@@ -6,13 +6,13 @@ and make the various optimization features be pluggable and co-exist in a pipeli
We borrowed some concepts from LLVM, such as
-[Pass](./pass.h)es to implement optimization that traverse the inference program,
-[DataFlowGraph](./data_flow_graph.h) to represent the data flow graph built from a program,
-[PassManager](./pass_manager.h) to manage a sequence of `Pass`es over a graph.
-[Pass](../../framework/ir/pass.h)es to implement optimization that traverse the inference program,
-[Graph](../../framework/ir/graph.h) to represent the data flow graph built from a program,
-[PassManager](./ir_pass_manager.h) to manage a sequence of `Pass`es over a graph.
There are some other basic concepts here
-[Node](./node.h), the node in a `DataFlowGraph`,
-[Node](../../framework/ir/node.h), the node in a `Graph`,
-`Function`, the Operator in Fluid,
-`Value`, the Variable in Fluid;
-[Argument](./argument.h), the argument that treat as the input and output of all `Pass`es in the pipeline,
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@@ -21,9 +21,9 @@ There are some other basic concepts here
The `inference/analysis` module make all the passes in a pipeline, and works in such way:
1. Build a `DataFlowGraph` from a Fluid inference ProgramDesc,
2. Call the middle passes one by one, the same `DataFlowGraph` is passed across all the passes,
3. Transform a new ProgramDesc from the modified `DataFlowGraph`.
1. Build a `Graph` from a Fluid inference ProgramDesc,
2. Call the middle passes one by one, the same `Graph` is passed across all the passes,
3. Transform a new ProgramDesc from the modified `Graph`.
The new optimization features can be added as an independent `Pass` and controlled by gflags,
each pass will generate unified debug information or visualization for better debugging.
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@@ -54,5 +54,5 @@ It can be used as a helper class that draws the modified graph after each pass.
There is some helper legacy/function/class for analysis.
-[dot.h](./dot.h) give a easy to use interface for generating `DOT` codes,
-[graph_traits.h](./graph_traits.h) contains the interfaces of the graph traversal algorithms, it uses `iterator`to make the algorithms easy to share across different passes,
there are some implementations in [data_flow_graph.cc](./data_flow_graph.cc) , such as BFS and DFS..
-[graph_traits.h](../../framework/ir/graph_traits.h) contains the interfaces of the graph traversal algorithms, it uses `iterator`to make the algorithms easy to share across different passes,
there are some implementations in [graph_helper.cc](../../framework/ir/graph_helper.cc) , such as BFS and DFS..
@@ -18,7 +18,7 @@ For reference, please examine the code of unit test enclosed in [analyzer_int8_i
* ### Create Analysis config
INT8 quantization is one of the optimizations in analysis config. More information about analysis config can be found [here](https://github.com/PaddlePaddle/FluidDoc/blob/develop/doc/fluid/advanced_usage/deploy/inference/native_infer_en.md#upgrade-performance-based-on-contribanalysisconfig-prerelease)
INT8 quantization is one of the optimizations in analysis config. More information about analysis config can be found [here](https://www.paddlepaddle.org.cn/documentation/docs/en/advanced_guide/inference_deployment/inference/native_infer_en.html#a-name-use-analysisconfig-to-manage-inference-configurations-use-analysisconfig-to-manage-inference-configurations-a)
