Question

我是AWS的新手，并尝试通过引用其demo（从Web控制台）构建模型。但是，当我尝试创建模型时，会出现以下错误。

无法访问以下位置的模型数据 https://s3.console.aws.amazon.com/s3/buckets/ 存储桶名称 /models/ 模型名称 -v0.1.hdf5. 请确保角色 “ arn：aws：iam :: id ：role / service-role / AmazonSageMaker-ExecutionRole- xxx ” 存在并且其信任关系策略允许该操作服务主体“ sagemaker.amazonaws.com”的“ sts：AssumeRole”。还要确保该角色具有“ s3：GetObject”权限，并且对象位于 eu-west-1 中。

我检查了IAM角色，并附加了AmazonSageMakerFullAccess和AmazonS3FullAccess策略。而且，还为角色指定了信任关系（如下所示）。

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "sagemaker.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

我正确地指定了ECR和S3路径，但是我不知道发生了什么。有人可以帮我解决这个问题吗？

很抱歉，如果我无法提供更多信息，但是如果需要，我还会提供其他信息。

更新：

下面是IAM策略。

AmazonS3FullAccess

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": "s3:*",
            "Resource": "*"
        }
    ]
}

AmazonSageMaker-ExecutionPolicy-xxx

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Action": [
                "s3:ListBucket"
            ],
            "Effect": "Allow",
            "Resource": [
                "arn:aws:s3:::<bucket_name>"
            ]
        },
        {
            "Action": [
                "s3:GetObject",
                "s3:PutObject",
                "s3:DeleteObject"
            ],
            "Effect": "Allow",
            "Resource": [
                "arn:aws:s3:::<bucket_name>/*"
            ]
        }
    ]
}

AmazonSageMakerFullAccess

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "sagemaker:*"
            ],
            "Resource": "*"
        },
        {
            "Effect": "Allow",
            "Action": [
                "ecr:GetAuthorizationToken",
                "ecr:GetDownloadUrlForLayer",
                "ecr:BatchGetImage",
                "ecr:BatchCheckLayerAvailability",
                "cloudwatch:PutMetricData",
                "cloudwatch:PutMetricAlarm",
                "cloudwatch:DescribeAlarms",
                "cloudwatch:DeleteAlarms",
                "ec2:CreateNetworkInterface",
                "ec2:CreateNetworkInterfacePermission",
                "ec2:DeleteNetworkInterface",
                "ec2:DeleteNetworkInterfacePermission",
                "ec2:DescribeNetworkInterfaces",
                "ec2:DescribeVpcs",
                "ec2:DescribeDhcpOptions",
                "ec2:DescribeSubnets",
                "ec2:DescribeSecurityGroups",
                "application-autoscaling:DeleteScalingPolicy",
                "application-autoscaling:DeleteScheduledAction",
                "application-autoscaling:DeregisterScalableTarget",
                "application-autoscaling:DescribeScalableTargets",
                "application-autoscaling:DescribeScalingActivities",
                "application-autoscaling:DescribeScalingPolicies",
                "application-autoscaling:DescribeScheduledActions",
                "application-autoscaling:PutScalingPolicy",
                "application-autoscaling:PutScheduledAction",
                "application-autoscaling:RegisterScalableTarget",
                "logs:CreateLogGroup",
                "logs:CreateLogStream",
                "logs:DescribeLogStreams",
                "logs:GetLogEvents",
                "logs:PutLogEvents"
            ],
            "Resource": "*"
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:PutObject",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::*SageMaker*",
                "arn:aws:s3:::*Sagemaker*",
                "arn:aws:s3:::*sagemaker*"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:CreateBucket",
                "s3:GetBucketLocation",
                "s3:ListBucket",
                "s3:ListAllMyBuckets"
            ],
            "Resource": "*"
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetObject"
            ],
            "Resource": "*",
            "Condition": {
                "StringEqualsIgnoreCase": {
                    "s3:ExistingObjectTag/SageMaker": "true"
                }
            }
        },
        {
            "Action": "iam:CreateServiceLinkedRole",
            "Effect": "Allow",
            "Resource": "arn:aws:iam::*:role/aws-service-role/sagemaker.application-autoscaling.amazonaws.com/AWSServiceRoleForApplicationAutoScaling_SageMakerEndpoint",
            "Condition": {
                "StringLike": {
                    "iam:AWSServiceName": "sagemaker.application-autoscaling.amazonaws.com"
                }
            }
        },
        {
            "Effect": "Allow",
            "Action": [
                "iam:PassRole"
            ],
            "Resource": "*",
            "Condition": {
                "StringEquals": {
                    "iam:PassedToService": "sagemaker.amazonaws.com"
                }
            }
        }
    ]
}

Answer 1

我认为sagemaker执行策略缺少存储桶级别的权限。尝试将"arn:aws:s3:::<bucket_name>"添加到AmazonSageMaker-ExecutionPolicy-xxx

{ "Version": "2012-10-17", "Statement": [ { "Action": [ "s3:ListBucket" ], "Effect": "Allow", "Resource": [ "arn:aws:s3:::<bucket_name>" ] }, { "Action": [ "s3:GetObject", "s3:PutObject", "s3:DeleteObject" ], "Effect": "Allow", "Resource": [ "arn:aws:s3:::<bucket_name>", "arn:aws:s3:::<bucket_name>/*" ] } ] }

我使用以下SageMaker执行策略运行了该演示，并且该演示有效。这是非常宽松的政策。一旦生效，您可以根据您的存储桶名称进行更改。

{ "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:GetObject", "s3:PutObject", "s3:DeleteObject", "s3:ListBucket" ], "Resource": [ "arn:aws:s3:::*" ] } ] }

创建SageMaker模型时的ValidationError

1 个答案: