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Endpoint - Get ML Model Endpoint Version

Service:
MLModel
API Version:
v1

Returns information about the specified MLModel endpoint version.
For machine learning model versions where endpoints have never been enabled, or have been disabled after enabling, the status would be 'deactivated'.

Permissions

The caller must have read permission on the MLModel.

Required Delegated Scopes

MLModel.Read.All or MLModel.ReadWrite.All or Item.Read.All or Item.ReadWrite.All

Microsoft Entra supported identities

This API supports the Microsoft identities listed in this section.

Identity Support
User Yes
Service principal and Managed identities Yes

Interface

GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/mlmodels/{modelId}/endpoint/versions/{name}

URI Parameters

Name In Required Type Description
modelId
 path True

string (uuid)

The machine learning model ID.
name
 path True

string

The MLModel version name.
workspaceId
 path True

string (uuid)

The workspace ID.

Responses

Name Type Description
200 OK

MLModelEndpointVersionInfo

Request completed successfully.
Other Status Codes

ErrorResponse

Common error codes:

  • NotFound - Could not retrieve endpoint metadata.

  • UnknownError - An error occurred.

Examples

Example of Get ML Model Endpoint Version
Example of Get ML Model Endpoint Version with an Activation Failure

Example of Get ML Model Endpoint Version

Sample request

GET https://api.fabric.microsoft.com/v1/workspaces/cf5fef71-f7f3-43f3-ae7f-3c427922bef1/mlmodels/7e92a6fc-3ef5-40bf-96df-ddae3fcde313/endpoint/versions/1

Sample response

Status code:
200 
{
  "versionName": "1",
  "status": "Running",
  "inputSignature": [
    {
      "type": "double",
      "name": "age",
      "required": true
    },
    {
      "type": "double",
      "name": "sex",
      "required": true
    },
    {
      "type": "double",
      "name": "bmi",
      "required": true
    },
    {
      "type": "double",
      "name": "bp",
      "required": true
    },
    {
      "type": "double",
      "name": "s1",
      "required": true
    },
    {
      "type": "double",
      "name": "s2",
      "required": true
    },
    {
      "type": "double",
      "name": "s3",
      "required": true
    },
    {
      "type": "double",
      "name": "s4",
      "required": true
    },
    {
      "type": "double",
      "name": "s5",
      "required": true
    },
    {
      "type": "double",
      "name": "s6",
      "required": true
    }
  ],
  "outputSignature": [
    {
      "type": "double",
      "name": "target",
      "required": true
    }
  ],
  "scaleRule": "AlwaysOn"
}

Example of Get ML Model Endpoint Version with an Activation Failure

Sample request

GET https://api.fabric.microsoft.com/v1/workspaces/cf5fef71-f7f3-43f3-ae7f-3c427922bef1/mlmodels/7e92a6fc-3ef5-40bf-96df-ddae3fcde313/endpoint/versions/1

Sample response

Status code:
200 
{
  "versionName": "1",
  "status": "Failed",
  "failureDetails": {
    "errorCode": "InvalidInput",
    "message": "Tensor-based models are not supported yet."
  }
}

Definitions

Name Description
ErrorRelatedResource

The error related resource details object.
ErrorResponse

The error response.
ErrorResponseDetails

The error response details.
FailureDetails

Activation Failure details.
MLModelDataSchema

Machine learning model data schema.
MLModelEndpointVersionInfo

Machine Learning Model Endpoint version information.
ModelEndpointVersionStatus

The status of a given machine learning model endpoint version. Additional ModelEndpointVersionStatus types may be added over time.
ScaleRule

Machine learning model endpoint scale rule. Additional ScaleRule types may be added over time.

ErrorRelatedResource

Object

The error related resource details object.

Name Type Description
resourceId

string

The resource ID that's involved in the error.
resourceType

string

The type of the resource that's involved in the error.

ErrorResponse

Object

The error response.

Name Type Description
errorCode

string

A specific identifier that provides information about an error condition, allowing for standardized communication between our service and its users.
message

string

A human readable representation of the error.
moreDetails

ErrorResponseDetails[]

List of additional error details.
relatedResource

ErrorRelatedResource

The error related resource details.
requestId

string

ID of the request associated with the error.

ErrorResponseDetails

Object

The error response details.

Name Type Description
errorCode

string

A specific identifier that provides information about an error condition, allowing for standardized communication between our service and its users.
message

string

A human readable representation of the error.
relatedResource

ErrorRelatedResource

The error related resource details.

FailureDetails

Object

Activation Failure details.

Name Type Description
errorCode

string

A specific identifier that provides information about an error condition, allowing for standardized communication between our service and its users.
message

string

A human readable representation of the error.
relatedResource

ErrorRelatedResource

The error related resource details.

MLModelDataSchema

Object

Machine learning model data schema.

Name Type Description
name

string

The name of the signature.
required

boolean

The boolean value to indicate if the signature is required or no. True - Required, False - Not Required.
type

string

The type of the signature.

MLModelEndpointVersionInfo

Object

Machine Learning Model Endpoint version information.

Name Type Description
failureDetails

FailureDetails

Activation Failure details.
inputSignature

MLModelDataSchema[]

The input signature for this version of the machine learning model.
outputSignature

MLModelDataSchema[]

The output signature for this version of the machine learning model.
scaleRule

ScaleRule

Machine learning model endpoint scale rule. Additional ScaleRule types may be added over time.
status

ModelEndpointVersionStatus

The status of a given machine learning model endpoint version. Additional ModelEndpointVersionStatus types may be added over time.
versionName

string

The machine learning model version name

ModelEndpointVersionStatus

Enumeration

The status of a given machine learning model endpoint version. Additional ModelEndpointVersionStatus types may be added over time.

Value Description
Deactivated

All resources are deactivated.
Activating

Machine learning model endpoint activation is under progress.
Deactivating

Machine learning model endpoint deactivation is in progress.
Active

Machine learning model endpoint is available to serve score requests.
Failed

Machine learning model endpoint is in failed state.

ScaleRule

Enumeration

Machine learning model endpoint scale rule. Additional ScaleRule types may be added over time.

Value Description
AlwaysOn

Machine learning model endpoint should be AlwaysOn.
AllowScaleToZero

Machine learning model endpoint can be scaled to zero after a period of inactivity.