Capture CUDA logging output

[fraxy-v]

Addresses logging capture issues reported here #5797.

This PR adds a CUDA logging callback similar to that in ggml-metal.h:
https://github.com/ggerganov/llama.cpp/blob/583fd6b000ec9ad1b465b5c98524f4a0ae388077/ggml-metal.h#L43

However, the issue OP has certainly experienced other uncaptured log messages. For example:

MY LOGGER SAYS: ggml_cuda_host_malloc: failed to allocate 256.00 MiB of pinned memory: no CUDA-capable device is detected
MY LOGGER SAYS: llama_kv_cache_init:        CPU KV buffer size =   256.00 MiB
MY LOGGER SAYS: llama_new_context_with_model: KV self size  =  256.00 MiB, K (f16):  128.00 MiB, V (f16):  128.00 MiB
MY LOGGER SAYS: ggml_cuda_host_malloc: failed to allocate 0.12 MiB of pinned memory: no CUDA-capable device is detected
MY LOGGER SAYS: llama_new_context_with_model:        CPU  output buffer size =     0.12 MiB
ggml_gallocr_reserve_n: reallocating CUDA_Host buffer from size 0.00 MiB to 70.50 MiB
MY LOGGER SAYS: ggml_cuda_host_malloc: failed to allocate 70.50 MiB of pinned memory: no CUDA-capable device is detected
MY LOGGER SAYS: llama_new_context_with_model:  CUDA_Host compute buffer size =    70.50 MiB
MY LOGGER SAYS: llama_new_context_with_model: graph nodes  = 1030
MY LOGGER SAYS: llama_new_context_with_model: graph splits = 1

system_info: n_threads = 4 / 8 | AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | 
sampling: 
	repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
	top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.800
	mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampling order: 
CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature 
generate: n_ctx = 512, n_batch = 2048, n_predict = -1, n_keep = 1


<s> Tell me a story about a llama
MY LOGGER SAYS: 
MY LOGGER SAYS: llama_print_timings:   

As evident methods in ggml-alloc.c, e.g. ggml_gallocr_reserve_n, use directly stderr. So that begs the question whether the internal logging in llama.cpp should not be made commonly available, e.g. in common.h.

[github-actions]

📈 llama.cpp server for bench-server-baseline on Standard_NC4as_T4_v3 for phi-2-q4_0: 547 iterations 🚀

Expand details for performance related PR only

• Concurrent users: 8, duration: 10m
• HTTP request : avg=8584.51ms p(95)=20980.66ms fails=, finish reason: stop=488 truncated=59
• Prompt processing (pp): avg=102.17tk/s p(95)=445.57tk/s
• Token generation (tg): avg=59.06tk/s p(95)=46.91tk/s
• ggml-org/models/phi-2/ggml-model-q4_0.gguf parallel=8 ctx-size=16384 ngl=33 batch-size=2048 ubatch-size=256 pp=1024 pp+tg=2048 branch=master commit=89b3236152d97e0361939091b467d4530226e9fc

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[ggerganov]

As evident methods in ggml-alloc.c, e.g. ggml_gallocr_reserve_n, use directly stderr. So that begs the question whether the internal logging in llama.cpp should not be made commonly available, e.g. in common.h.

Most of the printfs there are during Debug builds - these are not a problem.
For the rest though, I'm not sure - I am wondering if we should just keep using fprintf(stderr, ... for errors and only propagate a log function when we want to print some info/warning messages (such as the ones addressed in the current issue).