eb5916741305236fe322e180281cc8d330ea7cc5,official/benchmark/ncf_keras_benchmark.py,NCFKerasAccuracy,benchmark_8_gpu_tf_data_ctl_fp16_mlperf_like,#NCFKerasAccuracy#,375

Before Change

    8 GPU FP16 using CTL
    self._setup()
    FLAGS.keras_use_ctl = True
    FLAGS.num_gpus = 8
    FLAGS.train_epochs = 17
    FLAGS.batch_size = 1048576
    FLAGS.eval_batch_size = 1048000
    FLAGS.learning_rate = 0.0045
    FLAGS.beta1 = 0.25
    FLAGS.beta2 = 0.5
    FLAGS.epsilon = 1e-8
    FLAGS.dtype = "fp16"
    FLAGS.loss_scale = 8192
    FLAGS.train_dataset_path = os.path.join(NCF_TF_DATA_1M_BATCH_DIR_NAME, "training_cycle_*/*")
    FLAGS.eval_dataset_path = os.path.join(NCF_TF_DATA_1M_BATCH_DIR_NAME, "eval_data/*")
    FLAGS.input_meta_data_path = os.path.join(NCF_TF_DATA_1M_BATCH_DIR_NAME, "meta_data.json")
    self._run_and_report_benchmark_mlperf_like()

  def benchmark_8_gpu_tf_data_ctl_fp16_graph_rewrite_mlperf_like(self):
    8 GPU FP16 graph rewrite using CTL.

After Change

  def benchmark_8_gpu_tf_data_ctl_fp16_mlperf_like(self):
    8 GPU FP16 using CTL.
    self._setup()
    self._set_8_gpu_defaults()
    FLAGS.keras_use_ctl = True
    FLAGS.dtype = "fp16"
    FLAGS.loss_scale = 8192
    self._run_and_report_benchmark_mlperf_like()

Instances