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[CI] fix port conflicts (#5789)

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This commit is contained in:
Lianmin Zheng
2025-04-27 05:17:44 -07:00
committed by GitHub
parent 3c4e0ee64d
commit 35ca04d2fa
7 changed files with 55 additions and 51 deletions
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6
.github/workflows/pr-test.yml vendored
View File

@@ -54,7 +54,7 @@ jobs:
strategy:
fail-fast: false
matrix:
part: [0, 1, 2, 3, 4, 5, 6]
part: [0, 1, 2, 3, 4, 5, 6, 7]
steps:
- name: Checkout code
uses: actions/checkout@v4
@@ -64,10 +64,10 @@ jobs:
bash scripts/ci_install_dependency.sh
- name: Run test
timeout-minutes: 40
timeout-minutes: 30
run: |
cd test/srt
python3 run_suite.py --suite per-commit --auto-partition-id ${{ matrix.part }} --auto-partition-size 7
python3 run_suite.py --suite per-commit --auto-partition-id ${{ matrix.part }} --auto-partition-size 8
unit-test-backend-2-gpu:
if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') &&

11
python/sglang/bench_serving.py
View File

@@ -977,6 +977,7 @@ async def benchmark(
profile: bool,
pd_seperated: bool = False,
flush_cache: bool = False,
warmup_requests: int = 1,
):
if backend in ASYNC_REQUEST_FUNCS:
request_func = ASYNC_REQUEST_FUNCS[backend]
@@ -993,10 +994,8 @@ async def benchmark(
async with semaphore:
return await request_func(request_func_input=request_func_input, pbar=pbar)
if not hasattr(args, "warmup_requests"):
args.warmup_requests = 1
# Warmup
print(f"Starting warmup with {args.warmup_requests} sequences...")
print(f"Starting warmup with {warmup_requests} sequences...")
# Use the first request for all warmup iterations
test_prompt, test_prompt_len, test_output_len = input_requests[0]
@@ -1018,7 +1017,7 @@ async def benchmark(
# Run warmup requests
warmup_tasks = []
for _ in range(args.warmup_requests):
for _ in range(warmup_requests):
warmup_tasks.append(
asyncio.create_task(request_func(request_func_input=test_input))
)
@@ -1026,9 +1025,7 @@ async def benchmark(
warmup_outputs = await asyncio.gather(*warmup_tasks)
# Check if at least one warmup request succeeded
if args.warmup_requests > 0 and not any(
output.success for output in warmup_outputs
):
if warmup_requests > 0 and not any(output.success for output in warmup_outputs):
raise ValueError(
"Warmup failed - Please make sure benchmark arguments "
f"are correctly specified. Error: {warmup_outputs[0].error}"

4
python/sglang/srt/entrypoints/http_server.py
View File

@@ -281,7 +281,9 @@ async def generate_from_file_request(file: UploadFile, request: Request):
)
try:
ret = await _global_state.generate_request(obj, request).__anext__()
ret = await _global_state.tokenizer_manager.generate_request(
obj, request
).__anext__()
return ret
except ValueError as e:
logger.error(f"Error: {e}")

1
python/sglang/test/test_utils.py
View File

@@ -8,7 +8,6 @@ import random
import subprocess
import threading
import time
import traceback
import unittest
from concurrent.futures import ThreadPoolExecutor
from dataclasses import dataclass

50
test/srt/run_suite.py
View File

@@ -14,7 +14,7 @@ class TestFile:
suites = {
"per-commit": [
TestFile("models/lora/test_lora.py", 76),
TestFile("models/lora/test_lora_backend.py", 420),
TestFile("models/lora/test_lora_backend.py", 99),
TestFile("models/lora/test_multi_lora_backend.py", 60),
TestFile("models/test_embedding_models.py", 35),
TestFile("models/test_generation_models.py", 103),
@@ -23,30 +23,30 @@ suites = {
TestFile("models/test_compressed_tensors_models.py", 100),
TestFile("models/test_reward_models.py", 83),
TestFile("models/test_gme_qwen_models.py", 45),
TestFile("models/test_clip_models.py", 100),
TestFile("models/test_vlm_models.py", 100),
TestFile("models/test_clip_models.py", 52),
TestFile("models/test_vlm_models.py", 581),
TestFile("test_abort.py", 51),
TestFile("test_block_int8.py", 22),
TestFile("test_chunked_prefill.py", 336),
TestFile("test_eagle_infer.py", 500),
TestFile("test_chunked_prefill.py", 285),
TestFile("test_eagle_infer.py", 584),
TestFile("test_ebnf_constrained.py"),
TestFile("test_fa3.py", 400),
TestFile("test_fa3.py", 376),
TestFile("test_fp8_kernel.py", 8),
TestFile("test_embedding_openai_server.py", 36),
TestFile("test_embedding_openai_server.py", 141),
TestFile("test_hidden_states.py", 55),
TestFile("test_int8_kernel.py", 8),
TestFile("test_input_embeddings.py", 38),
TestFile("test_json_constrained.py", 98),
TestFile("test_large_max_new_tokens.py", 41),
TestFile("test_metrics.py", 32),
TestFile("test_mla.py", 162),
TestFile("test_mla.py", 242),
TestFile("test_mla_deepseek_v3.py", 221),
TestFile("test_mla_int8_deepseek_v3.py", 522),
TestFile("test_mla_int8_deepseek_v3.py", 674),
TestFile("test_mla_flashinfer.py", 395),
TestFile("test_mla_fp8.py", 93),
TestFile("test_mla_fp8.py", 153),
TestFile("test_no_chunked_prefill.py", 126),
TestFile("test_no_overlap_scheduler.py", 262),
TestFile("test_openai_server.py", 186),
TestFile("test_openai_server.py", 149),
TestFile("test_penalty.py", 41),
TestFile("test_page_size.py", 60),
TestFile("test_pytorch_sampling_backend.py", 66),
@@ -57,11 +57,11 @@ suites = {
TestFile("test_request_length_validation.py", 31),
TestFile("test_retract_decode.py", 54),
TestFile("test_server_args.py", 1),
TestFile("test_skip_tokenizer_init.py", 72),
TestFile("test_skip_tokenizer_init.py", 117),
TestFile("test_srt_engine.py", 237),
TestFile("test_srt_endpoint.py", 94),
TestFile("test_torch_compile.py", 76),
TestFile("test_torch_compile_moe.py", 85),
TestFile("test_torch_compile_moe.py", 235),
TestFile("test_torch_native_attention_backend.py", 123),
TestFile("test_torchao.py", 70),
TestFile("test_triton_attention_kernels.py", 4),
@@ -69,27 +69,27 @@ suites = {
TestFile("test_update_weights_from_disk.py", 114),
TestFile("test_update_weights_from_tensor.py", 48),
TestFile("test_vertex_endpoint.py", 31),
TestFile("test_vision_chunked_prefill.py", 99),
TestFile("test_vision_chunked_prefill.py", 119),
TestFile("test_vlm_accuracy.py", 60),
TestFile("test_vision_openai_server.py", 537),
TestFile("test_vision_openai_server.py", 637),
TestFile("test_fim_completion.py", 40),
TestFile("test_w8a8_quantization.py", 46),
TestFile("test_eval_fp8_accuracy.py", 303),
TestFile("test_create_kvindices.py", 2),
TestFile("test_hicache.py", 60),
TestFile("test_hicache_mla.py", 90),
TestFile("test_hicache.py", 116),
TestFile("test_hicache_mla.py", 254),
TestFile("test_fused_moe.py", 30),
TestFile("test_triton_moe_channel_fp8_kernel.py", 25),
],
"per-commit-2-gpu": [
TestFile("models/lora/test_lora_tp.py", 150),
TestFile("test_data_parallelism.py", 90),
TestFile("test_dp_attention.py", 150),
TestFile("test_mla_tp.py", 174),
TestFile("test_moe_ep.py", 220),
TestFile("test_patch_torch.py", 30),
TestFile("test_update_weights_from_distributed.py", 100),
TestFile("test_verl_engine.py", 100),
TestFile("models/lora/test_lora_tp.py", 116),
TestFile("test_data_parallelism.py", 73),
TestFile("test_dp_attention.py", 137),
TestFile("test_mla_tp.py", 170),
TestFile("test_moe_ep.py", 181),
TestFile("test_patch_torch.py", 19),
TestFile("test_update_weights_from_distributed.py", 103),
TestFile("test_verl_engine.py", 64),
],
"per-commit-8-gpu": [
TestFile("test_local_attn.py", 250),

2
test/srt/test_torch_compile_moe.py
View File

@@ -24,7 +24,7 @@ class TestTorchCompileMoe(CustomTestCase):
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=["--enable-torch-compile", "--torch-compile-max-bs", "8"],
other_args=["--enable-torch-compile", "--torch-compile-max-bs", "4"],
)
@classmethod

32
test/srt/test_update_weights_from_distributed.py
View File

@@ -129,7 +129,7 @@ def init_process_hf(
hf_instruct_params = []
hf_base_params = []
print("get parameter in hf instruct model and base model")
print("[hf] get parameter in hf instruct model and base model")
for parameter_name in checking_parameters:
hf_instruct_params.append(
hf_instruct_model.get_parameter(parameter_name)[:truncate_size]
@@ -152,10 +152,12 @@ def init_process_hf(
param_queue.put(("hf_base_params", hf_base_params))
# Init weight update group for rank 0 (the training engine in RLHF).
print(f"rank {rank} world_size: {world_size} init custom process group")
port = 60000 + int(os.environ.get("CUDA_VISIBLE_DEVICES", "0")[0]) * 100
init_method = f"tcp://localhost:{port}"
print(f"[hf] {rank=} {world_size=} init custom process group. {init_method=}")
group = init_custom_process_group(
backend="nccl",
init_method="tcp://localhost:65500",
init_method=init_method,
world_size=world_size,
rank=rank,
group_name="test_parameter_update_group",
@@ -184,7 +186,7 @@ def init_process_hf(
# Measure the latency of broadcasting/weights update.
broadcast_time = time_end_broadcast - time_begin_broadcast
print(f"rank {rank} broadcast parameter time: {broadcast_time:.3f}s")
print(f"[hf] {rank=} {broadcast_time=:.3f}s")
param_queue.put(("broadcast_time", broadcast_time))
# Delete the huggingface models to free up memory.
@@ -210,17 +212,21 @@ def init_process_sgl(
torch.cuda.synchronize()
base_gpu_id = 1 if rank == 1 else 1 + tp_size
if backend == "Engine":
print(f"[sgl] rank {rank} init engine")
engine = sgl.Engine(
model_path=model_name,
random_seed=42,
base_gpu_id=base_gpu_id,
tp_size=tp_size,
cuda_graph_max_bs=2,
)
else:
if rank == 1:
url = DEFAULT_URL_FOR_TEST
else:
url = DEFAULT_URL_FOR_TEST.replace("2157", "2159")
host, port = DEFAULT_URL_FOR_TEST.split(":")
url = ":".join(host, str(int(port) + 10000))
print(f"[sgl] rank {rank} init server on url: {url}")
process = popen_launch_server(
model_name,
url,
@@ -230,13 +236,11 @@ def init_process_sgl(
str(base_gpu_id),
"--tp-size",
str(tp_size),
"--cuda-graph-max-bs",
2,
),
)
torch.cuda.synchronize()
if backend == "Engine":
print(f"rank {rank} init engine")
else:
print(f"rank {rank} init server on url: {url}")
# Get weights of instruct model, i.e. pre-training weights.
instruct_params = []
@@ -252,11 +256,13 @@ def init_process_sgl(
param_queue.put((f"sgl_dp_{rank}_instruct_params", instruct_params))
port = 60000 + int(os.environ.get("CUDA_VISIBLE_DEVICES", "0")[0]) * 100
# Init weight update group with the training engine.
if backend == "Engine":
engine.init_weights_update_group(
master_address="localhost",
master_port="65500",
master_port=str(port),
rank_offset=base_gpu_id,
world_size=world_size,
group_name="test_parameter_update_group",
@@ -267,7 +273,7 @@ def init_process_sgl(
f"{url}/init_weights_update_group",
json={
"master_address": "localhost",
"master_port": "65500",
"master_port": str(port),
"rank_offset": base_gpu_id,
"world_size": world_size,
"group_name": "test_parameter_update_group",
@@ -311,7 +317,7 @@ def init_process_sgl(
# Measure the latency of broadcast/weights update.
update_time = time_end_update - time_begin_update
print(
f"fully update model_name {model_name} rank {rank} parameter from distributed time: {update_time:.3f}s"
f"[sgl] fully update model_name {model_name} rank {rank} parameter from distributed time: {update_time:.3f}s"
)
param_queue.put((f"update_sgl_dp_{rank}_time", update_time))