forked from IAHispano/Applio
-
Notifications
You must be signed in to change notification settings - Fork 0
/
datamigration_pth_files.py
91 lines (82 loc) · 2.71 KB
/
datamigration_pth_files.py
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
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
import itertools
import os
import boto3
from dataplane import s3_upload
from botocore.client import Config
import time
from tqdm import tqdm
from multiprocessing.pool import ThreadPool
n_threads = 10
S3Connect = boto3.client('s3',
endpoint_url='https://40ad419de279f41e9626e2faf500b6b4.r2.cloudflarestorage.com',
aws_access_key_id='7da645d13a990ecc11f684221ed975e3',
aws_secret_access_key='2ed0fe3463962449e5dbc8a66fb1f5ff49e06ecb2badac62120cc2c8caadc3e0',
config=Config(signature_version='s3v4'),
region_name='us-east-1')
def get_files():
current_dir = os.getcwd()
path = os.path.join(current_dir, 'logs', 'weights')
files = []
for root, dirs, filenames in os.walk(path):
for filename in filenames:
files.append((os.path.join(root, filename), filename))
return files
def get_pth_files(files):
index_files = []
for file, filename in files:
if file.endswith('.pth'):
index_files.append((file, os.path.basename(file)))
return index_files
def check_object_exists(
self,
bucket_name: str,
object_path: str,
) -> bool:
"""
Check if an object exists on the object storage.
:param bucket_name: Name of the bucket.
:param object_path: Path of the object to check.
:return: True if the object exists, False otherwise.
"""
try:
self.resource.Object(bucket_name, object_path).load()
return True
except botocore.exceptions.ClientError as e:
if e.response["Error"]["Code"] == "404":
return False
else:
logger.exception("Something else has gone wrong.")
raise
def single_upload(args):
bucket = 'vox-ai-model-pth-files'
S3Client, (file, filename) = args
print(f"Uploading file {filename}...")
rs = s3_upload(Bucket=bucket,
S3Client=S3Client,
SourceFilePath=file,
TargetFilePath=filename,
UploadMethod="File"
)
print(f"File {filename} uploaded successfully")
def parallel_uploads(index_files):
start_time = time.time()
# parallel operation
with ThreadPool(n_threads) as pool:
progress_bar = tqdm(
pool.imap(
single_upload,
zip(itertools.repeat(S3Connect), index_files),
),
total=len(index_files),
disable=False,
)
for _ in progress_bar:
progress_bar.set_description(f"Files uploaded: {progress_bar.n}/{progress_bar.total}")
end_time = time.time()
print(f"Parallel uploads completed in {end_time - start_time} seconds")
def main():
files = get_files()
pth_files = get_pth_files(files)
parallel_uploads(pth_files)
if __name__ == '__main__':
main()