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apache / tvm-vta / a83641356882555e96b077f453737271c1f759b8
commita83641356882555e96b077f453737271c1f759b8[log] [tgz]
authorRamana Radhakrishnan <ramana.radhakrishnan@arm.com>Wed Jul 10 16:59:01 2019 +0100
committerTianqi Chen <tqchen@users.noreply.github.com>Wed Jul 10 08:59:01 2019 -0700
treeae9ba6c178564e0fe49958a8e14579bbea9a36e2
parentb01a87b27c4c8765488d441e401e82ac23a6baa3 [diff]
Fix pylint issue in vta/python/vta/top/graphpack.py (#3519)

This appears in linting using the docker scripts. I'm not sure
why this isn't failing in the standard CI for TVM and it might
be that the docker images haven't been updated in the CI system.

python3 -m pylint vta/python/vta --rcfile=/workspace/tests/lint/pylintrc
Using config file /workspace/tests/lint/pylintrc
************* Module vta.top.graphpack
C:131, 4: Missing method docstring (missing-docstring)
1 file changed
tree: ae9ba6c178564e0fe49958a8e14579bbea9a36e2
  1. apps/
  2. config/
  3. hardware/
  4. include/
  5. python/
  6. scripts/
  7. src/
  8. tests/
  9. tutorials/
  10. README.md
README.md

VTA: Open, Modular, Deep Learning Accelerator Stack

VTA (versatile tensor accelerator) is an open-source deep learning accelerator complemented with an end-to-end TVM-based compiler stack.

The key features of VTA include:

  • Generic, modular, open-source hardware
    • Streamlined workflow to deploy to FPGAs.
    • Simulator support to prototype compilation passes on regular workstations.
  • Driver and JIT runtime for both simulator and FPGA hardware back-end.
  • End-to-end TVM stack integration
    • Direct optimization and deployment of models from deep learning frameworks via TVM.
    • Customized and extensible TVM compiler back-end.
    • Flexible RPC support to ease deployment, and program FPGAs with the convenience of Python.

Learn more about VTA here.