"torchvision/vscode:/vscode.git/clone" did not exist on "0c75d99d59bbc8e22e9dc40469c5b4ec1d742f03"
Unverified Commit 26f07294 authored by fzyzcjy's avatar fzyzcjy Committed by GitHub
Browse files

Warn users when release_memory_occupation is called without memory saver enabled (#4566)

parent 34e07a65
......@@ -22,7 +22,7 @@ concurrency:
jobs:
accuracy-test-1-gpu-amd:
if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') &&
github.event.pull_request.draft == false
github.event.pull_request.draft == false
runs-on: linux-mi300-gpu-1
steps:
- name: Checkout code
......@@ -56,13 +56,13 @@ jobs:
- name: Evaluate Accuracy
timeout-minutes: 20
run: |
docker exec -w /sglang-checkout/test/srt ci_sglang python3 test_eval_accuracy_large.py
docker exec -w /sglang-checkout/test/srt ci_sglang python3 test_eval_fp8_accuracy.py
docker exec -w /sglang-checkout/test/srt ci_sglang python3 models/test_qwen_models.py
docker exec -w /sglang-checkout/test/srt -e SGLANG_IS_IN_CI=1 ci_sglang python3 test_eval_accuracy_large.py
docker exec -w /sglang-checkout/test/srt -e SGLANG_IS_IN_CI=1 ci_sglang python3 test_eval_fp8_accuracy.py
docker exec -w /sglang-checkout/test/srt -e SGLANG_IS_IN_CI=1 ci_sglang python3 models/test_qwen_models.py
mla-test-1-gpu-amd:
if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') &&
github.event.pull_request.draft == false
github.event.pull_request.draft == false
runs-on: linux-mi300-gpu-1
steps:
- name: Checkout code
......@@ -96,7 +96,7 @@ jobs:
- name: MLA TEST
timeout-minutes: 20
run: |
docker exec -w /sglang-checkout/test/srt ci_sglang python3 test_mla.py
docker exec -w /sglang-checkout/test/srt -e SGLANG_IS_IN_CI=1 ci_sglang python3 test_mla.py
finish:
if: always()
......
......@@ -33,7 +33,7 @@ jobs:
pip install -r docs/requirements.txt
apt-get update
apt-get install -y pandoc
apt-get update && apt-get install -y parallel
apt-get update && apt-get install -y parallel retry
- name: Setup Jupyter Kernel
run: |
......
......@@ -72,7 +72,7 @@ srt_cpu = ["sglang[runtime_common]", "outlines>=0.0.44,<=0.1.11", "torch"]
openai = ["openai>=1.0", "tiktoken"]
anthropic = ["anthropic>=0.20.0"]
litellm = ["litellm>=1.0.0"]
torch_memory_saver = ["torch_memory_saver"]
torch_memory_saver = ["torch_memory_saver>=0.0.3"]
test = [
"jsonlines",
"matplotlib",
......
......@@ -1790,6 +1790,9 @@ class Scheduler(
return GetWeightsByNameReqOutput(parameter)
def release_memory_occupation(self, recv_req: ReleaseMemoryOccupationReqInput):
self.memory_saver_adapter.check_validity(
caller_name="release_memory_occupation"
)
self.stashed_model_static_state = _export_static_state(
self.tp_worker.worker.model_runner.model
)
......@@ -1798,6 +1801,7 @@ class Scheduler(
return ReleaseMemoryOccupationReqOutput()
def resume_memory_occupation(self, recv_req: ResumeMemoryOccupationReqInput):
self.memory_saver_adapter.check_validity(caller_name="resume_memory_occupation")
self.memory_saver_adapter.resume()
_import_static_state(
self.tp_worker.worker.model_runner.model, self.stashed_model_static_state
......
......@@ -287,7 +287,14 @@ class ModelRunner:
def init_torch_distributed(self):
logger.info("Init torch distributed begin.")
torch.get_device_module(self.device).set_device(self.gpu_id)
try:
torch.get_device_module(self.device).set_device(self.gpu_id)
except Exception:
logger.warning(
f"Context: {self.device=} {self.gpu_id=} {os.environ.get('CUDA_VISIBLE_DEVICES')=} {self.tp_rank=} {self.tp_size=}"
)
raise
if self.device == "cuda":
backend = "nccl"
elif self.device == "xpu":
......
import logging
from abc import ABC
from contextlib import contextmanager
......@@ -8,6 +9,8 @@ try:
except ImportError:
pass
logger = logging.getLogger(__name__)
class TorchMemorySaverAdapter(ABC):
@staticmethod
......@@ -16,6 +19,13 @@ class TorchMemorySaverAdapter(ABC):
_TorchMemorySaverAdapterReal() if enable else _TorchMemorySaverAdapterNoop()
)
def check_validity(self, caller_name):
if not self.enabled:
logger.warning(
f"`{caller_name}` will not save memory because torch_memory_saver is not enabled. "
f"Potential causes: `enable_memory_saver` is false, or torch_memory_saver has installation issues."
)
def configure_subprocess(self):
raise NotImplementedError
......@@ -28,6 +38,10 @@ class TorchMemorySaverAdapter(ABC):
def resume(self):
raise NotImplementedError
@property
def enabled(self):
raise NotImplementedError
class _TorchMemorySaverAdapterReal(TorchMemorySaverAdapter):
def configure_subprocess(self):
......@@ -42,6 +56,10 @@ class _TorchMemorySaverAdapterReal(TorchMemorySaverAdapter):
def resume(self):
return _primary_memory_saver.resume()
@property
def enabled(self):
return _primary_memory_saver.enabled
class _TorchMemorySaverAdapterNoop(TorchMemorySaverAdapter):
@contextmanager
......@@ -57,3 +75,7 @@ class _TorchMemorySaverAdapterNoop(TorchMemorySaverAdapter):
def resume(self):
pass
@property
def enabled(self):
return False
......@@ -6,6 +6,7 @@ from sglang.srt.layers.attention.flashattention_backend import FlashAttentionBac
from sglang.srt.layers.radix_attention import RadixAttention
from sglang.srt.mem_cache.memory_pool import MHATokenToKVPool
from sglang.srt.model_executor.forward_batch_info import ForwardBatch, ForwardMode
from sglang.test.test_utils import CustomTestCase
class MockModelRunner:
......@@ -39,7 +40,7 @@ class MockReqToTokenPool:
@unittest.skipIf(not torch.cuda.is_available(), "Test requires CUDA")
class TestFlashAttentionBackend(unittest.TestCase):
class TestFlashAttentionBackend(CustomTestCase):
def setUp(self):
"""Set up test fixtures before each test method."""
self.model_runner = MockModelRunner()
......
......@@ -3,6 +3,7 @@
import argparse
import asyncio
import copy
import logging
import os
import random
import subprocess
......@@ -922,6 +923,10 @@ def run_mulit_request_test(
def write_github_step_summary(content):
if not os.environ.get("GITHUB_STEP_SUMMARY"):
logging.warning("GITHUB_STEP_SUMMARY environment variable not set")
return
with open(os.environ["GITHUB_STEP_SUMMARY"], "a") as f:
f.write(content)
......
......@@ -46,7 +46,7 @@ class TestMLADeepseekV3ChannelInt8(CustomTestCase):
metrics = run_eval_few_shot_gsm8k(args)
print(metrics)
self.assertGreater(metrics["accuracy"], 0.62)
self.assertGreaterEqual(metrics["accuracy"], 0.61)
class TestDeepseekV3MTPChannelInt8(CustomTestCase):
......
......@@ -624,7 +624,6 @@ class TestMinicpmoServer(TestOpenAIVisionServer):
"minicpmo",
"--mem-fraction-static",
"0.7",
"--tp=2",
],
)
cls.base_url += "/v1"
......
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