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https://github.com/NVIDIA/TensorRT-LLM.git
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f430a4b447
* Update TensorRT-LLM --------- Co-authored-by: IbrahimAmin <ibrahimamin532@gmail.com> Co-authored-by: Fabian Joswig <fjosw@users.noreply.github.com> Co-authored-by: Pzzzzz <hello-cd.plus@hotmail.com> Co-authored-by: CoderHam <hemant@cohere.com> Co-authored-by: Konstantin Lopuhin <kostia.lopuhin@gmail.com>
73 lines
1.9 KiB
Python
73 lines
1.9 KiB
Python
import json
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import os
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import sys
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import tempfile
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import time
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from pathlib import Path
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from tensorrt_llm.hlapi._perf_evaluator import (LLMPerfEvaluator,
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MemoryContinuousMonitorThread)
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from tensorrt_llm.hlapi.llm import KvCacheConfig, ModelConfig
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sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
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from utils.llm_data import llm_models_root
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from utils.util import force_ampere
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def get_model_path(model_name):
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return str(llm_models_root() / model_name)
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llama_model_path = get_model_path("llama-models/llama-7b-hf")
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def test_memory_thread():
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thread = MemoryContinuousMonitorThread(0.5)
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thread.start()
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time.sleep(3)
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thread.stop()
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print(thread.memory_samples)
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print('max', thread.memory_samples.get_max())
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print('min', thread.memory_samples.get_min())
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print('ave', thread.memory_samples.get_average())
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def gen_fake_samples(samples_path: str, num_samples: int, sample_length: int):
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data = {
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"samples": [{
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"input_ids": [20] * sample_length,
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"output_len": sample_length
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} for _ in range(num_samples)]
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}
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with open(samples_path, "w") as f:
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json.dump(data, f)
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@force_ampere
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def test_perf_evaluator():
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config = ModelConfig(llama_model_path)
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with tempfile.TemporaryDirectory() as temp_dir:
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workspace = Path(temp_dir)
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samples_path = workspace / "data.json"
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gen_fake_samples(samples_path, 10, 5)
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# try to set some flags
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kvcache_config = KvCacheConfig(enable_block_reuse=True)
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evaluator = LLMPerfEvaluator.create(
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config,
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num_samples=10,
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samples_path=samples_path,
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warmup=10,
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kv_cache_config=kvcache_config,
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)
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assert evaluator
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report = evaluator.run()
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report.display()
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report.save_json(workspace / "report.json")
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if __name__ == '__main__':
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test_perf_evaluator()
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