Qualcomm AI Engine Direct - Addition of new APIs for QNN custom op package and quantization annotation

[qti-mmadhava]

Qualcomm AI Engine Direct - Addition of new APIs for QNN custom op package and quantization annotation

• Add QnnCustomOpPackageBuilder in backends/qualcomm/custom_op/interface.py to parse QNN XML op package configs via QnnOpPackageGenerator, register per-target/platform implementations, and validate torch-to-QNN op type name mappings
• Add IOQuantConfig dataclass and CustomOpsQuantAnnotator class in backends/qualcomm/custom_op/annotator.py to build per-op quantization annotation functions for custom ops, with support for both single and multi-output ops
• Updated examples/qualcomm/custom_op/custom_ops_1.py as an end-to-end example using the new builder and annotator APIs
• Add examples/qualcomm/custom_op/custom_ops_2.py and example_op_package_htp_multi_output/SplitCustomOpPackage demonstrating multi-output custom op support with a split op
• README doc updates

    python3 examples/qualcomm/custom_op/custom_ops_1.py --build_folder build-android -s <device_serial> -H <host> -m SM8650 --op_package_dir examples/qualcomm/custom_op/example_op_package_htp/ExampleOpPackage --build_op_package
    python3 examples/qualcomm/custom_op/custom_ops_2.py --build_folder build-android -s <device_serial> -H <host> -m SM8650 --op_package_dir examples/qualcomm/custom_op/example_op_package_htp_multi_output/SplitCustomOpPackage --build_op_package

[pytorch-bot]

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[qti-mmadhava]

Hi @cccclai, @abhinaykukkadapu,
This PR introduces new APIs and examples for using custom ops with QNN backend.
When you have time, could you please help review?
Thanks

[qti-mmadhava]

@pytorchbot label "release notes: qualcomm"