1. 12 8月, 2022 1 次提交
  2. 05 6月, 2022 1 次提交
    • S
      【code format check upgrade】 step2:yapf (#42944) · a072fca8
      Sing_chan 提交于
      * use yapf to format all python file
      
      * yapf exclude two unittests file for they rely on writing and reading file, and format will break them
      
      * disable diff_py_file because too many diff files cause command following failed
      a072fca8
  3. 13 5月, 2022 1 次提交
  4. 15 4月, 2021 1 次提交
    • J
      Update hapi to support AMP (#31417) · fabdb43c
      Jiaqi Liu 提交于
      * make hapi support amp, and add unittest
      
      * make unittest only support GPU
      
      * update parameters for amp in hapi.Model
      
      * update hapi.Model.prepare interface, and update unittest
      
      * fix test_model.py unittest bug
      
      * add grad clear in dygraph
      
      * use_fp16_guard defaults to True, which could avoid nan
      
      * add input check, and add internal doc link to low level api
      
      * update doc, and decrease the sample num of dataset to avoid timeout
      
      * make hapi amp param  support str 'O1' or 'O2'
      
      * resume calling , modify the code of the check part
      
      * upgrade the usage of Fleet API, and disable 'pure_fp16' param
      fabdb43c
  5. 16 9月, 2020 1 次提交
  6. 31 8月, 2020 1 次提交
    • Q
      Move hapi to python/paddle root dir. (#26442) · f7fb4c22
      qingqing01 提交于
      * Move hapi form paddle/incubate to paddle
      
      * Remove vision/datasets/utils.py and clean code
      
      * Add sample code for conll05
      
      * Print pull path when saving model
      
      * Fix sample code after paramter_list of SGD is changed to parameters
      
      * Fix bug in wmt16 datase
      f7fb4c22
  7. 11 5月, 2020 1 次提交
    • Q
      Add a high-level API with traning and inference into Paddle. (#24293) · 43625bda
      qingqing01 提交于
      * Merge hapi into Paddle
      
      Hapi is a high level API for training and inference.
      The main modules include Model, Loss, Metrics, Dataset.
      Also includes common modules and models in NLP and computer vision, such as BERT, ResNet.
      
      These modules are developed by:
      0YuanZhang0, guoshengCS heavengate, LielinJiang, qingqing01, xyzhou-puck huangjun12, wangxiao1021, zhangyang.
      43625bda