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program:mgbc-snap (v1.0.0)
License: BSD 3-clause (code) and CC BY-SA 4.0 (data)
Creation date: 2018-10-25
Source: GitHub
cID: b0ac08fe1d3c2615:b7d96f5078dd48fd

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Description  

This portable workflow is our attempt to provide a common CLI with Python JSON API and a JSON meta description to automatically detect or install required components (models, data sets, libraries, frameworks, tools), and then build, run, validate, benchmark and auto-tune the associated method (program) across diverse models, datasets, compilers, platforms and environments. Our on-going project is to make the onboarding process as simple as possible via this platform. Please check this CK white paper and don't hesitate to contact us if you have suggestions or feedback!
  • Automation framework: CK
  • Development repository: ck-graph-analytics
  • Source: GitHub
  • Available command lines:
    • ck run program:mgbc-snap --cmd_key=default (META)
    • ck run program:mgbc-snap --cmd_key=test (META)
  • Support for host OS: any
  • Support for target OS: any
  • Tags: graph
  • How to get the stable version via the client:
    pip install cbench
    cb download program:mgbc-snap --version=1.0.0 --all
    ck run program:mgbc-snap
  • How to get the development version:
    pip install ck
    ck pull repo:ck-graph-analytics
    ck run program:mgbc-snap

  • CLI and Python API: module:program
  • Dependencies    

    ReadMe  

    Pre-requisites

    Python 2

    Misc

    # pip2 install enum34 mock pillow
    # pip2 install wheel absl-py
    

    SciPy

    # apt install liblapack-dev libatlas-dev
    # pip2 install scipy
    

    Install via CK

    TensorFlow

    $ ck install package:lib-tensorflow-1.4.0-src-{cpu,cuda}{,-xla}
    

    TensorFlow models

    $ ck install package:tensorflowmodel-alexnet-py
    $ ck install package:tensorflowmodel-squeezenet-py
    $ ck install package:tensorflowmodel-googlenet-py
    $ ck install package:tensorflowmodel-mobilenet-v1-1.0-224-py
    $ ck show env --tags=tensorflowmodel
    Env UID:         Target OS: Bits: Name:                                                   Version: Tags:
    
    ef7343498dbec627   linux-64    64 TensorFlow python model and weights (squeezenet)        ImageNet 64bits,host-os-linux-64,python,squeezenet,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights
    dede2b537d476299   linux-64    64 TensorFlow python model and weights (mobilenet-1.0-224) ImageNet 64bits,host-os-linux-64,mobilenet,mobilenet-v1,mobilenet-v1-1.0-224,python,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights
    73619b7df1e2488e   linux-64    64 TensorFlow python model and weights (googlenet)         ImageNet 64bits,googlenet,host-os-linux-64,python,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights
    4dd098ad717db21d   linux-64    64 TensorFlow python model and weights (alexnet)           ImageNet 64bits,alexnet,host-os-linux-64,python,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights
    

    ImageNet dataset

    $ ck install package:imagenet-2012-val-min
    $ ck install package:imagenet-2012-aux
    

    Benchmark

    $ ck list local:experiment:*
    $ cd `ck find program:classification-tensorflow`
    $ python benchmark.nvidia-gtx1080.py
    

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