ptrendx commented on issue #9774: does not respect dtype 
   There are few possible explanations.
   The most probable reason is workspace size for convolutions. I tried 
pitching @piiswrong to change the default MXNet's behavior of limiting the 
results of cudnnFind to the ones fitting the workspace, but did not have luck 
with that. Try with MXNET_CUDNN_AUTOTUNE_DEFAULT = 2. 
   Also if you tried benchmarking with real data, make sure you are not limited 
by the IO (you may need to set --data-nthreads to something more than the 
default 4).
   And finally, depthwise convolutions in networks like resnext do not 
currently benefit much from TensorCore, so if that is what you tested, then 
benefit should be small.

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