ExecuTorch support

This change introduces a framework abstraction layer and adds initial support for the ExecuTorch backend alongside TensorFlow Lite Micro (TFLM).

Highlights:

• Introduced fwk/ module with backend-agnostic interfaces to decouple use-case logic from ML frameworks.
• Isolated TFLM-specific logic into fwk/tflm; added ExecuTorch based implementation under fwk/ExecuTorch.
• Enabled selection of ML framework via ML_FRAMEWORK_BUILD CMake flag.

ExecuTorch Integration:

• Added ExecuTorch model and tensor classes.
• Integrated native (host) inference flow.
• Enabled AOT compilation pipeline via aot_arm_compiler and .pte generation.
• Added portable ops shared library.
• Added data layout conversions (NHWC → NCHW) in common API.

Infrastructure & Setup:

• Refactored setup scripts with improved structure and Pylint compliance.
• Introduced --parallel flag to speed up model setup.
• Extended script to generate ExecuTorch models and support conditional use-case setup.

Documentation:

• Updated all use-case documentation to reflect framework compatibility.

This lays the groundwork for future extensibility, enabling use-cases to support multiple ML runtimes with minimal duplication.