Add random split transform (#1213)

datumaro/datumaro/plugins/transforms.py

@@ -5,6 +5,7 @@
 
 import logging as log
 import os.path as osp
+import random
 
 import pycocotools.mask as mask_utils
 
@@ -295,6 +296,66 @@ class MapSubsets(Transform, CliPlugin):
         return self.wrap_item(item,
             subset=self._mapping.get(item.subset, item.subset))
 
+class RandomSplit(Transform, CliPlugin):
+    """
+    Joins all subsets into one and splits the result into few parts.
+    It is expected that item ids are unique and subset ratios sum up to 1.|n
+    |n
+    Example:|n
+    |s|s%(prog)s --subset train:.67 --subset test:.33
+    """
+
+    @staticmethod
+    def _split_arg(s):
+        parts = s.split(':')
+        if len(parts) != 2:
+            import argparse
+            raise argparse.ArgumentTypeError()
+        return (parts[0], float(parts[1]))
+
+    @classmethod
+    def build_cmdline_parser(cls, **kwargs):
+        parser = super().build_cmdline_parser(**kwargs)
+        parser.add_argument('-s', '--subset', action='append',
+            type=cls._split_arg, dest='splits',
+            help="Subsets in the form of: '<subset>:<ratio>' (repeatable)")
+        parser.add_argument('--seed', type=int, help="Random seed")
+        return parser
+
+    def __init__(self, extractor, splits, seed=None):
+        super().__init__(extractor)
+
+        total_ratio = sum((s[1] for s in splits), 0)
+        if not total_ratio == 1:
+            raise Exception(
+                "Sum of ratios is expected to be 1, got %s, which is %s" %
+                (splits, total_ratio))
+
+        dataset_size = len(extractor)
+        indices = list(range(dataset_size))
+
+        random.seed(seed)
+        random.shuffle(indices)
+
+        parts = []
+        s = 0
+        for subset, ratio in splits:
+            s += ratio
+            boundary = int(s * dataset_size)
+            parts.append((boundary, subset))
+
+        self._parts = parts
+
+    def _find_split(self, index):
+        for boundary, subset in self._parts:
+            if index < boundary:
+                return subset
+        return subset
+
+    def __iter__(self):
+        for i, item in enumerate(self._extractor):
+            yield self.wrap_item(item, subset=self._find_split(i))
+
 class IdFromImageName(Transform, CliPlugin):
     def transform_item(self, item):
         name = item.id

datumaro/tests/test_transforms.py

@@ -320,3 +320,40 @@ class TransformsTest(TestCase):
 
         actual = transforms.BoxesToMasks(SrcExtractor())
         compare_datasets(self, DstExtractor(), actual)
+
+    def test_random_split(self):
+        class SrcExtractor(Extractor):
+            def __iter__(self):
+                return iter([
+                    DatasetItem(id=1, subset="a"),
+                    DatasetItem(id=2, subset="a"),
+                    DatasetItem(id=3, subset="b"),
+                    DatasetItem(id=4, subset="b"),
+                    DatasetItem(id=5, subset="b"),
+                    DatasetItem(id=6, subset=""),
+                    DatasetItem(id=7, subset=""),
+                ])
+
+        actual = transforms.RandomSplit(SrcExtractor(), splits=[
+            ('train', 4.0 / 7.0),
+            ('test', 3.0 / 7.0),
+        ])
+
+        self.assertEqual(4, len(actual.get_subset('train')))
+        self.assertEqual(3, len(actual.get_subset('test')))
+
+    def test_random_split_gives_error_on_non1_ratios(self):
+        class SrcExtractor(Extractor):
+            def __iter__(self):
+                return iter([DatasetItem(id=1)])
+
+        has_error = False
+        try:
+            transforms.RandomSplit(SrcExtractor(), splits=[
+                ('train', 0.5),
+                ('test', 0.7),
+            ])
+        except Exception:
+            has_error = True
+
+        self.assertTrue(has_error)