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suggest a numerical limit of 50MB for determining @slow (#8824)

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Stas Bekman
2020-11-27 13:04:54 -08:00
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1 changed files with 4 additions and 3 deletions
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@@ -909,9 +909,10 @@ pipelines), then we should run that test in the non-slow test suite. If it's foc
such as the documentation or the examples, then we should run these tests in the slow test suite. And then, to refine such as the documentation or the examples, then we should run these tests in the slow test suite. And then, to refine
this approach we should have exceptions: this approach we should have exceptions:
* All tests that need to download a heavy set of weights (e.g., model or tokenizer integration tests, pipeline * All tests that need to download a heavy set of weights or a dataset that is larger than ~50MB (e.g., model or
integration tests) should be set to slow. If you're adding a new model, you should create and upload to the hub a tokenizer integration tests, pipeline integration tests) should be set to slow. If you're adding a new model, you
tiny version of it (with random weights) for integration tests. This is discussed in the following paragraphs. should create and upload to the hub a tiny version of it (with random weights) for integration tests. This is
discussed in the following paragraphs.
* All tests that need to do a training not specifically optimized to be fast should be set to slow. * All tests that need to do a training not specifically optimized to be fast should be set to slow.
* We can introduce exceptions if some of these should-be-non-slow tests are excruciatingly slow, and set them to * We can introduce exceptions if some of these should-be-non-slow tests are excruciatingly slow, and set them to
``@slow``. Auto-modeling tests, which save and load large files to disk, are a good example of tests that are marked ``@slow``. Auto-modeling tests, which save and load large files to disk, are a good example of tests that are marked