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  23. 26 Nov, 2019 1 commit
  25. 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
  27. 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
  29. 10 Oct, 2019 2 commits
  31. 27 Sep, 2019 1 commit
  33. 24 Sep, 2019 1 commit
  35. 23 Sep, 2019 2 commits
  37. 20 Sep, 2019 1 commit
  39. 17 Sep, 2019 1 commit
  41. 11 Sep, 2019 1 commit
  43. 10 Sep, 2019 1 commit
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  47. 06 Sep, 2019 1 commit
  49. 05 Sep, 2019 1 commit
  51. 04 Sep, 2019 2 commits
  53. 29 Aug, 2019 1 commit
  55. 28 Aug, 2019 1 commit
  57. 26 Aug, 2019 1 commit
  59. 20 Aug, 2019 1 commit
  61. 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
  63. 14 Aug, 2019 2 commits