TF: GPT-J compatible with XLA generation #17986
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Related issue: #17935 |
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The documentation is not available anymore as the PR was closed or merged. |
patrickvonplaten
approved these changes
Jul 4, 2022
viclzhu
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Jul 18, 2022
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What does this PR do?
This PR modifies TF GPT-J so as to be compatible with XLA generation. It borrows the new code from FLAX -- in essence, instead of computing the embedded positions (
sincos) at each call, given the size of the sequence (which could be obtained from the size of the past), now pre-computes the embedded positions and gathers them given theposition_ids.@tooslow, due to the size of the model. I've reworked the tests BEFORE touching GPT-J code, to test all needed features correctly. All but the XLA test were passing before GPT-J was changed, and all tests pass after the changes. We still have two XLA tests being run in CI frequently (test_xla_generate_fastandtest_xla_generate_slow), as well as a couple of generic generate tests -- they just don't use the trained model weights.