b11576

graph: pad the KV dimension of the no-cache attention to 256 (#30416)

The no-cache path builds a [n_tokens, n_tokens] mask and passes K and V
unpadded, so FLASH_ATTN_EXT sees K->ne[1] == n_tokens. The CUDA kernels
for head size 512 require a multiple of FATTN_KQ_STRIDE, so the op falls
back to the CPU for most lengths, and the -fa auto probe (1 token)
disables flash attention for such models.

Pad the mask like llama_kv_cache::get_n_kv and pad K and V with zeros up
to the KV dimension of the mask. clef builds its own causal mask and
pads it the same way.

Website:

• https://llama.app

Attestations:

• https://github.com/ggml-org/llama.cpp/attestations/55199687

macOS/iOS:

• macOS Apple Silicon (arm64)
• macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED
• macOS Intel (x64)
• iOS XCFramework

Linux:

• Ubuntu x64 (CPU)
• Ubuntu arm64 (CPU)
• Ubuntu s390x (CPU)
• Ubuntu x64 (Vulkan)
• Ubuntu arm64 (Vulkan)
• Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries
• Ubuntu x64 (CUDA 13) - CUDA 13.4 libraries
• Ubuntu arm64 (CUDA 13) - CUDA 13.4 libraries
• Ubuntu x64 (ROCm 10.0)
• Ubuntu x64 (OpenVINO)
• Ubuntu x64 (SYCL FP32)
• Ubuntu x64 (SYCL FP16)
• Linux arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide

Android:

• Android arm64 (CPU)
• Android arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide

Windows:

• Windows x64 (CPU)
• Windows arm64 (CPU)
• Windows arm64 (OpenCL Adreno)
• Windows x64 (CUDA 12) - CUDA 12.4 DLLs
• Windows x64 (CUDA 13) - CUDA 13.4 DLLs
• Windows arm64 (CUDA 13) - CUDA 13.4 DLLs
• Windows x64 (Vulkan)
• Windows arm64 (Vulkan)
• Windows x64 (OpenVINO)
• Windows x64 (SYCL)
• Windows x64 (ROCm 10.0)

openEuler:

• DISABLED
• openEuler x86 (310p)
• openEuler x86 (910b, ACL Graph)
• openEuler aarch64 (310p)
• openEuler aarch64 (910b, ACL Graph)

• UI