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Benchmarks for DSSTNE

We ran the benchmark of DSSTNE using the Movielens data set. Training Parameter Specific

  • 27278 input/output dimensions
  • 3 Hidden Sigmoid layers with 1024 each
  • RMSProp learner
  • 256 Batchsize

Time taken to run one epoch is considered for performance comparison

DSSTNE

Use the Config at config.json. Follow the example and change the training command

train -i gl_input.nc -o gl_output.nc -d gl -c config.json -b 256 -e 20 -n gl_network.nc

TensorFlow

autoencoder.py

autoencoder.py -u 1024 -b 256 -i 1082 -v54 --vocab_size 27278 -l 3 -f /input/data/ml20m-all.remotcc