Eval bug: Segmentation fault with docker aarch64 on MacOS M1 using a small test model stories15M_MOE-Q8_0.gguf #11082
Description
Name and Version
version: 4410 (4b0c638)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for aarch64-linux-gnu
Operating systems
Mac
GGML backends
CPU
Hardware
MacOS M1
Models
https://huggingface.co/ggml-org/stories15M_MOE stories15M_MOE-Q8_0.gguf
Problem description & steps to reproduce
-
download the gguf model
mkdir -p models MODEL=stories15M_MOE-Q8_0.gguf && curl -sL -o models/$MODEL "https://huggingface.co/ggml-org/stories15M_MOE/resolve/main/$MODEL?download=true"
-
run with docker on aarch64 - it fails
docker run --platform linux/aarch64 --rm -it --name llama.cpp-full -v $PWD/models:/models ghcr.io/ggerganov/llama.cpp:full-b4410 --run -m /models/stories15M_MOE-Q8_0.gguf -p "Building a website can be done in 10 simple steps:" ... echo $? 139
When executing the run in the container with bash, it additionally prints "Segmentation fault (core dumped)"
docker run --entrypoint /bin/bash --platform linux/aarch64 --rm -it --name llama.cpp-full -v $PWD/models:/models ghcr.io/ggerganov/llama.cpp:full-b4410 ./llama-cli -m /models/stories15M_MOE-Q8_0.gguf -p "Building a website can be done in 10 simple steps:"
-
run with docker on amd64 - it succeeds
docker run --platform linux/amd64 --rm -it --name llama.cpp-full -v $PWD/models:/models ghcr.io/ggerganov/llama.cpp:full-b4410 --run -m /models/stories15M_MOE-Q8_0.gguf -p "Building a website can be done in 10 simple steps:" # use docker stop llama.cpp-full to stop that run
I see the aarch64 run does not load_backend, and amd64 does
< build: 4410 (4b0c638b) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for aarch64-linux-gnu
---
> load_backend: loaded CPU backend from ./libggml-cpu-haswell.so
> build: 4410 (4b0c638b) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
First Bad Commit
No response
Relevant log output
Unable to find image 'ghcr.io/ggerganov/llama.cpp:full-b4410' locally
full-b4410: Pulling from ggerganov/llama.cpp
Digest: sha256:03fd6a1abb47fc7abe25c50a7a2fb0651ef0f0ef314e5fe0c16fa80442b1f83f
Status: Downloaded newer image for ghcr.io/ggerganov/llama.cpp:full-b4410
build: 4410 (4b0c638b) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for aarch64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_loader: loaded meta data with 26 key-value pairs and 63 tensors from /models/stories15M_MOE-Q8_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 = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.size_label str = 4x24M
llama_model_loader: - kv 3: general.license str = mit
llama_model_loader: - kv 4: llama.block_count u32 = 6
llama_model_loader: - kv 5: llama.context_length u32 = 256
llama_model_loader: - kv 6: llama.embedding_length u32 = 288
llama_model_loader: - kv 7: llama.feed_forward_length u32 = 768
llama_model_loader: - kv 8: llama.attention.head_count u32 = 6
llama_model_loader: - kv 9: llama.attention.head_count_kv u32 = 6
llama_model_loader: - kv 10: llama.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 11: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 12: llama.expert_count u32 = 4
llama_model_loader: - kv 13: llama.expert_used_count u32 = 2
llama_model_loader: - kv 14: general.file_type u32 = 7
llama_model_loader: - kv 15: llama.vocab_size u32 = 32000
llama_model_loader: - kv 16: llama.rope.dimension_count u32 = 48
llama_model_loader: - kv 17: tokenizer.ggml.model str = llama
llama_model_loader: - kv 18: tokenizer.ggml.pre str = default
llama_model_loader: - kv 19: tokenizer.ggml.tokens arr[str,32000] = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv 20: tokenizer.ggml.scores arr[f32,32000] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 21: tokenizer.ggml.token_type arr[i32,32000] = [3, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 1
llama_model_loader: - kv 23: tokenizer.ggml.eos_token_id u32 = 2
llama_model_loader: - kv 24: tokenizer.ggml.unknown_token_id u32 = 0
llama_model_loader: - kv 25: general.quantization_version u32 = 2
llama_model_loader: - type f32: 19 tensors
llama_model_loader: - type q8_0: 44 tensors
llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
llm_load_vocab: special tokens cache size = 3
llm_load_vocab: token to piece cache size = 0.1684 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 256
llm_load_print_meta: n_embd = 288
llm_load_print_meta: n_layer = 6
llm_load_print_meta: n_head = 6
llm_load_print_meta: n_head_kv = 6
llm_load_print_meta: n_rot = 48
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 48
llm_load_print_meta: n_embd_head_v = 48
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 288
llm_load_print_meta: n_embd_v_gqa = 288
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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 = 768
llm_load_print_meta: n_expert = 4
llm_load_print_meta: n_expert_used = 2
llm_load_print_meta: causal attn = 1
llm_load_print_meta: pooling type = 0
llm_load_print_meta: rope type = 0
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 = 256
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 = Q8_0
llm_load_print_meta: model params = 36.36 M
llm_load_print_meta: model size = 36.87 MiB (8.51 BPW)
llm_load_print_meta: general.name = n/a
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_print_meta: EOG token = 2 '</s>'
llm_load_print_meta: max token length = 48