1. 24 9月, 2020 1 次提交
    • W
      use iwyu clean include (#27267) · df43905f
      wanghuancoder 提交于
      * use iwyu clean include, test=develop, test=win
      
      * compilation error, test=develop
      
      * fix compilation error2, test=develop
      
      * fix compilation error3, test=develop
      
      * fix compilation error4, test=develop
      
      * fix compilation error5, test=develop
      
      * fix compilation error6, test=develop
      
      * fix compilation error7, test=develop
      
      * fix compilation error8, test=develop
      
      * fix compilation error8, test=develop
      
      * fix compilation error10, test=develop
      
      * fix compilation error11, test=develop
      df43905f
  2. 18 9月, 2020 1 次提交
  3. 22 8月, 2020 1 次提交
  4. 24 4月, 2020 1 次提交
    • G
      Add cholesky_op (#23543) · a8c0fb4e
      Guo Sheng 提交于
      * Add cholesky_op forward part. test=develop
      
      * Complete cholesky_op forward part. test=develop
      
      * Add cholesky_op backward part. test=develop
      
      * Complete cholesky_op backward part. test=develop
      
      * Refine cholesky_op error check and docs. test=develop
      
      * Add grad_check unit test for cholesky_op. test=develop
      
      * Fix sample code in cholesky doc. test=develop
      
      * Refine some error messages of cholesky_op. test=develop
      
      * Refine some error messages of cholesky_op. test=develop
      
      * Remove unused input in cholesky_grad. test=develop
      
      * Remove unused input in cholesky_grad. test=develop
      
      * Fix stream for cusolverDnSetStream. test=develop
      
      * Update PADDLE_ENFORCE_CUDA_SUCCESS from cholesky_op to adapt to latest code.
      test=develop
      
      * Add CUSOLVER ERROR in enforce.h
      test=develop
      
      * Fix the missing return value in cholesky. test=develop
      a8c0fb4e
  5. 28 2月, 2020 1 次提交
  6. 22 11月, 2019 1 次提交
    • L
      add dequantize_abs_max op and modify lookup_table op (#20899) · f0b15184
      Liufang Sang 提交于
      * add int8 kernel to lookup_table op and add dequantize op test=develop
      
      * change paddle_enforce to paddle_enforce_eq test=develop
      
      * change copyright and change some not suitable code test=develop
      
      * remove debug log test=develop
      
      * replace GetInputType with IndicateVarDataType test=develop
      
      * fix EmptyGradMaker test=develop
      
      * fix diff between cpu and gpu test=develop
      
      * use memcopy when int8_t test=develop
      f0b15184
  7. 30 9月, 2019 1 次提交
  8. 25 9月, 2019 1 次提交
    • B
      add support of matmul with multiple head even different width and height (#19708) · c670058a
      Bob Zhu 提交于
      * add support of matmul with multiple head even different width and height
      
      Original matmul with multiple head supports only the mat_a.width == mat_b.height,
      in that case, mat_b will be horizontally split. In this patch, we extend the
      support when mat_a.width != mat_b.height but mat_a.width/head_number == mat_b.height,
      in this case, mab_b will be vertically split.
      
      One example is A is [3, 8], B is [2, 16], head_number is 4. In this
      case, A will be split as [3, 2], B will be (vertically) split as
      [2, 4]. The final result will be 4 matrix of 4 matrix of [3,4], i.e. [3, 16]
      
      test=develop
      
      * add support of matmul with multiple head even different width and height
      
      Original matmul with multiple head supports only the mat_a.width == mat_b.height,
      in that case, mat_b will be horizontally split. In this patch, we extend the
      support when mat_a.width != mat_b.height but mat_a.width/head_number == mat_b.height,
      in this case, mab_b will be vertically split.
      
      One example is A is [3, 8], B is [2, 16], head_number is 4. In this
      case, A will be split as [3, 2], B will be (vertically) split as
      [2, 4]. The final result will be 4 matrix of 4 matrix of [3,4], i.e. [3, 16]
      
      test=develop
      
      * refactor the code of matmul with multiple head even different width and height
      
      test=develop
      c670058a
  9. 04 9月, 2019 1 次提交
  10. 02 9月, 2019 1 次提交
  11. 20 8月, 2019 1 次提交
  12. 24 7月, 2019 1 次提交
    • B
      Extend Matmul to support matrix multiplication with multiple heads (#18570) · 220eef60
      Bob Zhu 提交于
      * extend matmul op to support multiple head multiplication
      
      With the support of multiple head, the multiplication of two big matrixes is
      split into multiplication of several (head_number) small matrixes. e.g. if
      Mat A is [3, 24] and Mat B is [24, 4], when multiple A and B with head_number
      as 4, Mat A will be split as 4 matrix of [3, 6] and Mat B will be 4 matrix of
      [6, 4]. The result of final matrix will be 4 matrix of [3, 4], i.e. [3, 16].
      220eef60
  13. 28 6月, 2019 1 次提交
  14. 04 3月, 2019 1 次提交
  15. 26 2月, 2019 1 次提交
  16. 22 2月, 2019 2 次提交
    • T
      Revert 15770 develop a6910f90 gelu mkl opt (#15872) · ee2321de
      tensor-tang 提交于
      * Revert "Optimze Gelu with MKL Erf function (#15770)"
      
      This reverts commit 676995c8.
      
      * test=develop
      ee2321de
    • Y
      Optimze Gelu with MKL Erf function (#15770) · 676995c8
      Yihua Xu 提交于
      * Optimize for gelu operator
      
      * Set up the low accuracy mode of MKL ERF function.
      
      test=develop
      
      * Only enable MKLML ERF when OS is linux
      
      * Use the speical mklml version included vmsErf function to verify gelu mkl kernel.
      
      test=develop
      
      * Add the CUDA macro to avoid NVCC's compile issue.
      
      test=develop
      
      * Add the TODO comments for mklml library modification.
      
      test=develop
      
      * Clean Code
      
      test=develop
      
      * Add the comment of marco for NVCC compiler.
      
      test=develop
      676995c8
  17. 13 12月, 2018 1 次提交
  18. 28 11月, 2018 1 次提交
  19. 27 11月, 2018 2 次提交
  20. 16 11月, 2018 1 次提交
  21. 13 11月, 2018 1 次提交
  22. 22 8月, 2018 5 次提交
  23. 16 8月, 2018 1 次提交
  24. 06 8月, 2018 1 次提交
  25. 03 8月, 2018 1 次提交
  26. 18 7月, 2018 2 次提交
  27. 11 7月, 2018 2 次提交
  28. 10 7月, 2018 1 次提交
  29. 09 7月, 2018 1 次提交
  30. 05 7月, 2018 1 次提交
  31. 20 6月, 2018 1 次提交
  32. 24 5月, 2018 1 次提交