1. 02 12月, 2022 1 次提交
    • J
      [Eager] Optimize Grad by prune useless branch (#47827) · d1e93be1
      Jiabin Yang 提交于
      * [Eager] Fix paddle.grad interface
      
      * [Eager] Support minimum SubGraph for GeneralGrad
      
      * Add needed_nodes to prune grad graph more thoroughly
      
      * [Eager] Add grad_node_trans_mapping_ to record which grad_node has been transformed to AccumulationNode
      
      * [Eager] Fix paddle.grad interface
      
      * Polish code
      
      * remove potential_stop_node
      
      * Add endding_nodes to enhance genSugraph logic
      
      * clear endding_nodes_
      
      * polish code
      
      * rename endding_nodes to endding_nades_
      
      * Refactor grad interface
      
      * Add register_hook case to fix coverage-ci
      
      * Fix code format
      
      * Refactor general_grad
      
      * Add more code comments
      
      * call clear directly to release GradSlotMeta
      
      * fix a mistake
      
      * fix matmul/ multiply kernel logic and optional input in yaml, fill zeros logic and so on.
      
      * fix batch_norm_double_grad yaml optional config
      
      * fix tanh_triple_grad yaml and kernels
      
      * fix MultiplyTripleGradKernel optional logic
      
      * fix merge mistake
      
      * fix compile error
      
      * remove legacy attr for bn
      
      * polish code
      
      * fix some kernel
      
      * merge develop
      
      * fix error
      
      * remote log
      
      * fix kernel with full like
      
      * hide value log behind
      
      * hide value log behind
      
      * fix matmul_triple grad
      Co-authored-by: NWeilong Wu <veyron_wu@163.com>
      d1e93be1
  2. 01 12月, 2022 1 次提交
  3. 30 11月, 2022 1 次提交
  4. 29 11月, 2022 1 次提交
  5. 28 11月, 2022 2 次提交
  6. 25 11月, 2022 1 次提交
  7. 24 11月, 2022 1 次提交
    • H
      [Phi Support CuDNN] Support ALL CuDNN (#47865) · 1623f1b4
      HongyuJia 提交于
      * support default use_gpudnn=True
      
      * fully support cudnn in phi
      
      * add header file
      
      * add white_list, verify accuracy
      
      * phi support all cudnn
      
      * opt affine_grad
      
      * try different arches of pretrained_model
      
      * try different arches of pretrained_model
      
      * add debug string
      
      * debug eager_method
      
      * add debug string, pass all local ctest
      
      * polish all debug code
      
      * delete use_cudnn relevant code autogen
      
      * fix depthwise_conv2d
      
      * Share all other members of Tensor except use_cudnn
      
      * polish codes according to review opinion
      
      * polish codes according to review opinion, fix bug
      
      * polish codes according to review opinion, opt performance
      
      * polish codes according to review opinion, fix pooling.py
      1623f1b4
  8. 17 11月, 2022 2 次提交
  9. 16 11月, 2022 1 次提交
  10. 11 11月, 2022 1 次提交
  11. 10 11月, 2022 2 次提交
  12. 09 11月, 2022 1 次提交
  13. 08 11月, 2022 2 次提交
  14. 04 11月, 2022 1 次提交
  15. 02 11月, 2022 2 次提交
  16. 01 11月, 2022 3 次提交
  17. 31 10月, 2022 1 次提交
  18. 28 10月, 2022 2 次提交
  19. 24 10月, 2022 1 次提交
  20. 21 10月, 2022 1 次提交
  21. 19 10月, 2022 1 次提交
  22. 12 10月, 2022 1 次提交
  23. 10 10月, 2022 1 次提交
    • Y
      [PHI]Add RNN yaml (#46812) · ab60fd8b
      YuanRisheng 提交于
      * add yaml entry for rnn and rrnn_grad, move infershape function for rnn_grad to phi infer meta
      
      * WIP: move rnn kernrl to phi
      
      * Change the code generation to avoid converting from intializer list to tuple of heterogeneous types.
      This is only triggered when an api has intermediate outputs, and the result of the outputs are of heterogeneous types.
      
      * fix the bug that when none in a vector of tensors requires gradient, the conversion to InferShapeContext to InferMetaContext (a.k.a. BuildInferMetaContext) produces errorous results.
      
      * fix ci bugs
      
      * fix ci bugs
      
      * fix ci bugs
      
      * modify code according comment
      Co-authored-by: Nchenfeiyu <chenfeiyu@baidu.com>
      ab60fd8b
  24. 19 9月, 2022 2 次提交
  25. 14 9月, 2022 3 次提交
  26. 13 9月, 2022 3 次提交
  27. 09 9月, 2022 1 次提交