mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
104 lines
3.6 KiB
Python
104 lines
3.6 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
import logging
|
|
from typing import Optional, Tuple
|
|
|
|
import click
|
|
from pydantic import BaseModel, field_validator
|
|
from transformers import AutoTokenizer
|
|
from transformers.tokenization_utils import PreTrainedTokenizer
|
|
from transformers.tokenization_utils_fast import PreTrainedTokenizerFast
|
|
from utils.prepare_real_data import dataset
|
|
from utils.prepare_synthetic_data import token_norm_dist, token_unif_dist
|
|
|
|
|
|
class RootArgs(BaseModel):
|
|
tokenizer: str
|
|
output: str
|
|
random_seed: int
|
|
task_id: int
|
|
std_out: bool
|
|
rand_task_id: Optional[Tuple[int, int]]
|
|
|
|
@field_validator('tokenizer')
|
|
def get_tokenizer(cls,
|
|
v: str) -> PreTrainedTokenizer | PreTrainedTokenizerFast:
|
|
try:
|
|
tokenizer = AutoTokenizer.from_pretrained(v, padding_side='left')
|
|
except EnvironmentError as e:
|
|
raise ValueError(
|
|
f"Cannot find a tokenizer from the given string because of {e}\nPlease set tokenizer to the directory that contains the tokenizer, or set to a model name in HuggingFace."
|
|
)
|
|
tokenizer.pad_token = tokenizer.eos_token
|
|
return tokenizer
|
|
|
|
|
|
@click.group()
|
|
@click.option(
|
|
"--tokenizer",
|
|
required=True,
|
|
type=str,
|
|
help=
|
|
"Tokenizer dir for the model run by gptManagerBenchmark, or the model name from HuggingFace."
|
|
)
|
|
@click.option("--output",
|
|
type=str,
|
|
help="Output json filename.",
|
|
default="preprocessed_dataset.json")
|
|
@click.option(
|
|
"--stdout",
|
|
is_flag=True,
|
|
help="Print output to stdout with a JSON dataset entry on each line.",
|
|
default=False)
|
|
@click.option("--random-seed",
|
|
required=False,
|
|
type=int,
|
|
help="random seed for token_ids",
|
|
default=420)
|
|
@click.option("--task-id", type=int, default=-1, help="LoRA task id")
|
|
@click.option("--rand-task-id",
|
|
type=int,
|
|
default=None,
|
|
nargs=2,
|
|
help="Random LoRA Tasks")
|
|
@click.option("--log-level",
|
|
default="info",
|
|
type=click.Choice(['info', 'debug']),
|
|
help="Logging level.")
|
|
@click.pass_context
|
|
def cli(ctx, **kwargs):
|
|
"""This script generates dataset input for gptManagerBenchmark."""
|
|
if kwargs['log_level'] == 'info':
|
|
logging.basicConfig(level=logging.INFO)
|
|
elif kwargs['log_level'] == 'debug':
|
|
logging.basicConfig(level=logging.DEBUG)
|
|
else:
|
|
raise ValueError(f"Unsupported logging level {kwargs['log_level']}")
|
|
|
|
ctx.obj = RootArgs(tokenizer=kwargs['tokenizer'],
|
|
output=kwargs['output'],
|
|
std_out=kwargs['stdout'],
|
|
random_seed=kwargs['random_seed'],
|
|
task_id=kwargs['task_id'],
|
|
rand_task_id=kwargs['rand_task_id'])
|
|
|
|
|
|
cli.add_command(dataset)
|
|
cli.add_command(token_norm_dist)
|
|
cli.add_command(token_unif_dist)
|
|
|
|
if __name__ == "__main__":
|
|
cli()
|