1. 23 3月, 2022 1 次提交
  2. 15 3月, 2022 1 次提交
    • X
      [phi] Transfer lgamma, kldiv_loss, isclose, cumprod kernels into phi and pass... · 64223620
      xiongkun 提交于
      [phi] Transfer lgamma, kldiv_loss, isclose, cumprod kernels into phi and pass the tests of these four kernels (#39770)
      
      * tranfer and pass the lgamma unittest
      
      * merge and pass the test
      
      * transfer kldiv_loss and kldiv_loss_grad; pass the unitest
      
      * trafer the isclose and cumprod kernel
      
      * change PT_REGISTER -> PD_REGISTER
      
      * fix by code review
      
      * fix by code review
      
      * fix
      
      * remove enforce include dependence from scalar
      
      * fix
      
      * fix by code review
      
      * fix by code review
      64223620
  3. 25 2月, 2022 1 次提交
  4. 24 2月, 2022 1 次提交
  5. 20 2月, 2022 1 次提交
  6. 21 1月, 2022 1 次提交
  7. 19 10月, 2020 1 次提交
    • P
      Fix error message of multinomial op (#27946) · 975bd887
      pangyoki 提交于
      * fix multinomial doc
      
      * fix multinomial error message
      
      * little doc change
      
      * fix Categorical class doc
      
      * optimize format of error message
      
      * fix CPU Kernel error message format
      
      * fix isinf and isnan error in WindowsOPENBLAS CI
      
      * delete inf and nan
      
      * add manual_seed in sample code
      
      * little error message change
      
      * change error message to InvalidArgument
      
      * add full point for error message and add manual_seed in CPU environment
      975bd887
  8. 29 9月, 2020 1 次提交
    • P
      add multinomial op (#27219) · 7cd2c13f
      pangyoki 提交于
      * add multinomial cpu kernel
      
      * fix C++ notype error
      
      * fix windows ci array len error
      
      * let array len be const
      
      * change array to vector
      
      * add cuda kernrl with num_distribution is 1, and not support replacement=False
      
      * add multinomial python api
      
      * support num_distribution different multinomial distributions
      
      * add multinomial python api unittest
      
      * change output dtype to int64
      
      * fix coverage prob
      
      * optimize format
      
      * fix dtype of output error, should be int64_t
      7cd2c13f