bartekkuncer edited a comment on issue #20967:
URL: 
https://github.com/apache/incubator-mxnet/issues/20967#issuecomment-1073966623


   Hi @DickJC123,
   1. 
https://jenkins.mxnet-ci.com/blue/organizations/jenkins/mxnet-validation%2Funix-cpu/detail/PR-20965/5/pipeline/288/
 test_fc_subgraph.py::test_fc_transpose[mxnet.numpy-int8-True-data_shape2]
   - Not related to oneDNN upgrade, @anko-intel analyzed it and here is PR with 
the fix https://github.com/apache/incubator-mxnet/pull/20969
   2. 
https://jenkins.mxnet-ci.com/blue/organizations/jenkins/mxnet-validation%2Funix-cpu/detail/PR-20965/2/pipeline/
 (test_conv_subgraph.py::test_pos_conv_act_add[True-gelu-True-data_shape1])
   AND
   
https://jenkins.mxnet-ci.com/blue/organizations/jenkins/mxnet-validation%2Funix-cpu/detail/PR-20965/3/pipeline/288
 (test_conv_subgraph.py::test_pos_conv_act_add[True-leakyrelu-True-data_shape1])
   - These two suffer from reading data from a neither updated nor zeroed 
register during convolution with the number of input channels lower than 4 and 
blocked weights (https://github.com/apache/incubator-mxnet/issues/20826). The 
full fix will arrive in v2.6 of oneDNN, therefore temporarily we will force 
plain format (at least on this axis) to make the convolution work properly and 
the test to pass PR: https://github.com/apache/incubator-mxnet/pull/20970.


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