large'
     local_root: Optional[str] = None,
 ) -> Dict[str, str]:
+    """
+    Download the three files needed into cache (or local_root if set):
+      - splits/<mode_dir>/<prefix>_<base>_query_subgraphs.pkl
+      - splits/<mode_dir>/<prefix>_<base>_rel_nx_is_subgraph_iso.pkl
+      - corpus/<base>_corpus_subgraphs.pkl
+    where <base> is the normalized dataset name (includes 80k/240k exactly once).
+    """
+    pairs = _pairs_for_size(dataset_size)
+    folder = _folder_for_size(dataset_size)           # "large_dataset" or "small_dataset"
+    base = _normalize_name(dataset_name, dataset_size)  # e.g., "aids240k" (no double-append)
+    prefix, mode_dir = _mode_prefix_and_dir(mode)
 
-    dataset_name = _normalize_name(dataset_name)
-    folder = _folder(dataset_size)              # "large_dataset" or "small_dataset"
-    prefix = "test" if "test" in mode.lower() else mode
-    pairs = "80k" if dataset_size == "small" else "240k"
-
-    query_fname  = f"{prefix}_{dataset_name}{pairs}_query_subgraphs.pkl"
-    rel_fname    = f"{prefix}_{dataset_name}{pairs}_rel_nx_is_subgraph_iso.pkl"
-    corpus_fname = f"{dataset_name}{pairs}_corpus_subgraphs.pkl"
+    # exact filenames used in your repo
+    query_fname  = f"{prefix}_{base}_query_subgraphs.pkl"
+    rel_fname    = f"{prefix}_{base}_rel_nx_is_subgraph_iso.pkl"
+    corpus_fname = f"{base}_corpus_subgraphs.pkl"
 
-    repo_query_path  = f"{folder}/splits/{mode}/{query_fname}"
-    repo_rel_path    = f"{folder}/splits/{mode}/{rel_fname}"
+    repo_query_path  = f"{folder}/splits/{mode_dir}/{query_fname}"
+    repo_rel_path    = f"{folder}/splits/{mode_dir}/{rel_fname}"
     repo_corpus_path = f"{folder}/corpus/{corpus_fname}"
 
-    kwargs = dict(repo_id=repo_id, repo_type="dataset", local_dir=local_root, local_dir_use_symlinks=False)
+    kwargs = dict(
+        repo_id=repo_id,
+        repo_type="dataset",
+        local_dir=local_root,
+        local_dir_use_symlinks=False,
+    )
 
     query_path  = hf_hub_download(filename=repo_query_path,  **kwargs)
     rel_path    = hf_hub_download(filename=repo_rel_path,    **kwargs)
@@ -49,19 +83,27 @@ def _ensure_paths(
 
     return {"query": query_path, "rel": rel_path, "corpus": corpus_path}
 
+# ----------------------------
+# Public entrypoint
+# ----------------------------
+
 def load_isonetpp_benchmark(
     repo_id: str = "structlearning/isonetpp-benchmark",
-    mode: str = "train",
-    dataset_name: str = "aids",
-    dataset_size: str = "large",
+    mode: str = "train",            # "train" | "val" | "test" | "Extra_test_300"
+    dataset_name: str = "aids",     # "aids" or "aids240k" (same for mutag/ptc_*)
+    dataset_size: str = "large",    # "small" | "large"
     batch_size: int = 128,
-    data_type: str = "pyg",
+    data_type: str = "pyg",         # "pyg" or "gmn"
     device: Optional[str] = None,
     download_root: Optional[str] = None,
 ):
+    # Map user mode to your class constants
     mode_map = {
-        "train": TRAIN_MODE, "val": VAL_MODE, "test": TEST_MODE,
-        "extra_test_300": BROAD_TEST_MODE, "Extra_test_300": BROAD_TEST_MODE
+        "train": TRAIN_MODE,
+        "val": VAL_MODE,
+        "test": TEST_MODE,
+        "extra_test_300": BROAD_TEST_MODE,
+        "Extra_test_300": BROAD_TEST_MODE,
     }
     mode_norm = mode_map.get(mode, mode)
 
@@ -70,25 +112,24 @@ def load_isonetpp_benchmark(
         mode=mode_norm,
         dataset_name=dataset_name,
         dataset_size=dataset_size,
-        local_root=download_root
+        local_root=download_root,
     )
 
-    # The downloaded structure is:
-    # <cache>/.../<folder>/splits/<mode>/<files>
-    # <cache>/.../<folder>/corpus/<files>
-    #
-    # So dataset_base_path = parent of <folder>
-    base_path = os.path.dirname(os.path.dirname(paths["query"]))   # .../<folder>/splits
-    dataset_base_path = os.path.dirname(base_path)                 # .../<folder>
+    # paths["query"] points to .../<folder>/splits/<mode_dir>/<file>
+    # dataset_base_path must be the parent "<folder>" so that subiso_dataset finds:
+    #   dataset_base_path/{splits/<mode_dir>/..., corpus/...}
+    splits_dir = os.path.dirname(paths["query"])           # .../<folder>/splits/<mode_dir>
+    folder_dir = os.path.dirname(splits_dir)               # .../<folder>
+    dataset_base_path = folder_dir
 
     dataset_config = dict(
         mode=mode_norm,
-        dataset_name=_normalize_name(dataset_name),
+        dataset_name=_normalize_name(dataset_name, dataset_size),  # ensure '...240k' once
         dataset_size=dataset_size,
         batch_size=batch_size,
         data_type=data_type,
         dataset_base_path=dataset_base_path,
-        dataset_path_override=_folder(dataset_size),   # 🟢 critical fix
+        dataset_path_override=_folder_for_size(dataset_size),      # critical: "large_dataset"/"small_dataset"
         experiment=None,
         device=device,
     )