[gluon][transform]fix unpicklable transform_first on windows

python/mxnet/gluon/data/dataset.py

@@ -88,11 +88,7 @@ def transform_first(self, fn, lazy=True):
         Dataset
             The transformed dataset.
         """
-        def base_fn(x, *args):
-            if args:
-                return (fn(x),) + args
-            return fn(x)
-        return self.transform(base_fn, lazy)
+        return self.transform(_TransformFirstClosure(fn), lazy)
 
 
 class SimpleDataset(Dataset):
@@ -129,6 +125,16 @@ def __getitem__(self, idx):
         return self._fn(item)
 
 
+class _TransformFirstClosure(object):
+    """Use callable object instead of nested function, it can be pickled."""
+    def __init__(self, fn):
+        self._fn = fn
+
+    def __call__(self, x, *args):
+        if args:
+            return (self._fn(x),) + args
+        return self._fn(x)
+
 class ArrayDataset(Dataset):
     """A dataset that combines multiple dataset-like objects, e.g.
     Datasets, lists, arrays, etc.

tests/python/unittest/test_gluon_data.py

@@ -77,6 +77,10 @@ def _dataset_transform_fn(x, y):
     """Named transform function since lambda function cannot be pickled."""
     return x, y
 
+def _dataset_transform_first_fn(x):
+    """Named transform function since lambda function cannot be pickled."""
+    return x
+
 @with_seed()
 def test_recordimage_dataset_with_data_loader_multiworker():
     recfile = prepare_record()
@@ -95,17 +99,13 @@ def test_recordimage_dataset_with_data_loader_multiworker():
         assert x.shape[0] == 1 and x.shape[3] == 3
         assert y.asscalar() == i
 
-    # try limit recursion depth
-    import sys
-    old_limit = sys.getrecursionlimit()
-    sys.setrecursionlimit(500)  # this should be smaller than any default value used in python
-    dataset = gluon.data.vision.ImageRecordDataset(recfile).transform(_dataset_transform_fn)
+    # with transform_first
+    dataset = gluon.data.vision.ImageRecordDataset(recfile).transform_first(_dataset_transform_first_fn)
     loader = gluon.data.DataLoader(dataset, 1, num_workers=5)
 
     for i, (x, y) in enumerate(loader):
         assert x.shape[0] == 1 and x.shape[3] == 3
         assert y.asscalar() == i
-    sys.setrecursionlimit(old_limit)
 
 @with_seed()
 def test_sampler():