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fix typos (#3684)

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2025-09-01 17:50:17 +08:00
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docs/features/graph_optimization.md
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@@ -44,7 +44,7 @@ CudaGrpah can be enabled by setting `--use-cudagraph` or `--graph-optimization-c
The `graph_opt_level` parameter within `--graph-optimization-config` is used to configure the graph optimization level, with the following available options:
+ `0`: Use Dynamic compute graph, default to 0
+ `1`: Use Static compute graph, during the initialization phase, Paddle API will be used to convert the dynamic image into a static image
+ `2`: Base on Static compute graph, use the complier(CINN, Compiler Infrastructure for Neural Networks) of Paddle to compile and optimize
+ `2`: Base on Static compute graph, use the compiler(CINN, Compiler Infrastructure for Neural Networks) of Paddle to compile and optimize
In general, static graphs have lower Kernel Launch overhead than dynamic graphs, and it is recommended to use static graphs.
For adapted models, FastDeploy's CudaGraph *can support both dynamic and static graphs* simultaneously.