TensorRT-LLMs/tests/integration/defs/disaggregated/test_disaggregated.py
Zheng Duan 54200ee8ac
fix: random fail of cache router test (#4597)
Signed-off-by: Zheng Duan <200704041+zhengd-nv@users.noreply.github.com>
2025-05-30 16:28:19 +08:00

760 lines
30 KiB
Python

# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import subprocess
import pytest
from defs.conftest import skip_no_hopper
from defs.trt_test_alternative import check_call, popen
from tensorrt_llm.logger import logger
def cleanup_output_files():
"""Clean up output files from previous runs."""
for file in ['output.json', 'output_streaming.json']:
try:
os.remove(file)
except FileNotFoundError:
pass
def get_test_config(test_desc, example_dir, test_root):
"""Get test configuration based on test description."""
test_configs_root = f"{test_root}/test_configs"
config_map = {
"2_ranks": (2, f"{example_dir}/disagg_config.yaml"),
"2_ranks_trt_backend":
(2, f"{test_configs_root}/disagg_config_trt_backend.yaml"),
"gen_only": (2, f"{test_configs_root}/disagg_config_gen_only.yaml"),
"gen_only_trt_backend":
(2, f"{test_configs_root}/disagg_config_gen_only_trt_backend.yaml"),
"4_ranks": (4, f"{test_configs_root}/disagg_config_ctxtp2_gentp1.yaml"),
"4_ranks_trt_backend":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp1_trt_backend.yaml"),
"cuda_graph":
(2, f"{test_configs_root}/disagg_config_cuda_graph_padding.yaml"),
"mixed": (2, f"{test_configs_root}/disagg_config_mixed.yaml"),
"overlap": (2, f"{test_configs_root}/disagg_config_overlap.yaml"),
"load_balance":
(4, f"{test_configs_root}/disagg_config_load_balance.yaml"),
"cache_aware_balance":
(4, f"{test_configs_root}/disagg_config_cache_aware_balance.yaml"),
"conditional": (2,
f"{test_configs_root}/disagg_config_conditional.yaml"),
"deepseek_v3_lite_fp8":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp2_deepseek_v3_lite.yaml"
),
"deepseek_v3_lite_fp8_tp1":
(2,
f"{test_configs_root}/disagg_config_ctxtp1_gentp1_deepseek_v3_lite.yaml"
),
"deepseek_v3_lite_fp8_tp1_mtp":
(2,
f"{test_configs_root}/disagg_config_ctxtp1_gentp1_deepseek_v3_lite_one_mtp.yaml"
),
"deepseek_v3_lite_fp_8_overlap_dp":
(2,
f"{test_configs_root}/disagg_config_ctxtp1_gentp1_deepseek_v3_lite_overlap_dp.yaml"
),
"deepseek_v3_lite_fp8_attention_dp":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp2_deepseek_v3_lite_attention_dp.yaml"
),
"deepseek_v3_lite_fp_8_attention_dp_overlap":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp2_deepseek_v3_lite_attention_dp_overlap.yaml"
),
"deepseek_v3_lite_fp8_attention_dp_overlap_cuda_graph":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp2_deepseek_v3_lite_attention_dp_overlap_cuda_graph.yaml"
),
"deepseek_v3_lite_fp8_overlap_cuda_graph":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp2_deepseek_v3_lite_overlap_cuda_graph.yaml"
),
"deepseek_v3_lite_fp8_attention_dp_one":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp2_deepseek_v3_lite_attention_dp_one.yaml"
),
"deepseek_v3_lite_fp8_attention_dp_one_mtp":
(4,
f"{test_configs_root}/disagg_config_ctxtp2_gentp2_deepseek_v3_lite_attention_dp_one_mtp.yaml"
),
"deepseek_v3_lite_fp8_tp1_attention_dp_overlap_one_mtp":
(2,
f"{test_configs_root}/disagg_config_ctxtp1_gentp1_deepseek_v3_lite_one_mtp_attention_dp_overlap.yaml"
),
}
if test_desc not in config_map:
raise ValueError(f"Invalid test description: {test_desc}, "
f"valid descriptions are: {config_map.keys()}")
return config_map[test_desc]
def run_disaggregated_test(example_dir,
test_desc,
num_iters=5,
env=None,
cwd=None):
"""Run disaggregated test with given configuration."""
cleanup_output_files()
num_ranks, config_file = get_test_config(test_desc, example_dir,
os.path.dirname(__file__))
workers_cmd = [
'mpirun', '--allow-run-as-root', '--oversubscribe', '-n',
str(num_ranks), 'trtllm-serve', 'disaggregated_mpi_worker', '-c',
config_file
]
server_start_timeout = 900
server_cmd = [
'trtllm-serve', 'disaggregated', '--server_start_timeout',
str(server_start_timeout), '-c', config_file
]
try:
with ( # Start workers
open('output_workers.log', 'w') as output_workers,
popen(workers_cmd,
stdout=output_workers,
stderr=subprocess.STDOUT,
env=env,
cwd=cwd),
# Start server
open('output_disagg.log', 'w') as output_disagg,
popen(server_cmd,
stdout=output_disagg,
stderr=subprocess.STDOUT,
env=env,
cwd=cwd)):
client_dir = f"{example_dir}/clients"
for _ in range(num_iters):
client_cmd = [
'python3', f'{client_dir}/disagg_client.py', '-c',
f'{example_dir}/disagg_config.yaml', '-p',
f'{client_dir}/prompts.json', '--ignore-eos',
'--server-start-timeout',
str(server_start_timeout)
]
check_call(client_cmd, env=env)
# Streaming client run
streaming_client_cmd = client_cmd + [
'--streaming', '-o', 'output_streaming.json'
]
check_call(streaming_client_cmd, env=env)
# Run the chat completion endpoint test only for TinyLlama
if test_desc == "overlap":
chat_client_cmd = client_cmd + [
'-e', 'chat', '-o', 'output_chat.json'
]
check_call(chat_client_cmd, env=env)
streaming_chat_client_cmd = chat_client_cmd + [
'--streaming', '-o', 'output_streaming_chat.json'
]
check_call(streaming_chat_client_cmd, env=env)
# Verify outputs
not_expected_strings = ["Berlin Berlin"]
output_files = ['output.json', 'output_streaming.json']
if test_desc == "overlap":
# Disable streaming chat completion for overlap test
# due to bug
output_files.extend(['output_chat.json'])
if test_desc.startswith("gen_only"):
continue
for output_file in output_files:
with open(output_file, 'r') as f:
content = f.read()
if "deepseek_v3_lite" in test_desc or output_file == "output_chat.json":
expected_strings = ["Berlin", "Asyncio is a"]
else:
expected_strings = [
"The capital of Germany is Berlin",
"Asyncio is a Python library"
]
for expected_string in expected_strings:
assert expected_string in content, f"Expected string '{expected_string}' not found in {output_file}"
for not_expected_string in not_expected_strings:
assert not_expected_string not in content, f"Unexpected string '{not_expected_string}' found in {output_file}"
except Exception:
# Print outputs on error
logger.error("-------- Workers output --------")
with open('output_workers.log', 'r') as f:
logger.error(f.read())
logger.error("-------- Disagg server output --------")
with open('output_disagg.log', 'r') as f:
logger.error(f.read())
raise
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_single_gpu_with_mpirun(disaggregated_test_root,
disaggregated_example_root,
llm_venv, llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"2_ranks",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_single_gpu_with_mpirun_trt_backend(
disaggregated_test_root, disaggregated_example_root, llm_venv,
llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"2_ranks_trt_backend",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_benchmark_gen_only(disaggregated_test_root,
disaggregated_example_root, llm_venv,
llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
env = llm_venv._new_env.copy()
env['TRTLLM_DISAGG_BENCHMARK_GEN_ONLY'] = '1'
run_disaggregated_test(disaggregated_example_root,
"gen_only",
env=env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_benchmark_gen_only_trt_backend(
disaggregated_test_root, disaggregated_example_root, llm_venv,
llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
env = llm_venv._new_env.copy()
env['TRTLLM_DISAGG_BENCHMARK_GEN_ONLY'] = '1'
run_disaggregated_test(disaggregated_example_root,
"gen_only_trt_backend",
env=env,
cwd=llm_venv.get_working_directory())
@pytest.mark.skip_less_device(2)
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_multi_gpu_with_mpirun(disaggregated_test_root,
disaggregated_example_root,
llm_venv, llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"4_ranks",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.skip_less_device(2)
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_multi_gpu_with_mpirun_trt_backend(
disaggregated_test_root, disaggregated_example_root, llm_venv,
llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"4_ranks_trt_backend",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_cuda_graph(disaggregated_test_root, llm_venv,
disaggregated_example_root, llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"cuda_graph",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_mixed(disaggregated_test_root, llm_venv,
disaggregated_example_root, llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"mixed",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_overlap(disaggregated_test_root, llm_venv,
disaggregated_example_root, llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"overlap",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_load_balance(disaggregated_test_root, llm_venv,
disaggregated_example_root,
llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"load_balance",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_cache_aware_balance(disaggregated_test_root, llm_venv,
disaggregated_example_root,
llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"cache_aware_balance",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@pytest.mark.parametrize("llama_model_root", ['TinyLlama-1.1B-Chat-v1.0'],
indirect=True)
def test_disaggregated_conditional(disaggregated_test_root, llm_venv,
disaggregated_example_root,
llama_model_root):
src_dst_dict = {
llama_model_root:
f"{llm_venv.get_working_directory()}/TinyLlama/TinyLlama-1.1B-Chat-v1.0",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"conditional",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8(disaggregated_test_root,
disaggregated_example_root,
llm_venv, deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_tp1_single_gpu(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8_tp1",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_tp1_single_gpu_mtp(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8_tp1_mtp",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_ucx(disaggregated_test_root,
disaggregated_example_root,
llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
env = llm_venv._new_env.copy()
env["TRTLLM_USE_UCX_KVCACHE"] = "1"
env["UCX_TLS"] = "^ib"
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8",
env=env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_nixl(disaggregated_test_root,
disaggregated_example_root,
llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
env = llm_venv._new_env.copy()
env["TRTLLM_USE_NIXL_KVCACHE"] = "1"
env["UCX_TLS"] = "^ib"
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8",
env=env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_ucx_tp1_single_gpu(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
env = llm_venv._new_env.copy()
env["TRTLLM_USE_UCX_KVCACHE"] = "1"
env["UCX_TLS"] = "^ib"
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8_tp1",
env=env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_attention_dp(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8_attention_dp",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_attention_dp_overlap(
disaggregated_test_root, llm_venv, disaggregated_example_root,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp_8_attention_dp_overlap",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_attention_dp_overlap_cuda_graph(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(
disaggregated_example_root,
"deepseek_v3_lite_fp8_attention_dp_overlap_cuda_graph",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_overlap_cuda_graph(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8_overlap_cuda_graph",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_attention_dp_one(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8_attention_dp_one",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_attention_dp_one_mtp(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(disaggregated_example_root,
"deepseek_v3_lite_fp8_attention_dp_one_mtp",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())
@skip_no_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'],
indirect=True)
def test_disaggregated_deepseek_v3_lite_fp8_tp1_attention_dp_overlap_one_mtp(
disaggregated_test_root, disaggregated_example_root, llm_venv,
deepseek_v3_model_root):
src_dst_dict = {
deepseek_v3_model_root:
f"{llm_venv.get_working_directory()}/DeepSeek-V3-Lite/fp8",
}
for src, dst in src_dst_dict.items():
if not os.path.islink(dst):
os.makedirs(os.path.dirname(dst), exist_ok=True)
os.symlink(src, dst, target_is_directory=True)
run_disaggregated_test(
disaggregated_example_root,
"deepseek_v3_lite_fp8_tp1_attention_dp_overlap_one_mtp",
env=llm_venv._new_env,
cwd=llm_venv.get_working_directory())