我知道将 .csv 文件从 S3 存储桶加载到 sagemaker notebook 非常简单,但我想加载存储在 S3 存储桶中的 model.tar.gz 文件。我尝试执行以下操作
import botocore
import sagemaker
from sagemaker import get_execution_role
from sagemaker.predictor import csv_serializer
import boto3
sm_client = boto3.client(service_name='sagemaker')
runtime_sm_client = boto3.client(service_name='sagemaker-runtime')
s3 = boto3.resource('s3')
s3_client = boto3.client('s3')
sagemaker_session = sagemaker.Session()
role = get_execution_role()
ACCOUNT_ID = boto3.client('sts').get_caller_identity()['Account']
REGION = boto3.Session().region_name
BUCKET = 'sagemaker.prismade.net'
data_key = 'DEMO_MME_ANN/multi_model_artifacts/axel.tar.gz'
loc = 's3://{}/{}'.format(BUCKET, data_key)
print(loc)
with tarfile.open(loc) as tar:
tar.extractall(path='.')
我收到以下错误:
--------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-215-bfdddac71b95> in <module>()
20 loc = 's3://{}/{}'.format(BUCKET, data_key)
21 print(loc)
---> 22 with tarfile.open(loc) as tar:
23 tar.extractall(path='.')
~/anaconda3/envs/python3/lib/python3.6/tarfile.py in open(cls, name, mode, fileobj, bufsize, **kwargs)
1567 saved_pos = fileobj.tell()
1568 try:
-> 1569 return func(name, "r", fileobj, **kwargs)
1570 except (ReadError, CompressionError):
1571 if fileobj is not None:
~/anaconda3/envs/python3/lib/python3.6/tarfile.py in gzopen(cls, name, mode, fileobj, compresslevel, **kwargs)
1632
1633 try:
-> 1634 fileobj = gzip.GzipFile(name, mode + "b", compresslevel, fileobj)
1635 except OSError:
1636 if fileobj is not None and mode == 'r':
~/anaconda3/envs/python3/lib/python3.6/gzip.py in __init__(self, filename, mode, compresslevel, fileobj, mtime)
161 mode += 'b'
162 if fileobj is None:
--> 163 fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
164 if filename is None:
165 filename = getattr(fileobj, 'name', '')
FileNotFoundError: [Errno 2] No such file or directory: 's3://sagemaker.prismade.net/DEMO_MME_ANN/multi_model_artifacts/axel.tar.gz'
这里有什么错误,我该如何做到这一点?
最佳答案
并非每个设计用于文件系统(在本例中为 tarfile.open)的 Python 库都知道如何将 S3 中的对象作为文件读取。
解决它的简单方法是首先将对象作为文件复制到本地文件系统中。
import boto3
s3 = boto3.client('s3')
s3.download_file('BUCKET_NAME', 'OBJECT_NAME', 'FILE_NAME')
关于python-3.x - 如何在 sagemaker notebook 中打开存储在 S3 存储桶中的模型 tarfile?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/60072981/