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Merge pull request #38 from onnx/gs/onnx-1.2
add CI build
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.travis.yml

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dist: trusty
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language: python
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env:
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addons:
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apt:
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packages:
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- build-essential
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- curl
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- git
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python:
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- "3.6"
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install:
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- curl -L https://repo.continuum.io/miniconda/Miniconda3-4.3.21-Linux-x86_64.sh -o $HOME/miniconda.sh;
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PYTHON_VER="3.6m";
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- cd $HOME && bash miniconda.sh -b -p $HOME/miniconda
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- export PATH="$HOME/miniconda/bin:$PATH"
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- export LD_LIBRARY_PATH="$HOME/miniconda/lib:$LD_LIBRARY_PATH"
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- export LIBRARY_PATH="$HOME/miniconda/lib:$LIBRARY_PATH"
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- export CPATH="$HOME/miniconda/include:$CPATH"
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- export CPATH="$HOME/miniconda/include/python$PYTHON_VER:$CPATH"
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- ls $HOME/miniconda/include/python$PYTHON_VER
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- export PATH="$PATH:$PWD/build/bin"
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- export LD_LIBRARY_PATH="$LD_LIBRARY_PATH$PWD/build/lib"
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- printenv
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- conda config --set always_yes yes --set changeps1 no
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- conda install -c conda-forge protobuf numpy
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- cd $TRAVIS_BUILD_DIR && pip install onnx pytest pytest-cov pytest-runner graphviz tensorflow
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- conda install -c caffe2 caffe2
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- cd $TRAVIS_BUILD_DIR && export PYTHONPATH=pwd
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script:
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- python -m pytest --cov=tf2onnx --cov-report=term --cov-report=html --cov-report=xml tests

README.md

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Tf2onnx is in its early development. Mileage will vary since TensorFlow supports ~4 times the operations that the current ONNX version supports. But standard models seem to be using mostly ops that ONNX does support.
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| Linux |
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|-------|
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| [![Build Status](https://travis-ci.org/tensorflow-onnx/tensorflow-onnx.svg?branch=master)](https://travis-ci.org/onnx/tensorflow-onnx) |
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# Status
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Basic net and conv nets should work. A list of models that pass tests can be found [here](tests/run_pretrained_models.yaml)
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