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903ad90325
Summary: **Summary** There is often a need to create a Tensor when writing IR by hand for JIT optimisation pass unit tests. The only options for this today are real Tensor creation functions like `aten::ones`. Any test that uses these functions must also use the same default arguments as the Python/C++ API, which means that all of the tests have to be updated when the API is updated. This commit introduces a new primitive, `prim::MakeTestTensor` with schema `() -> Tensor` that should be used in unit tests instead of real Tensor creation functions. This new primitive has no public-facing API, so the maintenance burden is much lower. **Testing** This commit updates the alias analysis and DCE tests to use `prim::MakeTestTensor` instead of `aten::rand`, `aten::ones`, and `aten::zeros`. ``` $ ./bin/test_jit CUDA not available. Disabling CUDA and MultiCUDA tests Note: Google Test filter = *-*_CUDA:*_MultiCUDA [==========] Running 75 tests from 1 test case. [----------] Global test environment set-up. [----------] 75 tests from JitTest [ RUN ] JitTest.ADFormulas [ OK ] JitTest.ADFormulas (82 ms) [ RUN ] JitTest.Attributes [ OK ] JitTest.Attributes (0 ms) ... ... ... [ RUN ] JitTest.LiteInterpreterPrim [ OK ] JitTest.LiteInterpreterPrim (0 ms) [ RUN ] JitTest.LiteInterpreterLoadOrigJit [ OK ] JitTest.LiteInterpreterLoadOrigJit (2 ms) [----------] 75 tests from JitTest (150 ms total) [----------] Global test environment tear-down [==========] 75 tests from 1 test case ran. (150 ms total) [ PASSED ] 75 tests. ``` **Fixes** This pull request fixes https://github.com/pytorch/pytorch/issues/33500. Pull Request resolved: https://github.com/pytorch/pytorch/pull/34334 Differential Revision: D20296437 Pulled By: SplitInfinity fbshipit-source-id: df4e7b0881ae4913424e5a409bfa171a61c3e568 |
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| .. | ||
| api | ||
| common | ||
| dist_autograd | ||
| jit | ||
| rpc | ||
| tensorexpr | ||
| __init__.py | ||