luyifanlu / HashingDeepLearning

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SLIDE

The SLIDE package contains the source code for reproducing the main experiments in this paper.

Dataset

The Datasets can be downloaded in Amazon-670K.

Tensorflow Baselines

We suggest directly get Tensorflow docker image to install [Tensorflow-GPU] (https://www.tensorflow.org/install/docker). For Tensorflow-CPU compiled with AVX2, we recommend using this precompiled build.

config.py controls the parameters of Tensorflow training like learning rate. example_full_softmax.py, example_sampled_softmax.py are example files for Amazon-670K dataset with full softmax and sampled softmax respectively.

Run

python python_examples/example_full_softmax.py python python_examples/example_sampled_softmax.py

Running SLIDE

Firstly, CNPY package needs to be installed.

Additionally, Transparent Huge Pages must be enabled. SLIDE requires approximately 900 2MB pages, and 10 1GB pages. (Instructions)

Run

make

./runme Config_amz.csv

Note that Makefile needs to be modified based on the CNPY path. Also the trainData, testData, logFile in Config_amz.csv needs to be changed accordingly too.

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License:MIT License


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