TensorRT-LLMs/tests/integration/defs/test_cache.py
nv-guomingz ec4f43a0ab
test:remove opt/mpt/gptj/gptneox/bloom/falcon/baichuan/internlm/deep_… (#2987)
* test:remove opt/mpt/gptj/gptneox/bloom/falcon/baichuan/internlm/deep_seek_v2 test cases.

Signed-off-by: nv-guomingz <37257613+nv-guomingz@users.noreply.github.com>

* updatet test case per review comments

Signed-off-by: nv-guomingz <37257613+nv-guomingz@users.noreply.github.com>

---------

Signed-off-by: nv-guomingz <37257613+nv-guomingz@users.noreply.github.com>
Co-authored-by: nv-guomingz <37257613+nv-guomingz@users.noreply.github.com>
2025-03-24 14:18:06 +08:00

41 lines
1.5 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.
'''
Test LLM_MODELS_ROOT has correct data for misc test fixture
'''
import pytest
from .conftest import llm_models_root
@pytest.mark.skipif(llm_models_root() is None,
reason="no need to check the cache if its not set")
def test_cache_sanity(
gpt_next_root,
llm_gpt2_model_root,
llm_gpt2_medium_model_root,
llm_gpt2_next_model_root,
llm_gpt2_santacoder_model_root,
llm_gpt2_starcoder_model_root,
llm_gpt2_starcoder2_model_root,
llm_gpt2_next_8b_model_root,
llm_chatglm_6b_model_root,
llm_glm_10b_model_root,
llm_qwen_7b_model_root,
):
# use this test to be a placeholder to trigger the execution of all the test fixture
# and this is only executed when the LLM_MODELS_ROOT is set, so it will not trigger any download of the models
pass