1. 12 2月, 2018 1 次提交
  2. 10 2月, 2018 2 次提交
  3. 08 2月, 2018 1 次提交
  4. 16 11月, 2017 1 次提交
    • Y
      feature/while_grad_op (#5554) · 18f0c40a
      Yang Yang(Tony) 提交于
      * first commit
      
      * Python API for while op
      
      * Python Unittest for simple while_op forward
      
      * fix out to be list
      
      * Fix UT
      
      * VarType
      
      * Fix several bugs
      
      * Fix bug
      
      * Fix bug
      
      * Fix Bug
      
      * Fix bug
      
      * Fix unittest
      
      * Remove debug log
      
      * Add comments
      
      * add PADDLE_ENFORCE
      
      * while_grad_op first commit
      
      * Add `BlockDescBind::FindRecursiveOrCreateVar()` and fix bugs
      
      * not sure how to setdim of while outputs
      
      * push for test
      
      * add executor vlog
      
      * fix bug of while_op cond
      
      * Several enhancement for code
      
      1. Backward always infer shape & infer var type. Since there are RENAME
      variables will be created when creating backward operator, but their
      shape & var types are not inferenced.
      2. Never use SomePtr-> directly, since every pointer could be nullptr if
      it is a function return value. Add `detail::Ref` to cast pointer to
      reference safely.
      3. Enhance error message for backward.
      4. Infer data type of variable in `sum` and `tensor_write`
      
      * Fix bugs of while_op gradient
      
      * Fix several bugs of while_op grad
      
      * fix fill zeros like
      
      * fix 3 >= 3
      
      * fix place holder shouldn't be null
      
      * fail on sum op
      
      * Fix SumOp of TensorList
      
      * clean up
      
      * pass while test
      
      * fix test_array_write_read
      
      * pass sum op
      
      * Support int/int64 for fill_constant_batch_size_like
      
      * Fix compile
      18f0c40a
  5. 08 11月, 2017 2 次提交
    • Y
      Feature/rnn to array to lod tensor (#5411) · f72729d4
      Yu Yang 提交于
      * Add LoDRankTable
      
      LoD Rank Table stores the `level` of `lod` which is ordered by sequence
      length in descending order. It is useful when implement dynamic RNN and
      is shared by dynamic RNN memory, dynamic RNN slice input and dynamic
      RNN slice output operators.
      
      * Add skeleton for array_to_lod_tensor and lod_tensor_to_array
      
      * Add VarType::LoDTensorArray
      
      * Add PyBind of LoDTensorArray
      
      * Add InferVarType
      
      * Add first unittest
      
      * Add ut
      
      * Add unittest
      
      * Add unittest
      
      * Add unittests
      
      * update
      
      * init
      
      * add infershape for lod_tensor_to_array_op
      
      * compelete array_to_lod_tensor_op
      
      * copy data
      
      * clean code
      
      * clean code
      
      * Fix unittest data
      
      * fix bugs
      
      * fix compile error
      
      * Refine TensorToArrayOp
      
      * refactor array_to_lod_tensor
      
      * Unittest
      
      * fix bugs
      
      * Fix unittest
      
      * Fix unittest
      
      * debug
      
      * Debug
      
      * Fix unittest
      
      * clean code
      
      * refactor
      
      * use ostream
      
      * update test
      
      * fix gpu build error
      
      * make gpu test pass
      f72729d4
    • Y
      Rewrite fill_constant op · 5ee62383
      Yu Yang 提交于
      5ee62383
  6. 27 10月, 2017 1 次提交
  7. 21 9月, 2017 1 次提交
  8. 07 9月, 2017 3 次提交
  9. 06 9月, 2017 3 次提交
  10. 05 9月, 2017 1 次提交
    • F
      WIP · e76fa85c
      fengjiayi 提交于
      e76fa85c
  11. 14 8月, 2017 1 次提交
  12. 08 8月, 2017 1 次提交
  13. 18 7月, 2017 1 次提交
    • Y
      Fix Merge Bugs · e00aae53
      Yu Yang 提交于
      * There is a merge conflict when merge PR #2914
      * Develop and PR #2914 both add `DDim::size` method, but did not
        triger git merge conflict while merge.
      e00aae53
  14. 17 7月, 2017 3 次提交
  15. 16 7月, 2017 1 次提交
  16. 15 7月, 2017 1 次提交
  17. 14 7月, 2017 1 次提交
  18. 11 7月, 2017 3 次提交
  19. 20 6月, 2017 2 次提交
  20. 19 5月, 2017 1 次提交
  21. 18 5月, 2017 1 次提交