TensorRT-LLMs/tests/integration/defs/deterministic/test_mixtral_deterministic.py
Kaiyu Xie 2631f21089
Update (#2978)
Signed-off-by: Kaiyu Xie <26294424+kaiyux@users.noreply.github.com>
2025-03-23 16:39:35 +08:00

82 lines
3.1 KiB
Python

# SPDX-FileCopyrightText: Copyright (c) 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 pytest
from defs.common import (convert_weights, generate_deterministic_cmd,
venv_mpi_check_call)
from defs.conftest import skip_pre_hopper
from defs.trt_test_alternative import check_call
@skip_pre_hopper
@pytest.mark.skip_less_device(4)
@pytest.mark.skip_less_device_memory(80000)
@pytest.mark.parametrize("data_type", ['float16', 'bfloat16'])
@pytest.mark.parametrize("llm_mixtral_model_root",
['Mixtral-8x7B-Instruct-v0.1'],
indirect=True)
def test_llm_mixtral_4gpus_deterministic(llama_example_root,
llm_mixtral_model_root,
deterministic_test_root, llm_venv,
cmodel_dir, engine_dir, data_type):
tp_size, pp_size = 4, 1
world_size = tp_size * pp_size
moe_tp_size = tp_size
os.environ['FORCE_DETERMINISTIC'] = "1"
print("Convert checkpoint...")
ckpt_dir = convert_weights(llm_venv=llm_venv,
example_root=llama_example_root,
cmodel_dir=cmodel_dir,
model="mixtral-instruct",
model_path=llm_mixtral_model_root,
tp_size=tp_size,
moe_tp_size=moe_tp_size,
pp_size=pp_size,
data_type=data_type,
workers=world_size)
print("Build engines...")
build_cmd = [
"trtllm-build",
f"--checkpoint_dir={ckpt_dir}",
f"--output_dir={engine_dir}",
f"--workers={world_size}",
"--use_paged_context_fmha=enable",
"--max_batch_size=256",
"--max_num_tokens=33280",
]
check_call(" ".join(build_cmd), shell=True, env=llm_venv._new_env)
print("Run deterministic test...")
deterministic_accuracy_threshold = 1
payload = os.path.join(deterministic_test_root, "payload.json")
deterministic_cmd = generate_deterministic_cmd(
deterministic_test_root,
engine_dir=engine_dir,
tokenizer_dir=llm_mixtral_model_root,
payload=payload,
deterministic_accuracy_threshold=deterministic_accuracy_threshold)
venv_mpi_check_call(
llm_venv, ["mpirun", "-n", f"{world_size}", "--allow-run-as-root"],
deterministic_cmd)
os.environ.pop('FORCE_DETERMINISTIC', None)