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[JIT] Functional Graph Pass (#33020)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/33020 This is a pass to create functional blocks. The other PRs in the stack help avoid some of the limitations that are are often found in graphs. It's possible that this would work well with a graph that is frozen. Follow up work items that will help this pass: - We don't currently have any capacity in alias analysis to tell whether a Value that came from the wildcard set "re-escapes" back into the wildcard set. - More comments on the semantics of the graph and correctness conditions - We could consider using dynamic dag if the perf of this is a limitation. - potential make Functional Graphs Functional Blocks instead, so that we do not repeatedly copy constants, also to make IR read easier. Test Plan: Imported from OSS Differential Revision: D20603188 Pulled By: eellison fbshipit-source-id: 6822a6e65f4cc2676f8f6445fe8aa1cb858ebeeb
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@ -399,6 +399,7 @@ if (NOT INTERN_BUILD_MOBILE OR NOT BUILD_CAFFE2_MOBILE)
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${TORCH_SRC_DIR}/csrc/jit/passes/constant_pooling.cpp
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${TORCH_SRC_DIR}/csrc/jit/passes/common_subexpression_elimination.cpp
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${TORCH_SRC_DIR}/csrc/jit/passes/create_autodiff_subgraphs.cpp
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${TORCH_SRC_DIR}/csrc/jit/passes/create_functional_graphs.cpp
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${TORCH_SRC_DIR}/csrc/jit/passes/inline_autodiff_subgraphs.cpp
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${TORCH_SRC_DIR}/csrc/jit/passes/insert_guards.cpp
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${TORCH_SRC_DIR}/csrc/jit/passes/inliner.cpp
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