1. 13 6月, 2019 1 次提交
  2. 24 5月, 2019 1 次提交
    • M
      [MKL-DNN] Add Fully Connected Op for inference only(#15226) · 0c39b97b
      Michał Gallus 提交于
      * fuse mul and elementwise add to fc
      
      * Reimplement the FC forward operator
      
      * Fix FC MKLDNN integration by transposing weights
      
      * Add FC MKLDNN Pass
      
      test=develop
      
      * FC MKLDNN Pass: change memcpy to std::copy
      
      * Fix MKLDNN FC handling of mismatch input and weights dims
      
      * Lower tolerance for MKL-DNN in resnet50 test
      
      test=develop
      
      * Adjust FC to support MKLDNN Op placement
      
      test=develop
      
      * Adjust Placement Op to set use_mkldnn attribute for graph
      
      test=develop
      
      * MKLDNN FC: fix weights format so that gemm version is called
      
      test=develop
      
      * FC MKLDNN: Remove tolerance decrease from tester_helper
      
      * FC MKL-DNN: Refactor the code, change input reorder to weight reorder
      
      * MKL-DNN FC: Introduce operator caching
      
      test=develop
      
      * FC MKL-DNN: Fix the tensor type in ExpectedKernelType
      
      test=develop
      
      * FC MKL-DNN: fix style changes
      
      test=develop
      
      * FC MKL-DNN: fallback to native on non-supported dim sizes
      
      test=develop
      
      * FC MKLDNN: fix CMake paths
      
      test=develop
      
      * FC MKLDNN: Refine placement pass graph mkldnn attribute
      
      test=develop
      
      * Fix Transpiler error for fuse_conv_eltwise
      
      test=develop
      
      * Fix missing STL includes in files
      
      test=develop
      
      * FC MKL-DNN: Enable new output size computation
      
      Also, refine pass to comply with newest interface.
      test=develop
      
      * FC MKL-DNN: enable only when fc_mkldnn_pass is enabled
      
      * FC MKL-DNN: Allow Weights to use oi or io format
      
      * FC MKL-DNN: Adjust UT to work with correct dims
      
      test=develop
      
      * Enable MKL DEBUG for resnet50 analyzer
      
      test=develop
      
      * FC MKL-DNN: Improve Hashing function
      
      test=develop
      
      * FC MKL-DNN: Fix shape for fc weights in transpiler
      
      * FC MKL-DNN: Update input pointer in re-used fc primitive
      
      * Add log for not handling fc fuse for unsupported dims
      
      test=develop
      
      * FC MKL-DNN: Move transpose from pass to Op Kernel
      
      test=develop
      
      * FC MKL-DNN: Disable transpose in unit test
      
      test=develop
      
      * FC MKL-DNN: Remove fc_mkldnn_pass from default list
      
      * Correct Flag for fake data analyzer tests
      
      test=develop
      
      * FC MKL-DNN: Add comment about fc mkldnn pass disablement
      
      test=develop
      
      * FC MKL-DNN: Disable fc in int8 tests
      
      test=develop
      0c39b97b
  3. 30 4月, 2019 1 次提交
    • T
      fix bn fuse vardesc and add model saver (#17143) · 79ed1c76
      tensor-tang 提交于
      * fix bn fuse vardesc and add model saver
      
      test=develop
      
      * unify save model in test helper
      
      test=develop
      
      * fix mkdir on windows
      
      test=develop
      
      * remove magic number use bn bias var desc
      
      test=develop
      79ed1c76
  4. 15 4月, 2019 1 次提交
  5. 02 4月, 2019 1 次提交
  6. 07 1月, 2019 1 次提交
  7. 20 12月, 2018 1 次提交
  8. 23 11月, 2018 2 次提交
  9. 15 11月, 2018 1 次提交
    • Y
      Refine tester of TensorRT engine (#14390) · 9e6b1c5f
      Yiqun Liu 提交于
      * Refine the tester for MixedRTPredictor.
      test=develop
      
      * Enable the profiler in TensorRT engine.
      
      * Support the use of combined inference model in TensorRT unittest, and print the shape of feed targets.
      9e6b1c5f
  10. 14 11月, 2018 1 次提交
  11. 07 11月, 2018 1 次提交
  12. 06 11月, 2018 1 次提交
  13. 23 10月, 2018 1 次提交
  14. 19 10月, 2018 2 次提交
  15. 18 10月, 2018 1 次提交
  16. 17 10月, 2018 2 次提交
  17. 16 10月, 2018 1 次提交
  18. 09 10月, 2018 1 次提交
  19. 08 10月, 2018 1 次提交
  20. 28 9月, 2018 3 次提交
  21. 20 9月, 2018 1 次提交
  22. 14 9月, 2018 2 次提交
  23. 13 9月, 2018 1 次提交
  24. 12 9月, 2018 3 次提交