Change specialization rules in GraphExecutors#10977
Change specialization rules in GraphExecutors#10977apaszke wants to merge 3 commits intopytorch:masterfrom
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zdevito
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This looks good! I have minor comments below.
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This commit fixes a number of issues connected to caching differentiability status of graphs inside graph executors, and changes the rules for optimization of differentiable subgraphs. Previously every one of those was instantiated as a separate graph executor, but now they are simply heavier-optimized graph regions, and graph executors are only instantiated for their backward.
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apaszke has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.
Summary: **Review last commit only.** Stacked on top of pytorch#10949. This commit fixes a number of issues connected to caching differentiability status of graphs inside graph executors, and changes the rules for optimization of differentiable subgraphs. Previously every one of those was instantiated as a separate graph executor, but now they are simply heavier-optimized graph regions, and graph executors are only instantiated for their backward. zdevito Pull Request resolved: pytorch#10977 Differential Revision: D9600626 Pulled By: apaszke fbshipit-source-id: dad09a0f586e396afbd5406319c1cd54fbb8a3d3
Review last commit only. Stacked on top of #10949.
This commit fixes a number of issues connected to caching
differentiability status of graphs inside graph executors,
and changes the rules for optimization of differentiable subgraphs.
Previously every one of those was instantiated as a separate graph
executor, but now they are simply heavier-optimized graph regions,
and graph executors are only instantiated for their backward.
@zdevito