add slicing method for NativeIterableDataset (#490)

modelscope/msdatasets/dataset_cls/dataset.py

@@ -1,7 +1,9 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 
 import copy
+import math
 import os
+from itertools import islice
 
 import datasets
 import pandas as pd
@@ -102,30 +104,60 @@ class NativeIterableDataset(IterableDataset):
                 desc='Overall progress',
                 total=self.n_shards,
                 dynamic_ncols=True):
-            ret = {}
-            if isinstance(item, dict):
-                try:
-                    for k, v in item.items():
-                        ret[k] = v
-                        if k.endswith(':FILE'):
-                            dl_manager = self._ex_iterable.kwargs.get(
-                                'dl_manager')
-                            ex_cache_path = dl_manager.download_and_extract(v)
-                            if isinstance(ex_cache_path, str):
-                                ex_cache_path = [ex_cache_path]
-                            ret[k] = ex_cache_path
-
-                except Exception as e:
-                    logger.error(e)
-                    ret = item
-            else:
-                ret = item
+            ret = self._download_item(item)
 
             yield ret
 
     def __len__(self):
         return self.n_shards
 
+    def __getitem__(self, index):
+        """
+        Returns the item at index `index` in the dataset. Slice indexing is supported.
+        """
+        if isinstance(index, int):
+            start = index
+            stop = index + 1
+            step = None
+        else:
+            start = index.start
+            stop = index.stop
+            step = index.step
+
+        if step is not None and step <= 0:
+            raise ValueError('step must be positive')
+
+        for item in tqdm(
+                islice(
+                    self.iter(batch_size=1, drop_last_batch=False), start,
+                    stop, step),
+                desc='Slicing progress',
+                dynamic_ncols=True):
+            ret = self._download_item(item)
+
+            yield ret
+
+    def _download_item(self, item):
+        ret = {}
+        if isinstance(item, dict):
+            try:
+                for k, v in item.items():
+                    ret[k] = v
+                    if k.endswith(':FILE'):
+                        dl_manager = self._ex_iterable.kwargs.get('dl_manager')
+                        ex_cache_path = dl_manager.download_and_extract(v)
+                        if isinstance(ex_cache_path, str):
+                            ex_cache_path = [ex_cache_path]
+                        ret[k] = ex_cache_path
+
+            except Exception as e:
+                logger.error(e)
+                ret = item
+        else:
+            ret = item
+
+        return ret
+
     def head(self, n=5):
         """
         Returns the first n rows of the dataset.