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pytorch/caffe2/python/onnx
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Junjie Bai 84427d26db Add aten_op to caffe2 onnx (python) backend 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10579

Reviewed By: houseroad

Differential Revision: D9357837

fbshipit-source-id: 2cc6fedbaf088df7e11b52a91dfe3b8f0d7fd599
2018-08-16 00:39:30 -07:00
..
bin Remove Apache headers from source. 2018-03-27 13:10:18 -07:00
tests Pass shape infos to ONNX -> Caffe2 C++ conversion backend (#9870) 2018-07-26 12:00:32 -07:00
__init__.py Move onnx-caffe2 inside caffe2 (#1921) 2018-02-20 13:56:52 -08:00
backend_cpp_rep.py Remove Apache headers from source. 2018-03-27 13:10:18 -07:00
backend_rep.py Disallow using the OOP api workspace as context managers (#6456) 2018-04-09 22:13:54 -07:00
backend.py Add aten_op to caffe2 onnx (python) backend 2018-08-16 00:39:30 -07:00
error.py Remove Apache headers from source. 2018-03-27 13:10:18 -07:00
frontend.py Bump up the C2 onnx frontend opset to 8 (#9006) 2018-06-29 11:56:11 -07:00
helper.py [Caffe2] Scoped dummy name generator (#6458) 2018-04-16 11:58:02 -07:00
onnxifi.py ONNXIFI transform (#9569) 2018-07-20 15:09:59 -07:00
ONNXOpCoverage.md Update the ONNX op coverage in C2 2018-06-29 17:25:19 -07:00
README.md Add README and ONNXOpCoverage doc back (#2102) 2018-03-01 17:05:25 -08:00
test_onnxifi.py ONNXIFI transform (#9569) 2018-07-20 15:09:59 -07:00
workspace.py Disallow using the OOP api workspace as context managers (#6456) 2018-04-09 22:13:54 -07:00

README.md

Caffe2 implementation of Open Neural Network Exchange (ONNX)

Usage

Installation

onnx-caffe2 is installed as a part of Caffe2. Please follow the instructions to install Caffe2.

Folder Structure

  • ./: the main folder that all code lies under
    • frontend.py: translate from caffe2 model to onnx model
    • backend.py: execution engine that runs onnx on caffe2
  • tests/: test files

Testing

onnx-caffe2 uses pytest as test driver. In order to run tests, first you need to install pytest:

pip install pytest-cov

After installing pytest, do

pytest

to run tests.

Testing coverage issues/status: https://github.com/caffe2/caffe2/blob/master/caffe2/python/onnx/ONNXOpCoverage.md

Development

During development it's convenient to install caffe2 in development mode:

cd /path/to/caffe2
pip install -e caffe2/

License

MIT License