The Cadence runtime example needs update

[jirioc]

🐛 Describe the bug

1. Building the runtime example is not possible because the examples/cadence/CMakeLists.txt uses outdated paths. For example, this fails
   add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/hifi/operators)
   because the hifi subdirectory does not exist inside examples/cadence but can be found in backends/cadence.

2. The file backends/cadence/hifi/kernels/CMakeLists.txt uses include paths from backends/cadence/hifi/third-party/nnlib/nnlib-hifi4 that do not exist. And backends/cadence/hifi/third-party/nnlib/CMakeLists.txt also uses such path. Even if I clone the nnlib from GitHub to this directory, it does not compile. The compilation reports conflicting types between nnlib and the original third-party content.

3. The file backends/cadence/hifi/kernels/CMakeLists.txt uses incomplete name of source file op_quantized_fully_connected_out.

Versions

Collecting environment information...
PyTorch version: 2.11.0.dev20251222+cpu
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.31.6
Libc version: glibc-2.31

Python version: 3.10.18 (main, Jun 4 2025, 08:56:00) [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-5.4.0-216-generic-x86_64-with-glibc2.31
Is CUDA available: False
CUDA runtime version: 10.1.243
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Could not collect
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Caching allocator config: N/A

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 43 bits physical, 48 bits virtual
CPU(s): 6
On-line CPU(s) list: 0-5
Thread(s) per core: 1
Core(s) per socket: 6
Socket(s): 1
NUMA node(s): 1
Vendor ID: GenuineIntel
CPU family: 6
Model: 79
Model name: Intel(R) Xeon(R) Gold 6154 CPU @ 3.00GHz
Stepping: 0
CPU MHz: 2992.968
BogoMIPS: 5985.93
Hypervisor vendor: VMware
Virtualization type: full
L1d cache: 192 KiB
L1i cache: 192 KiB
L2 cache: 6 MiB
L3 cache: 24.8 MiB
NUMA node0 CPU(s): 0-5
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: KVM: Vulnerable
Vulnerability L1tf: Mitigation; PTE Inversion
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Retbleed: Mitigation; IBRS
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; IBRS; IBPB conditional; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon nopl xtopology tsc_reliable nonstop_tsc cpuid pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 invpcid rdseed adx smap xsaveopt arat md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] executorch==1.1.0a0+cccf977
[pip3] flake8==6.1.0
[pip3] flake8-breakpoint==1.1.0
[pip3] flake8-bugbear==24.4.26
[pip3] flake8-comprehensions==3.14.0
[pip3] flake8-plugin-utils==1.3.3
[pip3] flake8-pyi==23.5.0
[pip3] mypy==1.14.1
[pip3] mypy_extensions==1.1.0
[pip3] numpy==2.0.0
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-cusparselt-cu12==0.6.2
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] optree==0.17.0
[pip3] pytorch_tokenizers==1.0.1
[pip3] torch==2.11.0.dev20251222+cpu
[pip3] torchao==0.16.0+git08e5e203f
[pip3] torchaudio==2.10.0.dev20251222+cpu
[pip3] torchdata==0.11.0
[pip3] torchgen==0.0.1
[pip3] torchsr==1.0.4
[pip3] torchtune==0.6.1
[pip3] torchvision==0.25.0.dev20251222+cpu
[pip3] triton==3.2.0
[conda] Could not collect