diff --git a/egs/librispeech/ASR/transducer_stateless/joiner.py b/egs/librispeech/ASR/transducer_stateless/joiner.py
index 55f0a81f1..b0ba7fd83 100644
--- a/egs/librispeech/ASR/transducer_stateless/joiner.py
+++ b/egs/librispeech/ASR/transducer_stateless/joiner.py
@@ -55,6 +55,9 @@ class Joiner(nn.Module):
 
         N = encoder_out.size(0)
 
+        encoder_out_len = encoder_out_len.tolist()
+        decoder_out_len = decoder_out_len.tolist()
+
         encoder_out_list = [
             encoder_out[i, : encoder_out_len[i], :] for i in range(N)
         ]
diff --git a/egs/librispeech/ASR/transducer_stateless/test_joiner.py b/egs/librispeech/ASR/transducer_stateless/test_joiner.py
new file mode 100755
index 000000000..6c6f2b19b
--- /dev/null
+++ b/egs/librispeech/ASR/transducer_stateless/test_joiner.py
@@ -0,0 +1,57 @@
+#!/usr/bin/env python3
+# Copyright    2021  Xiaomi Corp.        (authors: Fangjun Kuang)
+#
+# See ../../../../LICENSE for clarification regarding multiple authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+To run this file, do:
+
+    cd icefall/egs/librispeech/ASR
+    python ./transducer_stateless/test_joiner.py
+"""
+
+import torch
+from joiner import Joiner
+
+
+def test_joiner():
+    device = torch.device("cpu")
+    input_dim = 3
+    output_dim = 5
+    joiner = Joiner(input_dim, output_dim)
+    joiner.to(device)
+
+    encoder_out = torch.rand(3, 10, input_dim, device=device)
+    decoder_out = torch.rand(3, 8, input_dim, device=device)
+
+    encoder_out_len = torch.tensor([5, 10, 3], device=device)
+    decoder_out_len = torch.tensor([6, 8, 7], device=device)
+
+    out = joiner(
+        encoder_out=encoder_out,
+        decoder_out=decoder_out,
+        encoder_out_len=encoder_out_len,
+        decoder_out_len=decoder_out_len,
+    )
+    assert out.size(0) == (encoder_out_len * decoder_out_len).sum()
+    assert out.size(1) == output_dim
+
+
+def main():
+    test_joiner()
+
+
+if __name__ == "__main__":
+    main()