WEIGHT_FORMAT_WARN in RNN.cpp does not get set on rocm

[bmedishe]

🚀 The feature, motivation and pitch

I am working on enabling test_nn.py test_cudnn_weight_format on rocm, an observed that the test works if

diff --git a/test/test_nn.py b/test/test_nn.py
index c8311c91d7..85b391e880 100644
--- a/test/test_nn.py
+++ b/test/test_nn.py
@@ -8460,8 +8460,9 @@ tensor(..., device='meta', size=(1,), requires_grad=True)""")
                 with warnings.catch_warnings(record=True) as w:
                     output_noncontig = rnn(input, hx)
                 if first_warn:
-                    self.assertEqual(len(w), 1)
-                    self.assertIn('weights are not part of single contiguous chunk of memory', w[0].message.args[0])
+                    if (torch.version.hip is None):
+                        self.assertEqual(len(w), 1)
+                        self.assertIn('weights are not part of single contiguous chunk of memory', w[0].message.args[0])
                     first_warn = False
                     warnings.resetwarnings()
                 output_noncontig[0].sum().backward()

This warning is generated from aten/src/ATen/native/cudnn/RNN.cpp

How can this test pass without bypassing the above checks ??

Alternatives

No response

Additional context

No response

[jithunnair-amd]

This might simply be a result of the corresponding MIOpen file being out-of-sync with the cudnn file.

@alugorey has been looking into the RNN implementation for a different issue, but this issue might also get resolved if and when we sync up the MIOpen version with the CUDNN version, so co-assigning this to Andy.

[alugorey]

@jithunnair-amd @bmedishe Jithun is correct. This error is a direct side effect of the lack of weight flattening in our version of RNNs.