1. 08 5月, 2019 1 次提交
  2. 12 12月, 2018 1 次提交
  3. 16 11月, 2018 1 次提交
  4. 15 11月, 2018 1 次提交
    • S
      add mkldnn prop_kind phase for inference-only case to pooling and activations (#14278) · 8a1eeec5
      Sylwester Fraczek 提交于
      * add is_test to pooling and activations
      
      add prop_kind support for layers activation. conv and pooling
      
      add a pass that sets is_test to true
      
      add transpiler version of is_test pass
      
      test=develop
      
      * patch test and pass
      
      test=develop
      
      * add pass to analyzer.h
      
      test=develop
      
      * add is_test attr description & pass only on mkldnn
      
      in:
      activation_op.cc
      batch_norm_op.cc
      conv_op.cc
      dropout_op.cc
      lrn_op.cc
      pool_op.cc
      sequence_pool_op.cc
      softmax_op.cc
      
      * fix is_test handling for activation pool and conv
      
      * change description of is_test for all layers again
      
      * remove GetAttr(use_mkldnn) from pass
      
      * rename correct_mkldnn_test_phase to is_test
      
      and remove dependency on MKLDNN
      test=develop
      
      * review fix magic number
      
      * two if(..)s into one
      
      * Check is_test once and pass mkldnn forward prop kind
      
      * dereference shared_ptr with * (without get())
      
      test=develop
      
      * add is_test_pass back
      
      test=develop
      8a1eeec5
  5. 13 11月, 2018 1 次提交
  6. 07 6月, 2018 1 次提交
    • M
      Mkldnn layout (#11040) · 3ff9ba0e
      mozga-intel 提交于
      * Add MKLDNN layout support in Paddle
      
      Add MKLDNN layout in Paddle so that MKLDNN friendly memory layout
      can be used in MKLDNN enabled OP kernel. Before this commit, NCHW
      is hardcode to be used in all MKLDNN op kernels. As a result,
      non-optimized execution path is selected in MKLDNN primitive which
      bring worse performance.
      Besides framework change, three MKLDNN OP kernels were updated
      for using new MKLDNN layout. They are conv/pool2d/batch_norm.
      Other MKLDNN OP kernels need be also updated in similar way to
      achieve best performance.
      
      * Add MKLDNN layout support in activation OP
      
      * Don't populate layout from input to output when kMKLDNN in
      
      * Refine pool mkldnn op kernel
      
      * MKLDNN layout
      
      * Remove the inferitance from tensor file
      
      * MKLDNN layout: refactoring
      
      * Remove additional #define to register new operator
      
      * Prepare mkldnn tests to work with layout
      3ff9ba0e
  7. 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
  8. 19 4月, 2018 1 次提交
  9. 17 4月, 2018 1 次提交
  10. 12 4月, 2018 1 次提交
  11. 30 3月, 2018 1 次提交
  12. 22 3月, 2018 1 次提交
  13. 21 3月, 2018 1 次提交
  14. 19 3月, 2018 3 次提交
  15. 15 3月, 2018 1 次提交
  16. 12 2月, 2018 1 次提交
  17. 10 2月, 2018 2 次提交
  18. 26 12月, 2017 1 次提交
  19. 20 12月, 2017 1 次提交
  20. 12 12月, 2017 1 次提交
    • Q
      Refine device context (#6433) · 61ec0b95
      QI JUN 提交于
      There are mainly following fixes:
      
      - take `DeviceContext` as the template parameter of math functors and OpKernel instead of `Place`
      - remove `eigen_device` interface in base class  `DeviceContext`
      - remove `GetEigenDevice` interface in `ExecutionContext` and base class `DeviceContext`
      - remove unused `platform::EigenDeviceConverter`
      - rename `REGISTER_OP_GPU_KERNEL` to `REGISTER_OP_CUDA_KERNEL`
      - rename `USE_GPU_ONLY_OP` to `USE_CUDA_ONLY_OP`
      61ec0b95
  21. 06 12月, 2017 1 次提交
  22. 04 11月, 2017 1 次提交
  23. 26 10月, 2017 1 次提交