TensorRT-LLMs/tests/integration/defs/examples/test_commandr.py

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"""Module test_commandr test commandr examples."""
import os

import pytest
from defs.common import (convert_weights, generate_summary_cmd, venv_check_call,
                         venv_mpi_check_call)
from defs.conftest import get_gpu_device_list
from defs.trt_test_alternative import check_call


@pytest.mark.skip_less_device_memory(80000)
@pytest.mark.parametrize("use_weight_only", [True, False],
                         ids=["enable_weight_only", "disable_weight_only"])
def test_llm_commandr_v01_single_gpu_summary(commandr_example_root,
                                             llm_commandr_v01_model_root,
                                             llm_datasets_root, llm_rouge_root,
                                             llm_venv, cmodel_dir, engine_dir,
                                             use_weight_only):
    "Build & run commandr_v01 on single gpu."
    if "GH200" in get_gpu_device_list()[0] and not use_weight_only:
        pytest.skip("OOM on GH200. https://nvbugs/5250460")

    print("Converting checkpoint...")
    dtype = 'float16'
    model_name = os.path.basename(llm_commandr_v01_model_root)
    ckpt_dir = convert_weights(llm_venv=llm_venv,
                               example_root=commandr_example_root,
                               cmodel_dir=cmodel_dir,
                               model=model_name,
                               model_path=llm_commandr_v01_model_root,
                               data_type=dtype,
                               use_weight_only=use_weight_only)

    print("Building engines...")
    build_cmd = [
        "trtllm-build",
        f"--checkpoint_dir={ckpt_dir}",
        f"--output_dir={engine_dir}",
        f"--max_batch_size={8}",
        f"--max_input_len={924}",
        f"--max_seq_len={1024}",
        f"--gemm_plugin={dtype}",
        f"--gpt_attention_plugin={dtype}",
    ]

    check_call(" ".join(build_cmd), shell=True, env=llm_venv._new_env)

    summary_cmd = [
        f"{commandr_example_root}/../../../summarize.py",
        "--test_trt_llm",
        "--hf_model_dir",
        f"{llm_commandr_v01_model_root}",
        "--data_type",
        "fp16",
        "--check_accuracy",
        f"--engine_dir={engine_dir}",
        "--tensorrt_llm_rouge1_threshold=12",
        f"--dataset_dir={llm_datasets_root}",
        f"--rouge_dir={llm_rouge_root}",
    ]

    venv_check_call(llm_venv, summary_cmd)


@pytest.mark.skip_less_device(4)
@pytest.mark.skip_less_device_memory(80000)
@pytest.mark.skip_less_host_memory(1000000)
@pytest.mark.parametrize("use_weight_only", [True, False],
                         ids=["enable_weight_only", "disable_weight_only"])
def test_llm_commandr_plus_4gpus_summary(commandr_example_root,
                                         llm_commandr_plus_model_root,
                                         llm_datasets_root, llm_rouge_root,
                                         llm_venv, cmodel_dir, engine_dir,
                                         use_weight_only):
    "Build & run Command-R+ with smoothquant on 4 gpus."
    dtype = 'float16'
    tp_size = 4
    model_name = os.path.basename(llm_commandr_plus_model_root)
    print("Converting checkpoint...")
    ckpt_dir = convert_weights(llm_venv=llm_venv,
                               example_root=commandr_example_root,
                               cmodel_dir=cmodel_dir,
                               model=model_name,
                               model_path=llm_commandr_plus_model_root,
                               data_type=dtype,
                               tp_size=tp_size,
                               gpus=tp_size,
                               use_weight_only=use_weight_only)

    print("Building engines...")
    build_cmd = [
        "trtllm-build",
        f"--checkpoint_dir={ckpt_dir}",
        f"--output_dir={engine_dir}",
        f"--max_batch_size={8}",
        f"--max_input_len={924}",
        f"--max_seq_len={1024}",
        f"--max_beam_width={4}",
        f"--gemm_plugin={dtype}",
        f"--gpt_attention_plugin={dtype}",
    ]

    run_cmd = [
        f"{commandr_example_root}/../../../run.py",
        f"--max_output_len={50}",
        f"--tokenizer_dir={llm_commandr_plus_model_root}",
        f"--engine_dir={engine_dir}",
    ]

    check_call(" ".join(build_cmd), shell=True, env=llm_venv._new_env)

    venv_mpi_check_call(
        llm_venv,
        ["mpirun", "-n", str(tp_size), "--allow-run-as-root"], run_cmd)

    summary_cmd = generate_summary_cmd(
        commandr_example_root,
        hf_model_dir=llm_commandr_plus_model_root,
        data_type="fp16",
        engine_dir=engine_dir,
        dataset_dir=llm_datasets_root,
        rouge_dir=llm_rouge_root)

    venv_mpi_check_call(
        llm_venv,
        ["mpirun", "-n", str(tp_size), "--allow-run-as-root"], summary_cmd)