pack_padded_sequence: Check for empty (zero-element) tensors (#21461)

Summary:
Fixes: #20529

Thank you, JamieCT for the bug report with reproducing script.
Pull Request resolved: pytorch/pytorch#21461

Differential Revision: D15696183

Pulled By: ezyang

fbshipit-source-id: a93cde2c924f8447563c64ce8a1cf75fcee60a01

aten/src/ATen/native/PackedSequence.cpp

@@ -20,6 +20,7 @@ std::tuple<Tensor, Tensor> _pack_padded_sequence(const Tensor& _input, const Ten
 
   int64_t batch_size = input.size(1);
   int64_t * lengths = lengths_t.data<int64_t>();
+  TORCH_CHECK(input.numel() > 0, "Cannot pack empty tensors.");
   TORCH_CHECK(lengths_t.size(0) == batch_size,
            "Expected `len(lengths)` to be equal to batch_size, but got ", lengths_t.size(0),
            " (batch_size=", batch_size, ")");

test/test_nn.py

@@ -5329,9 +5329,11 @@ def pad(tensor, length):
                 if l < 10:
                     self.assertEqual(padded.grad.data[l:, i].abs().sum(), 0)
 
-        # test error message
+        # test error messages
         with self.assertRaisesRegex(RuntimeError, 'You can pass `enforce_sorted=False`'):
             packed = rnn_utils.pack_padded_sequence(torch.randn(3, 3), [1, 3, 2])
+        with self.assertRaisesRegex(RuntimeError, 'empty tensor'):
+            packed = rnn_utils.pack_padded_sequence(torch.randn(0, 0), [])
 
     def _test_variable_sequence(self, device="cpu", dtype=torch.float):
         def pad(var, length):