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FIXES https://github.com/pytorch/pytorch/issues/144775 frfr See details on the problem: https://github.com/pytorch/pytorch/issues/144775#issuecomment-2611699385 We fixed some silent incorrectness, but it results in less nodes DCE'd. The benchmark iteration loop had some dead code which could contain side effect ops that aren't safe to DCE. The regression is expected. This PR removes the compile time benchmarking of the dead code, which should reduce the noise of the benchmark and aligns with the benchmarking used by performance tests New benchmark results: ```python dev,name,batch_size,accuracy,calls_captured,unique_graphs,graph_breaks,unique_graph_breaks,autograd_captures,autograd_compiles,cudagraph_skips,compilation_latency cuda,BartForConditionalGeneration,1,pass,897,1,0,0,0,0,0,39.322364 # after https://github.com/pytorch/pytorch/pull/144319 cuda,BartForConditionalGeneration,1,pass,897,1,0,0,0,0,0,38.972257 # before https://github.com/pytorch/pytorch/pull/144319 ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/145590 Approved by: https://github.com/jansel ghstack dependencies: #145447
4 lines
99 B
YAML
4 lines
99 B
YAML
# removing this file prevents the TimmRunner from dynamically skipping models
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skip:
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all:
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- ~
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