trt-perf-analysis

name

trt-perf-analysis

description

Validate and analyze TensorRT performance data from paired layer-info JSON and profile/latency JSON files. Use when asked to inspect TensorRT, TRT, torch-tensorrt, or ONNX-TensorRT perf reports, verify that layer/profile JSON files are valid and from the same model, infer basic model information, find likely fusion or latency optimization opportunities, and produce a concise Markdown performance report or structured JSON data.

TRT Perf Analysis

Workflow

Use scripts/run.sh on Unix-like systems or scripts\run.cmd on Windows for Python scripts. These wrappers do best-effort Python 3.8+ discovery; set SKILL_PYTHON to a Python executable to override discovery. Replace placeholders with platform-native paths.

1. Choose the input scope. Use one folder that directly contains layers_*.json and/or profile_*.json. Do not call the packager on a parent folder that only contains component subfolders. For model suites with separate encoder, transformer, decoder, VAE, or similar components, handle each component folder separately.

2. Infer model identity and components. Prefer an explicit model name from the user prompt and pass it with --model-name. Otherwise rely on the analyzer/packager to inspect likely config files, the input directory name, and layer/profile filenames. Keep the name empty when confidence is low. Serialized JSON records the inferred model identity at the top level and in each successful backend's model object.

3. Run deterministic analysis. Run scripts/analyze_trt_perf.py first when you need an integrity gate before interpretation. The script uses only Python built-in modules, extracts structured analysis data, and serializes it as JSON. This JSON is the authoritative analyzer output for validation, packaging, and AI diagnosis.

4. Check validation before interpreting. The analyzer exits when it can emit structured validation data, even if one or more backends fail validation. Read the generated JSON object to decide which backend reports are usable. If the analyzer exits nonzero, stop because it could not emit structured data. If the schema validator exits nonzero, stop because the generated JSON contract is invalid. Do not continue into performance interpretation for a backend unless its validation status is , its analysis mode is , the layer graph is a DAG, and the layer/profile names match. For backends, graph and layer inspection are available but latency/performance interpretation is not.