mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
b777bd6475
* Update TensorRT-LLM --------- Co-authored-by: RunningLeon <mnsheng@yeah.net> Co-authored-by: Tlntin <TlntinDeng01@Gmail.com> Co-authored-by: ZHENG, Zhen <zhengzhen.z@qq.com> Co-authored-by: Pham Van Ngoan <ngoanpham1196@gmail.com> Co-authored-by: Nathan Price <nathan@abridge.com> Co-authored-by: Tushar Goel <tushar.goel.ml@gmail.com> Co-authored-by: Mati <132419219+matichon-vultureprime@users.noreply.github.com>
64 lines
2.1 KiB
Python
64 lines
2.1 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 argparse
|
|
import json
|
|
import time
|
|
|
|
import safetensors
|
|
from safetensors.torch import save_file
|
|
|
|
import tensorrt_llm
|
|
from tensorrt_llm.models.phi3.phi3small.convert import shuffle_qkv_weights
|
|
|
|
|
|
def parse_arguments():
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument('--checkpoint_dir', type=str, default=None)
|
|
args = parser.parse_args()
|
|
|
|
return args
|
|
|
|
|
|
if __name__ == '__main__':
|
|
print(tensorrt_llm.__version__)
|
|
args = parse_arguments()
|
|
tensorrt_llm.logger.set_level('info')
|
|
|
|
tik = time.time()
|
|
with open(f"{args.checkpoint_dir}/config.json", "r") as f:
|
|
config = json.load(f)
|
|
|
|
weights = {}
|
|
with safetensors.safe_open(f"{args.checkpoint_dir}/rank0.safetensors",
|
|
framework="pt") as f:
|
|
for k in f.keys():
|
|
weights[k] = f.get_tensor(k)
|
|
|
|
# Transform QKV weights from custom Phi3Small format to TRT-LLM format
|
|
num_total_heads = config[
|
|
'num_attention_heads'] + 2 * config['num_key_value_heads']
|
|
for key, value in weights.items():
|
|
if "qkv." in key:
|
|
if 'scaling_factor' in key and value.shape[0] % num_total_heads != 0:
|
|
continue
|
|
weights[key] = shuffle_qkv_weights(value, config)
|
|
|
|
save_file(weights, f'{args.checkpoint_dir}/rank0.safetensors')
|
|
|
|
tok = time.time()
|
|
t = time.strftime('%H:%M:%S', time.gmtime(tok - tik))
|
|
print(f'Total time of converting checkpoints: {t}')
|