* llama : fix pooling assertion crash in chunked GDN detection path
The chunked fused Gated Delta Net detection in sched_reserve() calls
graph_reserve(16*n_seqs, n_seqs, n_outputs, ...) where n_outputs = n_seqs.
This creates a dimension mismatch in build_pooling() for embedding models
with mean/rank pooling: build_inp_mean() creates a tensor with shape
[n_tokens=16*n_seqs, ...] while t_embd is reduced to [n_outputs=n_seqs, ...]
via out_ids, causing ggml_mul_mat to assert on ggml_can_mul_mat(a, b).
Fix: pass n_tokens as n_outputs in the chunked GDN graph reservation,
matching the pattern used by the pp/tg worst-case reservations.
Regression introduced by #20340 (d28961d).
Same class of bug as #12517, fixed by #12545.
* server : add mean pooling tests to embedding test suite
Add test_embedding_pooling_mean and test_embedding_pooling_mean_multiple
to cover the --pooling mean codepath, which was previously untested.
These tests would have caught the regression introduced by #20340 where
build_pooling() crashes with a ggml_mul_mat assertion due to mismatched
dimensions in the chunked GDN detection path.
---------
Co-authored-by: Domenico Crupi <domenico@zerovolt.it>
Tests target GitHub workflows job runners with 4 vCPU.
Note: If the host architecture inference speed is faster than GitHub runners one, parallel scenario may randomly fail.
To mitigate it, you can increase values in n_predict, kv_size.
Install dependencies
pip install -r requirements.txt
Run tests
Build the server
cd ../../..
cmake -B build
cmake --build build --target llama-server
Start the test: ./tests.sh
It's possible to override some scenario steps values with environment variables:
variable
description
PORT
context.server_port to set the listening port of the server during scenario, default: 8080
LLAMA_SERVER_BIN_PATH
to change the server binary path, default: ../../../build/bin/llama-server
DEBUG
to enable steps and server verbose mode --verbose
N_GPU_LAYERS
number of model layers to offload to VRAM -ngl --n-gpu-layers
LLAMA_CACHE
by default server tests re-download models to the tmp subfolder. Set this to your cache (e.g. $HOME/Library/Caches/llama.cpp on Mac or $HOME/.cache/llama.cpp on Unix) to avoid this
To run slow tests (will download many models, make sure to set LLAMA_CACHE if needed):
SLOW_TESTS=1 ./tests.sh
To run with stdout/stderr display in real time (verbose output, but useful for debugging):
It can sometimes be useful to run the server in a debugger when invesigating test
failures. To do this, the environment variable DEBUG_EXTERNAL=1 can be set
which will cause the test to skip starting a llama-server itself. Instead, the
server can be started in a debugger.