diff --git a/python/paddle/io/__init__.py b/python/paddle/io/__init__.py
index 8d9a1909f07ca..6a0f6e05a37d5 100755
--- a/python/paddle/io/__init__.py
+++ b/python/paddle/io/__init__.py
@@ -25,6 +25,7 @@
     Sampler,
     SequenceSampler,
     Subset,
+    SubsetRandomSampler,
     TensorDataset,
     WeightedRandomSampler,
     get_worker_info,
@@ -48,4 +49,5 @@
     'WeightedRandomSampler',
     'random_split',
     'Subset',
+    'SubsetRandomSampler',
 ]
diff --git a/python/paddle/io/dataloader/__init__.py b/python/paddle/io/dataloader/__init__.py
index bb65463f70afc..aff32fd70de49 100644
--- a/python/paddle/io/dataloader/__init__.py
+++ b/python/paddle/io/dataloader/__init__.py
@@ -29,3 +29,4 @@
 from .sampler import SequenceSampler
 from .sampler import RandomSampler
 from .sampler import WeightedRandomSampler
+from .sampler import SubsetRandomSampler
diff --git a/python/paddle/io/dataloader/sampler.py b/python/paddle/io/dataloader/sampler.py
index 44bc545f777cd..f6bb2e41b4b8f 100644
--- a/python/paddle/io/dataloader/sampler.py
+++ b/python/paddle/io/dataloader/sampler.py
@@ -15,6 +15,7 @@
 import numpy as np
 
 from ...framework import core
+from ...tensor import randperm
 
 
 class Sampler:
@@ -340,3 +341,45 @@ def __iter__(self):
     def __len__(self):
         mul = np.prod(self.weights.shape) // self.weights.shape[-1]
         return self.num_samples * mul
+
+
+class SubsetRandomSampler(Sampler):
+    r"""
+    Randomly sample elements from a given list of indices, without replacement.
+
+    Args:
+        indices (sequence): a sequence of indices
+
+    Examples:
+
+        .. code-block:: python
+
+            >>> import paddle
+            >>> from paddle.io import SubsetRandomSampler
+
+            >>> paddle.seed(2023)
+            >>> sampler = SubsetRandomSampler(indices=[1, 3, 5, 7, 9])
+
+            >>> for index in sampler:
+            ...     print(index)
+            9
+            3
+            7
+            5
+            1
+
+    """
+
+    def __init__(self, indices):
+        if len(indices) == 0:
+            raise ValueError(
+                "The length of `indices` in SubsetRandomSampler should be greater than 0."
+            )
+        self.indices = indices
+
+    def __iter__(self):
+        for i in randperm(len(self.indices)):
+            yield self.indices[i]
+
+    def __len__(self) -> int:
+        return len(self.indices)
diff --git a/test/legacy_test/test_batch_sampler.py b/test/legacy_test/test_batch_sampler.py
index 72ea1577beb53..750a916b3b29a 100644
--- a/test/legacy_test/test_batch_sampler.py
+++ b/test/legacy_test/test_batch_sampler.py
@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import random
 import unittest
 
 import numpy as np
@@ -22,6 +23,7 @@
     RandomSampler,
     Sampler,
     SequenceSampler,
+    SubsetRandomSampler,
     WeightedRandomSampler,
 )
 
@@ -110,6 +112,28 @@ def test_with_generator_num_samples(self):
         assert tuple(sorted(rets)) == tuple(range(0, 50))
 
 
+class TestSubsetRandomSampler(unittest.TestCase):
+    def test_main(self):
+        indices = list(range(100))
+        random.shuffle(indices)
+        indices = indices[:30]
+        sampler = SubsetRandomSampler(indices)
+        assert len(sampler) == len(indices)
+
+        hints = {i: 0 for i in indices}
+        for index in iter(sampler):
+            hints[index] += 1
+        for h in hints.values():
+            assert h == 1
+
+    def test_raise(self):
+        try:
+            sampler = SubsetRandomSampler([])
+            self.assertTrue(False)
+        except ValueError:
+            self.assertTrue(True)
+
+
 class TestBatchSampler(unittest.TestCase):
     def setUp(self):
         self.num_samples = 1000