1. 09 4月, 2019 1 次提交
    • H
      Fix op registry (#16677) · 2146293d
      Huihuang Zheng 提交于
      list of fixed ops:
      lookup_table_op
      space_to_depth_op
      squared_l2_distance_op
      squared_l2_norm_op
      teacher_student_sigmoid_loss_op
      tree_conv_op
      warpctc_op
      
      test=develop
      2146293d
  2. 25 12月, 2018 1 次提交
  3. 19 12月, 2018 1 次提交
  4. 12 12月, 2018 1 次提交
  5. 16 11月, 2018 1 次提交
    • W
      Add cudnn ctc loss (#12366) · b32c13dc
      Wu Yi 提交于
      * add cudnn ctc loss
      
      * wip add test test=develop
      
      * wip
      
      * wip
      
      * done test=develop
      
      * move include cudnn test=develop
      
      * test test=develop
      
      * fix build test=develop
      
      * fix build test=develop
      
      * fix build on cudnn5 test=develop
      
      * fix cudnn5 build test=develop
      
      * fix cudnn5 build test=develop
      
      * merge develop softmax functor change test=develop
      b32c13dc
  6. 08 5月, 2018 1 次提交
    • Y
      Clean OpProtoAndCheckerMaker · 0e78cb69
      Yu Yang 提交于
      Do not use ctor
      
      * Reduce line of codes.
      * We can use virtual function for Maker now.
      * The implementation does not care what maker holds, it is easier to
      refactor later.
      0e78cb69
  7. 19 4月, 2018 1 次提交
  8. 17 4月, 2018 1 次提交
  9. 12 2月, 2018 1 次提交
  10. 10 2月, 2018 2 次提交
  11. 09 1月, 2018 1 次提交
    • Y
      Port WarpCTC Operator (#5107) · b5fda272
      Yiqun Liu 提交于
      * Add Seq2BatchFunctor, which will be used in WarpCTCOp.
      
      * Implement WrapCTCFunctor and WrapCTCKernel.
      
      * Add unittest of warpctc_op.
      
      * Modify the check_output inferface in python unittest framework to allow check a subset of outputs.
      
      * Use absolute offset lod in warpctc_op and related functors.
      
      * Refine the comments of warpctc_op.
      
      * The new python unittest supports checking a subset of the outputs, so revoke the previous change.
      
      * Rename the transform from LoDTensor to Tensor with shape [max_sequence_length, num_sequences, sequence_width] to PaddingSequenceFunctor.
      
      * Update to the newest codes.
      
      * Rename the PaddingSequenceFunctor to PaddingLoDTensorFunctor and remove the computation of dimensions out of the functos.
      b5fda272