mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-12-23 21:17:54 +01:00

History

slaren f30ea47a87 llama : add pipeline parallelism support (#6017 ) * llama : add pipeline parallelism support for batch processing with multiple CUDA GPUs ggml-ci * server : add -ub, --ubatch-size parameter * fix server embedding test * llama : fix Mamba inference for pipeline parallelism Tested to work correctly with both `main` and `parallel` examples. * llama : limit max batch size to n_batch * add LLAMA_SCHED_MAX_COPIES to configure the number of input copies for pipeline parallelism default increase to 4 (from 2) changing this value may improve performance for some systems, but increases memory usage * fix hip build * fix sycl build (disable cpy_tensor_async) * fix hip build * llama : limit n_batch and n_ubatch to n_ctx during context creation * llama : fix norm backend * batched-bench : sync after decode * swiftui : sync after decode * ggml : allow ggml_get_rows to use multiple threads if they are available * check n_ubatch >= n_tokens with non-casual attention * llama : do not limit n_batch to n_ctx with non-casual attn * server : construct batch with size of llama_n_batch * ggml_backend_cpu_graph_compute : fix return value when alloc fails * llama : better n_batch and n_ubatch comment * fix merge * small fix * reduce default n_batch to 2048 --------- Co-authored-by: Francis Couture-Harpin <git@compilade.net> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>		2024-03-13 18:54:21 +01:00
..
features	llama : add pipeline parallelism support (#6017 )	2024-03-13 18:54:21 +01:00
README.md	server: tests: passkey challenge / self-extend with context shift demo (#5832 )	2024-03-02 22:00:14 +01:00
requirements.txt	server : refactor (#5882 )	2024-03-07 11:41:53 +02:00
tests.sh	server: tests: passkey challenge / self-extend with context shift demo (#5832 )	2024-03-02 22:00:14 +01:00

README.md

Server tests

Python based server tests scenario using BDD and behave:

issues.feature Pending issues scenario
parallel.feature Scenario involving multi slots and concurrent requests
security.feature Security, CORS and API Key
server.feature Server base scenario: completion, embedding, tokenization, etc...

Tests target GitHub workflows job runners with 4 vCPU.

Requests are using aiohttp, asyncio based http client.

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 ../../..
mkdir build
cd build
cmake ../
cmake --build . --target 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/server`
`DEBUG`	"ON" to enable steps and server verbose mode `--verbose`
`SERVER_LOG_FORMAT_JSON`	if set switch server logs to json format
`N_GPU_LAYERS`	number of model layers to offload to VRAM `-ngl --n-gpu-layers`

Run @bug, @wip or @wrong_usage annotated scenario

Feature or Scenario must be annotated with @llama.cpp to be included in the default scope.

@bug annotation aims to link a scenario with a GitHub issue.
@wrong_usage are meant to show user issue that are actually an expected behavior
@wip to focus on a scenario working in progress
@slow heavy test, disabled by default

To run a scenario annotated with @bug, start:

DEBUG=ON ./tests.sh --no-skipped --tags bug

After changing logic in steps.py, ensure that @bug and @wrong_usage scenario are updated.

./tests.sh --no-skipped --tags bug,wrong_usage || echo "should failed but compile"