-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathcli_inference.py
More file actions
executable file
·62 lines (51 loc) · 2 KB
/
Copy pathcli_inference.py
File metadata and controls
executable file
·62 lines (51 loc) · 2 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
# Copyright (2024) Tsinghua University, Bytedance Ltd. and/or its affiliates
#
# 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 torch
from transformers import WhisperFeatureExtractor
from config import Config
from models.salmonn import SALMONN
from utils import prepare_one_sample
parser = argparse.ArgumentParser()
parser.add_argument("--cfg-path", type=str, required=True, help='path to configuration file')
parser.add_argument("--device", type=str, default="cuda:0")
parser.add_argument(
"--options",
nargs="+",
help="override some settings in the used config, the key-value pair "
"in xxx=yyy format will be merged into config file (deprecate), "
"change to --cfg-options instead.",
)
args = parser.parse_args()
cfg = Config(args)
model = SALMONN.from_config(cfg.config.model)
model.to(args.device)
model.eval()
wav_processor = WhisperFeatureExtractor.from_pretrained(cfg.config.model.whisper_path)
while True:
print("=====================================")
wav_path = input("Your Wav Path:\n")
prompt = input("Your Prompt:\n")
if args.device.startswith("cuda"):
cuda_enabled=True
print("Use GPU")
else:
cuda_enabled=False
print("Use CPU")
samples = prepare_one_sample(wav_path, wav_processor, cuda_enabled=cuda_enabled)
prompt = [
cfg.config.model.prompt_template.format("<Speech><SpeechHere></Speech> " + prompt.strip())
]
print("Output:")
print(model.generate(samples, cfg.config.generate, prompts=prompt)[0])