--oo_level

Applicability

Description

Extended parameter for debugging. It cannot be used in commercial products and will be released as a formal function in later versions.

Multi-level optimization options for graph build include subgraph optimization, entire graph optimization, and static shape model offloading.

Static shape model offloading: In this approach, the input and output shapes of all operators in a static shape model can be determined at build time, allowing for model-level memory orchestration and operator tiling computation to be completed on the host. These computations are then batched and sent to the device stream when the model is loaded, but they are not executed immediately. Instead, the execution of all tasks within the model is triggered by deliver model execution tasks.

See Also

None

Argument

• O1: Disables all graph fusion and UB fusion passes, and performs only optimizations related to static offloading, such as InferShape (output tensor shape inference), constant folding, dead-edge elimination, and other optimizations.

  The Atlas 350 Accelerator Card does not support UB fusion. Only the graph fusion pass is disabled.

• O3 (default): Enables all optimizations.

Suggestions and Benefits

None

Example

--oo_level=O1

Restrictions

If the value is O1, all graph fusion and UB fusion passes are disabled, and only passes related to static offloading are enabled. However, the graph fusion passes in the following files are enabled by default because function problems may occur if they are disabled:

All graph fusion passes under the ExceptionalPassOfO1Level field in the ${INSTALL_DIR}/x86_64-linux/lib64/plugin/opskernel/fusion_pass/config/fusion_config.json file

Replace ${INSTALL_DIR} with the CANN component directory. For example, if the installation is performed by the root user, the default file storage path is /usr/local/Ascend/cann.