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After the binaries have been generated successfully, please take the failed command from the screenshot above and execute it in the root of your MXNet workspace. In this case, you would like to run ci/build.py --nvidiadocker --build --platform ubuntu_gpu /work/runtime_functions.sh unittest_ubuntu_python2_gpu . Please note the parameter --nvidiadocker in this example. This indicates that this test requires a GPU and is thus only executable on a Ubuntu machine with Nvidia-Docker and a GPU installed. The result of this execution should look like follows:

Tips and Tricks

Repeating test execution

In order to test a test for it's robustness against flakyness, you might want to repeat the execution multiple times. This can be achieved with the MXNET_TEST_COUNT environment variable. The execution would look like follows:

MXNET_TEST_COUNT=10000 nosetests --logging-level=DEBUG --verbose -s test_module.py:test_op3

Setting a fixed test seed

To reproduce a test failure caused by random data, you can use the MXNET_TEST_SEED environment variable. 

MXNET_TEST_SEED=2096230603 nosetests --logging-level=DEBUG --verbose -s test_module.py:test_op3

Troubleshooting

In case you run into any issues, please try the following steps:

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