updated dataloader and README config section

GBI-16-4D.py

@@ -3,9 +3,12 @@ import random
 from glob import glob
 import json
 
+
+import pyarrow as pa
 from astropy.io import fits
 import datasets
-
+from datasets import DatasetInfo, DownloadManager
+from fsspec.core import url_to_fs
 
 _DESCRIPTION = (
 "GBI-16-4D is a dataset which is part of the AstroCompress project. It contains data "
@@ -62,53 +65,67 @@ class GBI_16_4D(datasets.GeneratorBasedBuilder):
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "image": datasets.Array4D(shape=(None, 5, 800, 800), dtype="uint16"),
+                    "ra": datasets.Value("float64"),
+                    "dec": datasets.Value("float64"),
+                    "pixscale": datasets.Value("float64"),
+                    "ntimes": datasets.Value("int64"),
+                    "nbands": datasets.Value("int64"),
+                }
+            ),
+            supervised_keys=None,
             homepage=_HOMEPAGE,
             license=_LICENSE,
+            citation="TBD",
         )
 
-    def _split_generators(self, dl_manager):
+    def _split_generators(self, dl_manager: DownloadManager):
 
-        urls = _URLS[self.config.name]
-
-        data_dir = dl_manager.download_and_extract(urls) 
         ret = []
-        if "train" in data_dir:
-            ret.append(
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    gen_kwargs={"filepath": data_dir["train"],
-                                "split": "train"},
-                ),
-            )
-        if "test" in data_dir:
+        base_path = dl_manager._base_path
+        if base_path.startswith(datasets.config.HF_ENDPOINT):
+            base_path = base_path[len(datasets.config.HF_ENDPOINT):].replace("/resolve/", "@", 1)
+            base_path = "hf://" + base_path.lstrip("/")
+        _, path = url_to_fs(base_path)
+
+        for split in ["train", "test"]:
+            split_file_location = os.path.normpath(os.path.join(path, _URLS[self.config.name][split]))
+            split_file = dl_manager.download(split_file_location)
+            with open(split_file, encoding="utf-8") as f:
+                data_filenames = []
+                data_metadata = []
+                for line in f:
+                    item = json.loads(line)
+                    data_filenames.append(item["image"])
+                    data_metadata.append({"ra": item["ra"], 
+                                          "dec": item["dec"], 
+                                          "pixscale": item["pixscale"], 
+                                          "ntimes": item["ntimes"], 
+                                          "nbands": item["nbands"]})
+
+                data_urls = [os.path.normpath(os.path.join(path,data_filename)) for data_filename in data_filenames]
+                data_files = [dl_manager.download(data_url) for data_url in data_urls]
             ret.append(
                 datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    gen_kwargs={"filepath": data_dir["test"],
-                                "split": "test"},
+                    name=datasets.Split.TRAIN if split == "train" else datasets.Split.TEST,
+                    gen_kwargs={"filepaths": data_files,
+                                "split_file": split_file,
+                                "split": split, 
+                                "data_metadata": data_metadata},
                 ),
             )
         return ret
 
-    def _generate_examples(self, filepath, split, base_url=_URL):
+    def _generate_examples(self, filepaths, split_file, split, data_metadata):
         """Generate GBI-16-4D examples"""
 
-        with open(filepath, "r") as f:
-            idx = 0
-            for line in f:
-                task_instance_key = f"{self.config.name}-{split}-{idx}"
-                item = json.loads(line)
-                image_path = os.path.join(base_url, item["image"].split("./")[-1])
-                with fits.open(image_path, memmap=False) as hdul:
-                    image_data = hdul[0].data
-                    yield task_instance_key, {"image": image_data, 
-                                            "ra": item["ra"], 
-                                            "dec": item["dec"], 
-                                            "pixscale": item["pixscale"], 
-                                            "ntimes": item["ntimes"], 
-                                            "nbands": item["nbands"]}
-                idx += 1
-
+        for idx, (filepath, item) in enumerate(zip(filepaths, data_metadata)):
+            task_instance_key = f"{self.config.name}-{split}-{idx}"
+            with fits.open(filepath, memmap=False) as hdul:
+                image_data = hdul[0].data.tolist()
+                yield task_instance_key, {**{"image": image_data}, **item}
 
 def make_split_jsonl_files(config_type="tiny", data_dir="./data", 
                         outdir="./splits", seed=42):

README.md

@@ -9,10 +9,13 @@ dataset_info:
   config_name: tiny
   features:
   - name: image
-    sequence:
-      sequence:
-        sequence:
-          sequence: uint16
+    dtype:
+      array4_d:
+        shape:
+        - 5
+        - 800
+        - 800
+        dtype: uint16
   - name: ra
     dtype: float64
   - name: dec
@@ -30,7 +33,7 @@ dataset_info:
   - name: test
     num_bytes: 352881364
     num_examples: 1
-  download_size: 692
+  download_size: 908845172
   dataset_size: 911075540
 ---
 GBI-16-4D Dataset