Fix mlx seed (#1094)

## Motivation

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## Changes

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## Why It Works

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## Test Plan

### Manual Testing
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---------

Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
Co-authored-by: Ryuichi Leo Takashige <[email protected]>
This commit is contained in:
Chris A
2026-01-09 01:40:15 +00:00
committed by GitHub
co-authored by google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com> Ryuichi Leo Takashige
parent b9a78f6f3a
commit c65320acd3
4 changed files with 18 additions and 18 deletions
@@ -3,6 +3,7 @@ from typing import Any, Callable, Generator, cast, get_args
import mlx.core as mx
from mlx_lm import stream_generate
from mlx_lm.models.cache import KVCache
from mlx_lm.sample_utils import make_sampler
from mlx_lm.tokenizer_utils import TokenizerWrapper
# from exo.engines.mlx.cache import KVPrefixCache
@@ -47,7 +48,6 @@ def maybe_quantize_kv_cache(
def warmup_inference(
model: Model,
tokenizer: TokenizerWrapper,
sampler: Callable[[mx.array], mx.array],
) -> int:
content = "Prompt to warm up the inference engine. Repeat this."
@@ -70,6 +70,9 @@ def warmup_inference(
model=model,
)
# Use a default sampler for warmup
sampler = make_sampler(temp=0.7)
logger.info("Generating warmup tokens")
for _r in stream_generate(
model=model,
@@ -115,7 +118,6 @@ def eos_ids_from_tokenizer(tokenizer: TokenizerWrapper) -> list[int]:
def mlx_generate(
model: Model,
tokenizer: TokenizerWrapper,
sampler: Callable[[mx.array], mx.array],
task: ChatCompletionTaskParams,
) -> Generator[GenerationResponse]:
# Ensure that generation stats only contains peak memory for this generation
@@ -125,6 +127,9 @@ def mlx_generate(
# Currently we support chat-completion tasks only.
logger.info(f"task_params: {task}")
if task.seed is not None:
mx.random.seed(task.seed)
prompt = apply_chat_template(
tokenizer=tokenizer,
chat_task_data=task,
@@ -138,6 +143,11 @@ def mlx_generate(
eos_ids = eos_ids_from_tokenizer(tokenizer)
logits_processors = [ban_token_ids(eos_ids)]
sampler = make_sampler(
temp=task.temperature if task.temperature is not None else 0.7,
top_p=task.top_p if task.top_p is not None else 1.0,
)
max_tokens = task.max_tokens or MAX_TOKENS
for out in stream_generate(
model=model,
+3 -8
View File
@@ -3,11 +3,10 @@ import os
import resource
import time
from pathlib import Path
from typing import Any, Callable, cast
from typing import Any, cast
from mlx_lm.models.cache import KVCache, QuantizedKVCache, RotatingKVCache
from mlx_lm.models.deepseek_v3 import DeepseekV3Model
from mlx_lm.sample_utils import make_sampler
from mlx_lm.tokenizer_utils import TokenizerWrapper
from exo.worker.engines.mlx.constants import (
@@ -176,11 +175,7 @@ def initialize_mlx(
def load_mlx_items(
bound_instance: BoundInstance, group: Group | None
) -> tuple[Model, TokenizerWrapper, Callable[[mx.array], mx.array]]:
# TODO: pass temperature
sampler: Callable[[mx.array], mx.array] = make_sampler(temp=0.7)
logger.info("Created a sampler")
) -> tuple[Model, TokenizerWrapper]:
if group is None:
logger.info(f"Single device used for {bound_instance.instance}")
model_path = build_model_path(bound_instance.bound_shard.model_meta.model_id)
@@ -201,7 +196,7 @@ def load_mlx_items(
set_wired_limit_for_model(get_weights_size(bound_instance.bound_shard))
return cast(Model, model), tokenizer, sampler
return cast(Model, model), tokenizer
def shard_and_load(
+2 -7
View File
@@ -68,7 +68,6 @@ def main(
model = None
tokenizer = None
sampler = None
group = None
current_status: RunnerStatus = RunnerIdle()
@@ -110,14 +109,13 @@ def main(
)
)
model, tokenizer, sampler = load_mlx_items(bound_instance, group)
model, tokenizer = load_mlx_items(bound_instance, group)
current_status = RunnerLoaded()
logger.info("runner loaded")
case StartWarmup() if isinstance(current_status, RunnerLoaded):
assert model
assert tokenizer
assert sampler
current_status = RunnerWarmingUp()
logger.info("runner warming up")
event_sender.send(
@@ -130,7 +128,6 @@ def main(
toks = warmup_inference(
model=model,
tokenizer=tokenizer,
sampler=sampler,
# kv_prefix_cache=kv_prefix_cache, # supply for warmup-time prefix caching
)
logger.info(f"warmed up by generating {toks} tokens")
@@ -144,7 +141,6 @@ def main(
):
assert model
assert tokenizer
assert sampler
logger.info(f"received chat request: {str(task)[:500]}")
current_status = RunnerRunning()
logger.info("runner running")
@@ -160,7 +156,6 @@ def main(
for response in mlx_generate(
model=model,
tokenizer=tokenizer,
sampler=sampler,
task=task_params,
):
match response:
@@ -204,7 +199,7 @@ def main(
RunnerStatusUpdated(runner_id=runner_id, runner_status=current_status)
)
if isinstance(current_status, RunnerShutdown):
del model, tokenizer, group, sampler
del model, tokenizer, group
mx.clear_cache()
import gc
@@ -111,7 +111,7 @@ def assert_events_equal(test_events: Iterable[Event], true_events: Iterable[Even
def patch_out_mlx(monkeypatch: pytest.MonkeyPatch):
# initialize_mlx returns a "group" equal to 1
monkeypatch.setattr(mlx_runner, "initialize_mlx", make_nothin(1))
monkeypatch.setattr(mlx_runner, "load_mlx_items", make_nothin((1, 1, 1)))
monkeypatch.setattr(mlx_runner, "load_mlx_items", make_nothin((1, 1)))
monkeypatch.setattr(mlx_runner, "warmup_inference", make_nothin(1))
monkeypatch.setattr(mlx_runner, "_check_for_debug_prompts", nothin)