mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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124 lines
5.4 KiB
Python
124 lines
5.4 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import pytest
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from defs.common import (convert_weights, generate_summary_cmd, venv_check_call,
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venv_mpi_check_call)
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from defs.conftest import get_sm_version, skip_post_blackwell
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from defs.trt_test_alternative import check_call
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# skip trt flow cases on post-Blackwell-Ultra
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if get_sm_version() >= 103:
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pytest.skip(
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"TRT workflow tests are not supported on post Blackwell-Ultra architecture",
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allow_module_level=True)
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@pytest.mark.parametrize("gemm_plugin", [True, False],
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ids=["enable_gemm_plugin", "disable_gemm_plugin"])
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@pytest.mark.parametrize("dtype", ['bfloat16', 'float16'])
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@pytest.mark.parametrize("mamba_model_root", [
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pytest.param('mamba-130m', marks=skip_post_blackwell), 'mamba-2.8b',
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'mamba-1.4b', 'mamba-790m', 'mamba-370m', 'mamba2-130m', 'mamba2-2.7b',
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'mamba2-1.3b', 'mamba2-780m', 'mamba2-370m',
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pytest.param('mamba-codestral-7B-v0.1', marks=skip_post_blackwell)
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],
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indirect=True)
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def test_llm_mamba_1gpu(mamba_example_root, mamba_model_root,
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llm_gptneox_model_root, llm_mathstral_model_root,
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llm_datasets_root, llm_rouge_root, llm_venv,
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gemm_plugin, dtype, cmodel_dir, engine_dir):
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"Build & Run mamba model with one gpu"
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print("Build engines...")
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model_name = os.path.basename(mamba_model_root)
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model_dir = convert_weights(llm_venv=llm_venv,
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example_root=mamba_example_root,
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cmodel_dir=cmodel_dir,
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model=model_name,
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model_path=mamba_model_root,
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data_type=dtype)
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build_cmd = [
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"trtllm-build",
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f"--checkpoint_dir={model_dir}",
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f"--output_dir={engine_dir}",
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"--paged_kv_cache=disable",
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"--max_batch_size=8",
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]
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if gemm_plugin:
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build_cmd.append("--gemm_plugin=auto")
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check_call(" ".join(build_cmd), shell=True, env=llm_venv._new_env)
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print(f'Run {model_name}...')
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tokenizer_dir = llm_mathstral_model_root if model_name == "mamba-codestral-7B-v0.1" else llm_gptneox_model_root
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summary_cmd = generate_summary_cmd(mamba_example_root,
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hf_model_dir=mamba_model_root,
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tokenizer_dir=tokenizer_dir,
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data_type=dtype,
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engine_dir=engine_dir,
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batch_size=8,
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tensorrt_llm_rouge1_threshold="13.5",
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dataset_dir=llm_datasets_root,
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rouge_dir=llm_rouge_root)
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venv_check_call(llm_venv, summary_cmd)
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@pytest.mark.parametrize("mamba_model_root", ['mamba-codestral-7B-v0.1'],
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indirect=True)
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def test_llm_mamba2_2gpu(mamba_example_root, mamba_model_root,
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llm_gptneox_model_root, llm_mathstral_model_root,
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llm_datasets_root, llm_rouge_root, llm_venv,
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cmodel_dir, engine_dir):
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"Build & Run mamba2 model with two gpus"
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print("Build engines...")
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model_name = mamba_model_root.split('/')[-1]
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model_dir = convert_weights(llm_venv=llm_venv,
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example_root=mamba_example_root,
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cmodel_dir=cmodel_dir,
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model=model_name,
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model_path=mamba_model_root,
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data_type='float16',
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tp_size=2)
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build_cmd = [
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"trtllm-build",
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"--gemm_plugin=auto",
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f"--checkpoint_dir={model_dir}",
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f"--output_dir={engine_dir}",
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"--paged_kv_cache=disable",
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"--max_batch_size=8",
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]
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check_call(" ".join(build_cmd), shell=True, env=llm_venv._new_env)
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print(f'Run {model_name}...')
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tokenizer_dir = llm_mathstral_model_root
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summary_cmd = generate_summary_cmd(mamba_example_root,
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hf_model_dir=mamba_model_root,
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tokenizer_dir=tokenizer_dir,
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data_type='float16',
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engine_dir=engine_dir,
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batch_size=8,
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tensorrt_llm_rouge1_threshold="19.0",
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dataset_dir=llm_datasets_root,
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rouge_dir=llm_rouge_root)
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venv_mpi_check_call(llm_venv, ["mpirun", "-n", "2", "--allow-run-as-root"],
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summary_cmd)
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