1. 24 5月, 2019 3 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
    • S
      Conv concat relu quantization (#17466) · 5b2a3c4b
      Sylwester Fraczek 提交于
      * add conv_concat_relu fuse
      
      test=develop
      
      * add test code
      
      test=develop
      
      * added missing include with unordered_map
      
      test=develop
      
      * review fixes for wojtuss
      
      test=develop
      
      * remove 'should (not) be fused' comment statements
      
      one of them was invalid anyway
      
      test=develop
      5b2a3c4b
    • S
      fix quantize_squash_pass segfault when no tensor linked to Bias (#17292) · bccb0ba4
      Sylwester Fraczek 提交于
      * fix quantize_squash_pass segfault when there is no tensor linked do Bias input
      
      test=develop
      
      * add googlenet test
      
      test=develop
      
      * fix concat CreateKey not using input format
      
      test=develop
      bccb0ba4
  2. 22 5月, 2019 1 次提交
    • G
      Enable the convolution/relu6(bounded_relu) fusion for FP32 on Intel platform. (#17130) · 2281ebf0
      guomingz 提交于
      * Relu6 is the bottleneck op for Mobilenet-v2. As the mkldnn supports the conv/relu6 fusion, we implement it fusion via cpass way. Due to the int8 enabling for this fusion will be supported in MKLDNN v0.20, so this PR is focused on the fp32 optimization.
      
      Below table shows the benchmark(FPS) which measured on skx-8180(28 cores)
      Batch size | with fusion | without fusion
      -- | -- | --
      1 | 214.7 | 53.4
      50 | 1219.727 | 137.280
      
      test=develop
      
      * Fix the format issue
      
      test=develop
      
      * Add the missing nolint comments.
      
      test=develop
      
      * Fix the typos.
      
      test=develop
      
      * Register the conv_brelu_mkldnn_fuse_pass for the MKLDNN engine.
      
      test=develop
      
      * Adjust the indentation.
      
      test=develop
      
      * Add the test_conv_brelu_mkldnn_fuse_pass case.
      
      test=develop
      
      * Slightly update the code per Baidu comments.
      Let the parameter definition embedded into the code.
      That's will make the code easy to understand.
      
      test=develop
      2281ebf0
  3. 16 5月, 2019 1 次提交
  4. 28 3月, 2019 1 次提交
    • C
      Fix the interface of Pass::Apply (#16484) · ed61d67c
      chengduo 提交于
      * modify the interface of Pass::Allay
      test=develop
      
      * Polish code
      test=develop
      
      * Fix Travis CI
      test=develop
      
      * fix Pass::Apply interface
      test=develop
      
      * Fix Travis CI
      test=develop
      ed61d67c
  5. 25 3月, 2019 1 次提交
  6. 21 3月, 2019 1 次提交
  7. 26 2月, 2019 1 次提交
  8. 25 2月, 2019 1 次提交
  9. 22 2月, 2019 1 次提交
  10. 21 2月, 2019 1 次提交
  11. 29 1月, 2019 1 次提交