mindstudio_profiler_data_check

To validate MindStudio profiler data, you can pre-check data integrity, collection status, and essential artifacts to ensure the dataset is ready for downstream diagnostics and analysis.

You can trigger offline parsing by executing scripts/offline_parse_pytorch.py or scripts/offline_parse_mindspore.py to convert raw framework profiler outputs into analysis-ready results.

Yes, the profiler data check supports both single-card and multi-card scenarios, and applies to framework profilers like _ascend_pt and _ascend_ms as well as msprof PROF_ directories.

The best way to verify Stop state and parse-status is to run pre-checks that enforce type binding and validate collection completion to guarantee downstream tooling can execute properly.

MindStudio profiler data fails downstream analysis when required outputs are missing, the Stop state is incomplete, or the parse-status verification fails the pre-check data integrity validation.

Yes, you need MindSpore or torch_npu installed in your environment as dependencies to properly validate and parse the Ascend framework profiler data for analysis readiness.