[Upstream] IFU 05072020 #4
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Co-authored-by: Sukru Eryilmaz <[email protected]>
* update fused bias relu backward kernel * adding support for not require first layer dgrad * fix bug: wrong layer in requires grad * add infrastructure for optional bias and activation, currently only support no bias and no relu * make bias and relu optional separately * add sigmoid activation option
* modify MTA axpby for wider load/store * Make scale/axpby/l2/adam/lamb multi_tensor uses wider load
…VIDIA#725) * Changes to make xentropysoftmax load/store vectorized when possible: Increase default ILP so that each thread handle 16 Bytes data in one step Make thread load/store longest vector possible Make unroll case handle adjacent data instead of strided, so same order compare to vector case * Add shift for not aligned case. Remove less than 16 bytes aligned access
jeffdaily
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Jan 18, 2021
Accept custom (layer type:param name) to include in sparse_parameter …
hubertlu-tw
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Oct 15, 2021
* Added support for fused ReLU and dropout into transducer joint * Reorganized code selection path in transducer joint fwd * Added support for fused ReLU+dropout into transducer joint * Vectorize transducer loss backward with fused softmax (#3) * Nanz/transducer loss (#4) * Vectorize transducer loss backward with fused softmax * Added a predicate to avoid potential IMA * Nanz/transducer loss (#5) * Vectorize transducer loss backward with fused softmax * Added a predicate to avoid potentional IMA * Added more predicates to avoid IMAs * Updated documentations for newly added features. * Fixed a error in transducer.py
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Integrate changes from upstream