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51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
import os
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import sys
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from tensorrt_llm.hlapi.llm import LLM, SamplingParams
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from tensorrt_llm.hlapi.llm_utils import CalibConfig, QuantAlgo, QuantConfig
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sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
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from utils.util import skip_pre_ampere, skip_pre_hopper
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try:
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from .test_llm import cnn_dailymail_path, llama_model_path
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except ImportError:
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from test_llm import cnn_dailymail_path, llama_model_path
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@skip_pre_ampere
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def test_llm_int4_awq_quantization():
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quant_config = QuantConfig(quant_algo=QuantAlgo.W4A16_AWQ)
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assert quant_config.quant_mode.has_any_quant()
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calib_config = CalibConfig(calib_dataset=cnn_dailymail_path)
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llm = LLM(llama_model_path,
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quant_config=quant_config,
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calib_config=calib_config)
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sampling_params = SamplingParams(max_tokens=6)
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for output in llm.generate(["A B C"], sampling_params=sampling_params):
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print(output)
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assert output.outputs[0].text == "D E F G H I"
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@skip_pre_hopper
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def test_llm_fp8_quantization():
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quant_config = QuantConfig(quant_algo=QuantAlgo.FP8,
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kv_cache_quant_algo=QuantAlgo.FP8)
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assert quant_config.quant_mode.has_any_quant()
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calib_config = CalibConfig(calib_dataset=cnn_dailymail_path)
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llm = LLM(llama_model_path,
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quant_config=quant_config,
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calib_config=calib_config)
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sampling_params = SamplingParams(max_tokens=6)
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for output in llm.generate(["A B C"], sampling_params=sampling_params):
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print(output)
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assert output.outputs[0].text == "D E F G H I"
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if __name__ == "__main__":
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test_llm_int4_awq_quantization()
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test_llm_fp8_quantization()
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