diff --git a/tensorrt_llm/serve/scripts/__init__.py b/tensorrt_llm/serve/scripts/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tensorrt_llm/serve/scripts/benchmark_dataset.py b/tensorrt_llm/serve/scripts/benchmark_dataset.py index ab7f45e893..59ce5d045b 100644 --- a/tensorrt_llm/serve/scripts/benchmark_dataset.py +++ b/tensorrt_llm/serve/scripts/benchmark_dataset.py @@ -26,10 +26,11 @@ from typing import Any, Callable, Optional, Union import numpy as np import pandas as pd -from benchmark_utils import download_and_cache_file from datasets import load_dataset from transformers import PreTrainedTokenizerBase +from .benchmark_utils import download_and_cache_file + logger = logging.getLogger(__name__) # ----------------------------------------------------------------------------- diff --git a/tensorrt_llm/serve/scripts/benchmark_serving.py b/tensorrt_llm/serve/scripts/benchmark_serving.py index fb41378977..13df3eeab1 100644 --- a/tensorrt_llm/serve/scripts/benchmark_serving.py +++ b/tensorrt_llm/serve/scripts/benchmark_serving.py @@ -31,18 +31,19 @@ from datetime import datetime from typing import Any, Optional import numpy as np -from backend_request_func import (ASYNC_REQUEST_FUNCS, - OPENAI_COMPATIBLE_BACKENDS, RequestFuncInput, - RequestFuncOutput, get_tokenizer) -from benchmark_dataset import (AIMODataset, BurstGPTDataset, - ConversationDataset, HuggingFaceDataset, - InstructCoderDataset, RandomDataset, - SampleRequest, ShareGPTDataset, SonnetDataset, - VisionArenaDataset) -from benchmark_utils import convert_to_pytorch_benchmark_format, write_to_json from tqdm.asyncio import tqdm from transformers import PreTrainedTokenizerBase +from .backend_request_func import (ASYNC_REQUEST_FUNCS, + OPENAI_COMPATIBLE_BACKENDS, RequestFuncInput, + RequestFuncOutput, get_tokenizer) +from .benchmark_dataset import (AIMODataset, BurstGPTDataset, + ConversationDataset, HuggingFaceDataset, + InstructCoderDataset, RandomDataset, + SampleRequest, ShareGPTDataset, SonnetDataset, + VisionArenaDataset) +from .benchmark_utils import convert_to_pytorch_benchmark_format, write_to_json + MILLISECONDS_TO_SECONDS_CONVERSION = 1000