fix dropout scaling from p to 1/(1-p) in multihead attention #816
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kevinstephano
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lcskrishna
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* fix dropout scaling from p to 1/(1-p) (NVIDIA#816) Co-authored-by: Sukru Eryilmaz <[email protected]> * Improvements to apex.mlp (NVIDIA#804) * 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 * enable wider load/store for multi_tensor_apply kernels (NVIDIA#763) * modify MTA axpby for wider load/store * Make scale/axpby/l2/adam/lamb multi_tensor uses wider load * Changes to make xentropysoftmax load/store vectorized when possible: (NVIDIA#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 Co-authored-by: Burc Eryilmaz <[email protected]> Co-authored-by: Sukru Eryilmaz <[email protected]> Co-authored-by: Deyu Fu <[email protected]>
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Fixes dropout scaling in backward pass of multihead attention