1. 16 Dec, 2019 1 commit
  2. 15 Dec, 2019 1 commit
  3. 14 Dec, 2019 2 commits
  4. 03 Dec, 2019 1 commit
  5. 26 Nov, 2019 1 commit
  6. 25 Nov, 2019 1 commit
    • Sai Ganesh Bandiatmakuri's avatar
      Inject enable_runtime_flags into benchmarks. · bcce419a
      Sai Ganesh Bandiatmakuri authored
      This will help general debugging by enabling custom execution with  --benchmark_method_steps.
      
      E.g --benchmark_method_steps=train_steps=7 will run the benchmark for only 7 steps without modifying benchmark code.
      
      PiperOrigin-RevId: 282396875
      bcce419a
  7. 16 Oct, 2019 1 commit
    • Reed Wanderman-Milne's avatar
      Add support for the tf.keras.mixed_precision API in NCF · cb913691
      Reed Wanderman-Milne authored
      To test, I did 50 fp32 runs and 50 fp16 runs. I used the following command:
      
      python ncf_keras_main.py --dataset=ml-20m --num_gpus=1 --train_epochs=10 --clean --batch_size=99000 --learning_rate=0.00382059 --beta1=0.783529 --beta2=0.909003 --epsilon=1.45439e-7 --layers=256,256,128,64 --num_factors=64 --hr_threshold=0.635 --ml_perf --nouse_synthetic_data --data_dir ~/ncf_data_dir_python3 --model_dir ~/tmp_model_dir --keras_use_ctl
      
      For the fp16 runs, I added --dtype=fp16. The average hit-rate for both fp16 and fp32 was 0.6365. I also did 50 runs with the mixed precision graph rewrite, and the average hit-rate was 0.6363. The difference is likely due to noise.
      
      PiperOrigin-RevId: 275059871
      cb913691
  8. 10 Oct, 2019 2 commits
  9. 27 Sep, 2019 1 commit
  10. 24 Sep, 2019 1 commit
  11. 23 Sep, 2019 2 commits
  12. 20 Sep, 2019 1 commit
  13. 17 Sep, 2019 1 commit
  14. 11 Sep, 2019 1 commit
  15. 10 Sep, 2019 1 commit
  16. 09 Sep, 2019 2 commits
  17. 06 Sep, 2019 1 commit
  18. 05 Sep, 2019 1 commit
  19. 04 Sep, 2019 2 commits
  20. 29 Aug, 2019 1 commit
  21. 28 Aug, 2019 1 commit
  22. 26 Aug, 2019 1 commit
  23. 20 Aug, 2019 1 commit
  24. 19 Aug, 2019 2 commits
    • Reed Wanderman-Milne's avatar
      Do not expose --max_train_steps in models that do not use it. · 824ff2d6
      Reed Wanderman-Milne authored
      Only the V1 resnet model uses --max_train_steps. This unexposes the flag in the keras_application_models, mnist, keras resnet, CTL resnet Models. Before this change, such models allowed the flag to be specified, but ignored it.
      
      I also removed the "max_train" argument from the run_synthetic function, since this only had any meaning for the V1 resnet model. Instead, the V1 resnet model now directly passes --max_train_steps=1 to run_synthetic.
      
      PiperOrigin-RevId: 264269836
      824ff2d6
    • Toby Boyd's avatar
      Increase max hr@10 to cover the rare >.640 · 725f65b6
      Toby Boyd authored
      725f65b6
  25. 14 Aug, 2019 4 commits
  26. 13 Aug, 2019 3 commits
  27. 12 Aug, 2019 1 commit
    • Hongjun Choi's avatar
      Merged commit includes the following changes: (#7430) · 03b4a0af
      Hongjun Choi authored
      262988559  by A. Unique TensorFlower<gardener@tensorflow.org>:
      
          Enable NCF TF 2.0 model to run on TPUStrategy.
      
      --
      262971756  by A. Unique TensorFlower<gardener@tensorflow.org>:
      
          Internal change
      
      262967691  by hongkuny<hongkuny@google.com>:
      
          Internal
      
      --
      
      PiperOrigin-RevId: 262988559
      03b4a0af
  28. 09 Aug, 2019 2 commits