get_model_run_logs_of_dataset¶

MachineLearningApi.get_model_run_logs_of_dataset(role_id, model_run_id, modelid, id, servicename, serviceloggroup, _request_timeout=None, _request_auth=None, _content_type=None, _headers=None, _host_index=0)¶

Download SageMaker transform job logs for a model run

Returns a presigned S3 URL plus log preview for CloudWatch logs of a SageMaker batch transform job tied to a dataset file model run. Required query params: servicename=sagemaker and serviceloggroup=TransformJobs (else IPV-1053 when missing, LOG-1001 when values differ). Caller must have access to the dataset. Safe to retry (read-only URL/preview mint).

Parameters:

role_id (str) – Amorphic role ID the request is authorized against. Must grant access to the dataset. (required)
model_run_id (str) – Model run ID used as the CloudWatch log stream prefix for the transform job. (required)
modelid (str) – ML model ID associated with the run. (required)
id (str) – Dataset ID the model was run against. (required)
servicename (str) – Must be sagemaker. Any other value returns LOG-1001; missing with other required params returns IPV-1053. (required)
serviceloggroup (str) – Must be TransformJobs. Log group resolved as /aws/{servicename}/{serviceloggroup}. (required)
_request_timeout (int, tuple(int, int), optional) – timeout setting for this request. If one number provided, it will be total request timeout. It can also be a pair (tuple) of (connection, read) timeouts.
_request_auth (dict, optional) – set to override the auth_settings for an a single request; this effectively ignores the authentication in the spec for a single request.
_content_type (str, Optional) – force content-type for the request.
_headers (dict, optional) – set to override the headers for a single request; this effectively ignores the headers in the spec for a single request.
_host_index (int, optional) – set to override the host_index for a single request; this effectively ignores the host_index in the spec for a single request.

Return type:

FileDownload

Returns:

Returns the result object.

Request and Response Examples¶

HTTP: GET /datasets/{id}/files/models/{modelid}/run/{model_run_id}/logs

Parameter examples¶

Name	In	Example
`model_run_id`	path	`"c9d8e7f6-a5b4-3210-9876-543210fedcba"`
`modelid`	path	`"a1b2c3d4-e5f6-7890-abcd-ef1234567890"`
`id`	path	`"b1e6c2a0-9f4d-4c7a-8f2e-1a2b3c4d5e6f"`
`servicename`	query	`"sagemaker"`
`serviceloggroup`	query	`"TransformJobs"`

Success (HTTP 200)¶

Logs uploaded to the logs bucket. Body is FileDownload with url (presigned), logPreview, and logTruncated.

Request / response example

{
  "url": "https://s3.amazonaws.com/example-logs-bucket/ml-model-runs/c9d8e7f6-a5b4-3210-9876-543210fedcba.log?X-Amz-Algorithm=...",
  "logPreview": "Starting the inference container\nTransform job completed successfully\n",
  "logTruncated": false
}

Errors¶

Documented error codes: IPV-1053, LOG-1001.

HTTP 400

Validation or authorization failure. Body is {“Message”: “<CODE> - <text>”}. Codes: IPV-1053 (missing servicename/serviceloggroup/model_run_id), LOG-1001 (wrong service/group), AUTH-* (no dataset access).

Missing required log query/path params

{
  "Message": "IPV-1053 - Missing mandatory parameter(s) servicename, serviceloggroup in queryStringParameters and/or model_run_id in pathParameters"
}

Unsupported service or log group

{
  "Message": "LOG-1001 - Invalid service name or service log group - glue, TransformJobs"
}

HTTP 500

Backend/generic failure. Body is {“Message”: “<CODE> - <text>”}.