Closed xvim closed 2 months ago
I am not able to reproduce this error. Does llama-cli
work with the CUDA backend?
I am not able to reproduce this error. Does
llama-cli
work with the CUDA backend?
yes, use CUDA backend success.
root@kylin-Default-string:/data/liucong/llama.cpp# ./build_rpc_cuda/bin/llama-cli --version
version: 3639 (20f1789d)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
root@kylin-Default-string:/data/liucong/llama.cpp# ./build_rpc_cuda/bin/llama-server -m /data/models/huggingface/Qwen/Qwen2-7B-Instruct-GGUF/qwen2-7b-instruct-q4_0.gguf -ngl 33 --host 0.0.0.0
INFO [ main] build info | tid="139330554249216" timestamp=1724836378 build=3639 commit="20f1789d"
INFO [ main] system info | tid="139330554249216" timestamp=1724836378 n_threads=14 n_threads_batch=-1 total_threads=28 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 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 | "
INFO [ main] HTTP server is listening | tid="139330554249216" timestamp=1724836378 n_threads_http="27" port="8080" hostname="0.0.0.0"
INFO [ main] loading model | tid="139330554249216" timestamp=1724836378 n_threads_http="27" port="8080" hostname="0.0.0.0"
llama_model_loader: loaded meta data with 26 key-value pairs and 339 tensors from /data/models/huggingface/Qwen/Qwen2-7B-Instruct-GGUF/qwen2-7b-instruct-q4_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen2
llama_model_loader: - kv 1: general.name str = qwen2-7b-instruct
llama_model_loader: - kv 2: qwen2.block_count u32 = 28
llama_model_loader: - kv 3: qwen2.context_length u32 = 32768
llama_model_loader: - kv 4: qwen2.embedding_length u32 = 3584
llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 18944
llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 28
llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 4
llama_model_loader: - kv 8: qwen2.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 9: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 10: general.file_type u32 = 2
llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 15: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 19: tokenizer.chat_template str = {% for message in messages %}{% if lo...
llama_model_loader: - kv 20: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 21: general.quantization_version u32 = 2
llama_model_loader: - kv 22: quantize.imatrix.file str = ../Qwen2/gguf/qwen2-7b-imatrix/imatri...
llama_model_loader: - kv 23: quantize.imatrix.dataset str = ../sft_2406.txt
llama_model_loader: - kv 24: quantize.imatrix.entries_count i32 = 196
llama_model_loader: - kv 25: quantize.imatrix.chunks_count i32 = 1937
llama_model_loader: - type f32: 141 tensors
llama_model_loader: - type q4_0: 194 tensors
llama_model_loader: - type q4_1: 3 tensors
llama_model_loader: - type q6_K: 1 tensors
llm_load_vocab: special tokens cache size = 421
llm_load_vocab: token to piece cache size = 0.9352 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = qwen2
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 152064
llm_load_print_meta: n_merges = 151387
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 32768
llm_load_print_meta: n_embd = 3584
llm_load_print_meta: n_layer = 28
llm_load_print_meta: n_head = 28
llm_load_print_meta: n_head_kv = 4
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 7
llm_load_print_meta: n_embd_k_gqa = 512
llm_load_print_meta: n_embd_v_gqa = 512
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-06
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale = 0.0e+00
llm_load_print_meta: n_ff = 18944
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attn = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 2
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 32768
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: ssm_d_conv = 0
llm_load_print_meta: ssm_d_inner = 0
llm_load_print_meta: ssm_d_state = 0
llm_load_print_meta: ssm_dt_rank = 0
llm_load_print_meta: ssm_dt_b_c_rms = 0
llm_load_print_meta: model type = ?B
llm_load_print_meta: model ftype = Q4_0
llm_load_print_meta: model params = 7.62 B
llm_load_print_meta: model size = 4.13 GiB (4.66 BPW)
llm_load_print_meta: general.name = qwen2-7b-instruct
llm_load_print_meta: BOS token = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token = 151645 '<|im_end|>'
llm_load_print_meta: PAD token = 151643 '<|endoftext|>'
llm_load_print_meta: LF token = 148848 'ÄĬ'
llm_load_print_meta: EOT token = 151645 '<|im_end|>'
llm_load_print_meta: max token length = 256
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 2 CUDA devices:
Device 0: NVIDIA GeForce RTX 4060 Ti, compute capability 8.9, VMM: yes
Device 1: NVIDIA GeForce RTX 2060, compute capability 7.5, VMM: yes
llm_load_tensors: ggml ctx size = 0.45 MiB
llm_load_tensors: offloading 28 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 29/29 layers to GPU
llm_load_tensors: CPU buffer size = 292.36 MiB
llm_load_tensors: CUDA0 buffer size = 2138.17 MiB
llm_load_tensors: CUDA1 buffer size = 1802.04 MiB
......................................................................................
llama_new_context_with_model: n_ctx = 32768
llama_new_context_with_model: n_batch = 2048
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CUDA0 KV buffer size = 1088.00 MiB
llama_kv_cache_init: CUDA1 KV buffer size = 704.00 MiB
llama_new_context_with_model: KV self size = 1792.00 MiB, K (f16): 896.00 MiB, V (f16): 896.00 MiB
llama_new_context_with_model: CUDA_Host output buffer size = 1.16 MiB
llama_new_context_with_model: pipeline parallelism enabled (n_copies=4)
ggml_gallocr_reserve_n: reallocating CUDA0 buffer from size 0.00 MiB to 2104.01 MiB
ggml_gallocr_reserve_n: reallocating CUDA1 buffer from size 0.00 MiB to 2104.02 MiB
ggml_gallocr_reserve_n: reallocating CUDA_Host buffer from size 0.00 MiB to 263.02 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 2104.01 MiB
llama_new_context_with_model: CUDA1 compute buffer size = 2104.02 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 263.02 MiB
llama_new_context_with_model: graph nodes = 986
llama_new_context_with_model: graph splits = 3
It looks like you have 2 CUDA devices and you are using CUDA_VISIBLE_DEVICES=0
when starting the rpc-server
. Maybe at some point the CUDA backend decides to also use device 1 which is not initialized.
# CUDA_VISIBLE_DEVICES=0 ./build_rpc_cuda/bin/rpc-server -p 50052 -H 0.0.0.0
remove CUDA_VISIBLE_DEVICES=0 then run rpc-server ,also crash
upgrade cuda version ,seems no crash
What happened?
crash
Name and Version
./build_rpc_cuda/bin/llama-cli --version
version: 3639 (20f1789d) built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
What operating system are you seeing the problem on?
No response
Relevant log output