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Fix typo for --lens_recipe option, update readme and example
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backends/qualcomm/debugger/README.md

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@@ -90,28 +90,27 @@ Note: Files ending with `.bin` do not support graph visualization in qairt_visua
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For more details, visit the [QAIRT Visualizer](https://pypi.org/project/qairt-visualizer/).
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# Observatory (GraphView Minimal, RFC-aligned)
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# Observatory
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A new, review-focused Observatory implementation is available under:
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`backends/qualcomm/debugger/observatory`
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Key properties:
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1. Uses RFC-style view contracts: `ViewBlock`, `ViewList`, and `GraphView`.
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2. Keeps UI behavior close to legacy observatory while splitting JS into topic files.
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3. Supports ETRecord auto-collection through context-managed monkey patching.
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4. Migrates minimal built-in lenses for v1: metadata and stack trace (plus canonical graph lens).
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Quick demo:
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Use observaotry.cli to invoke ordinary aot script. Use `--lens_recipe=accuracy` to enable accuracy Lenses.
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```bash
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source ~/executorch/.venv/bin/activate
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source ~/executorch/qairt/2.37.0.250724/bin/envsetup.sh
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export PYTHONPATH=~/
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python backends/qualcomm/debugger/observatory/examples/demo_graphview_accuracy_compare.py \
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--model toy --output-dir /tmp/observatory_graphview_demo
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python -m executorch.backends.qualcomm.debugger.observatory.cli \
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--output-html obs_report.html \
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--lens_recipe=accuracy \
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{original script and args}
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```
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For example
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```bash
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python -m executorch.backends.qualcomm.debugger.observatory.cli \
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--output-html obs_report.html \
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--lens_recipe=accuracy \
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examples/qualcomm/oss_scripts/mobilevit_v2.py --backend htp --model SM8650 -d ./imagenet-mini-val/ -b build-android/ --compile_only
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```
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# ExecuTorch QNN Intermediate Output Debugger
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backends/qualcomm/debugger/observatory/cli.py

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With accuracy debugging:
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python -m executorch.backends.qualcomm.debugger.observatory \\
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--lense_recipe=accuracy SCRIPT [SCRIPT_ARGS...]
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--lens_recipe=accuracy SCRIPT [SCRIPT_ARGS...]
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Visualize mode (JSON -> HTML):
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python -m executorch.backends.qualcomm.debugger.observatory visualize \\
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prog="python -m executorch.backends.qualcomm.debugger.observatory"
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)
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parser.add_argument(
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"--lense_recipe",
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"--lens_recipe",
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choices=["accuracy"],
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default=None,
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help="Lens recipe to enable (e.g. accuracy)",
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PipelineGraphCollectorLens.register_backend_patches(install_qnn_patches)
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Observatory.register_lens(PipelineGraphCollectorLens)
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if args.lense_recipe == "accuracy":
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if args.lens_recipe == "accuracy":
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from executorch.devtools.observatory.lenses.accuracy import AccuracyLens
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from .lenses.qnn_dataset_patches import install_qnn_dataset_patches
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backends/xnnpack/debugger/observatory/cli.py

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With accuracy debugging:
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python -m executorch.backends.xnnpack.debugger.observatory \\
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--lense_recipe=accuracy SCRIPT [SCRIPT_ARGS...]
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--lens_recipe=accuracy SCRIPT [SCRIPT_ARGS...]
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Visualize mode (JSON -> HTML):
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python -m executorch.backends.xnnpack.debugger.observatory visualize \\
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prog="python -m executorch.backends.xnnpack.debugger.observatory"
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)
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parser.add_argument(
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"--lense_recipe",
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"--lens_recipe",
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choices=["accuracy"],
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default=None,
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help="Lens recipe to enable (e.g. accuracy)",
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PipelineGraphCollectorLens.register_backend_patches(install_xnnpack_patches)
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Observatory.register_lens(PipelineGraphCollectorLens)
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if args.lense_recipe == "accuracy":
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if args.lens_recipe == "accuracy":
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from devtools.observatory.lenses.accuracy import AccuracyLens
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Observatory.register_lens(AccuracyLens)

devtools/observatory/rfc_draft.md

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