vbatts/llama.cpp
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server : simplify state machine for slot (#9283)

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* server : simplify state machine for slot

* add SLOT_STATE_DONE_PROMPT

* pop_deferred_task

* add missing notify_one

* fix passkey test

* metrics : add n_busy_slots_per_decode

* fix test step

* add test

* maybe fix AddressSanitizer?

* fix deque ?

* missing lock

* pop_deferred_task: also notify

* Update examples/server/server.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Xuan Son Nguyen 2024-09-06 23:21:29 +02:00 • committed by GitHub
parent 134bc38ecf
commit 9b2c24c099
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4 changed files with 147 additions and 93 deletions
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29
examples/server/tests/features/parallel.feature
View file

@ -77,6 +77,35 @@ Feature: Parallel
| disabled | 128 |
| enabled | 64 |
Scenario Outline: Multi users with number of prompts exceeding number of slots
Given a system prompt You are a writer.
And a model tinyllama-2
Given a prompt:
"""
Write a very long book.
"""
And a prompt:
"""
Write another a poem.
"""
And a prompt:
"""
What is LLM?
"""
And a prompt:
"""
The sky is blue and I love it.
"""
And <n_predict> max tokens to predict
And streaming is <streaming>
Given concurrent OAI completions requests
Then the server is busy
Then the server is idle
Then all prompts are predicted with <n_predict> tokens
Examples:
| streaming | n_predict |
| disabled | 128 |
| enabled | 64 |
Scenario: Multi users with total number of tokens to predict exceeds the KV Cache size #3969
Given a prompt:

4
examples/server/tests/features/passkey.feature
View file

@ -15,6 +15,7 @@ Feature: Passkey / Self-extend with context shift
And <n_junk> as number of junk
And <n_predicted> server max tokens to predict
And 42 as seed
And 0.0 temperature
And <n_ctx> KV cache size
And 1 slots
And <n_ga> group attention factor to extend context size through self-extend
@ -22,7 +23,8 @@ Feature: Passkey / Self-extend with context shift
# Can be override with N_GPU_LAYERS
And <ngl> GPU offloaded layers
Then the server is starting
Then the server is healthy
# Higher timeout because the model may need to be downloaded from the internet
Then the server is healthy with timeout 120 seconds
Given available models
Then model 0 is trained on <n_ctx_train> tokens context
Given a prefix prompt:

20
examples/server/tests/features/steps/steps.py
View file

@ -202,17 +202,15 @@ def step_start_server(context):
time.sleep(0.1)
@step("the server is {expecting_status}")
@async_run_until_complete
async def step_wait_for_the_server_to_be_started(context, expecting_status: Literal['healthy', 'ready', 'idle', 'busy'] | str):
async def wait_for_server_status_with_timeout(context, expecting_status: Literal['healthy', 'ready', 'idle', 'busy'] | str, timeout: int):
match expecting_status:
case 'healthy':
await wait_for_slots_status(context, context.base_url, 200,
timeout=30)
timeout=timeout)
case 'ready' | 'idle':
await wait_for_slots_status(context, context.base_url, 200,
timeout=30,
timeout=timeout,
params={'fail_on_no_slot': 1},
slots_idle=context.n_slots,
slots_processing=0)
@ -225,6 +223,18 @@ async def step_wait_for_the_server_to_be_started(context, expecting_status: Lite
assert False, "unknown status"
@step("the server is {expecting_status} with timeout {timeout:d} seconds")
@async_run_until_complete
async def step_wait_for_server_status_with_timeout(context, expecting_status: Literal['healthy', 'ready', 'idle', 'busy'] | str, timeout: int):
await wait_for_server_status_with_timeout(context, expecting_status, timeout)
@step("the server is {expecting_status}")
@async_run_until_complete
async def step_wait_for_server_status(context, expecting_status: Literal['healthy', 'ready', 'idle', 'busy'] | str):
await wait_for_server_status_with_timeout(context, expecting_status, 30)
@step('all slots are {expected_slot_status_string}')
@async_run_until_complete
async def step_all_slots_status(context, expected_slot_status_string: Literal['idle', 'busy'] | str):