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Amazon web services AWS Sagemaker中S3中的培训数据_Amazon Web Services_Amazon S3_Mxnet_Amazon Sagemaker - Fatal编程技术网

Amazon web services AWS Sagemaker中S3中的培训数据

Amazon web services AWS Sagemaker中S3中的培训数据,amazon-web-services,amazon-s3,mxnet,amazon-sagemaker,Amazon Web Services,Amazon S3,Mxnet,Amazon Sagemaker,我已将自己的Jupyter笔记本上传到Sagemaker,并尝试为S3中的培训/验证数据创建迭代器,如下所示: train = mx.io.ImageRecordIter( path_imgrec = ‘s3://bucket-name/train.rec’ …… ) 我收到以下例外情况: MXNetError: [04:33:32] src/io/s3_filesys.cc:899: Need to set enviroment variable AWS_SE

我已将自己的Jupyter笔记本上传到Sagemaker,并尝试为S3中的培训/验证数据创建迭代器,如下所示:

train = mx.io.ImageRecordIter(
        path_imgrec         = ‘s3://bucket-name/train.rec’ …… )
我收到以下例外情况:

MXNetError: [04:33:32] src/io/s3_filesys.cc:899: Need to set enviroment variable AWS_SECRET_ACCESS_KEY to use S3

我已检查此笔记本实例附带的IAM角色是否具有S3访问权限。关于修复此问题可能需要什么的任何线索?

如果您的IAM角色设置正确,那么您需要先将文件下载到Sagemaker实例,然后再处理它。以下是方法:

# Import roles
import sagemaker
role = sagemaker.get_execution_role()

# Download file locally
s3 = boto3.resource('s3')
s3.Bucket(bucket).download_file('your_training_s3_file.rec', 'training.rec')

#Access locally
train = mx.io.ImageRecordIter(path_imgrec=‘training.rec’ …… )