azure-native.machinelearningservices.BatchDeployment
Explore with Pulumi AI
API Version: 2021-03-01-preview.
Example Usage
CreateOrUpdate Batch Deployment.
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
var batchDeployment = new AzureNative.MachineLearningServices.BatchDeployment("batchDeployment", new()
{
DeploymentName = "testBatchDeployment",
EndpointName = "testBatchEndpoint",
Identity = new AzureNative.MachineLearningServices.Inputs.ResourceIdentityArgs
{
Type = "UserAssigned",
UserAssignedIdentities =
{
{ "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", new AzureNative.MachineLearningServices.Inputs.UserAssignedIdentityMetaArgs
{
ClientId = "string",
PrincipalId = "string",
} },
},
},
Kind = "string",
Location = "string",
Properties = new AzureNative.MachineLearningServices.Inputs.BatchDeploymentArgs
{
CodeConfiguration = new AzureNative.MachineLearningServices.Inputs.CodeConfigurationArgs
{
CodeId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/testcode/versions/1",
ScoringScript = "score.py",
},
Compute = new AzureNative.MachineLearningServices.Inputs.ComputeConfigurationArgs
{
InstanceCount = 0,
InstanceType = "string",
IsLocal = false,
Location = "string",
Properties =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
Target = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/computes/testcompute",
},
Description = "string",
EnvironmentId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/myenv",
EnvironmentVariables =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
ErrorThreshold = 0,
LoggingLevel = "Info",
MiniBatchSize = 0,
Model = new AzureNative.MachineLearningServices.Inputs.IdAssetReferenceArgs
{
AssetId = "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/testmodel/versions/1",
ReferenceType = "Id",
},
OutputConfiguration = new AzureNative.MachineLearningServices.Inputs.BatchOutputConfigurationArgs
{
AppendRowFileName = "string",
OutputAction = "SummaryOnly",
},
PartitionKeys = new[]
{
"string",
},
Properties =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
RetrySettings = new AzureNative.MachineLearningServices.Inputs.BatchRetrySettingsArgs
{
MaxRetries = 0,
Timeout = "PT1M",
},
},
ResourceGroupName = "resourceGroup-1234",
Tags =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
WorkspaceName = "testworkspace",
});
});
package main
import (
machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := machinelearningservices.NewBatchDeployment(ctx, "batchDeployment", &machinelearningservices.BatchDeploymentArgs{
DeploymentName: pulumi.String("testBatchDeployment"),
EndpointName: pulumi.String("testBatchEndpoint"),
Identity: machinelearningservices.ResourceIdentityResponse{
Type: pulumi.String("UserAssigned"),
UserAssignedIdentities: machinelearningservices.UserAssignedIdentityMetaMap{
"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity": &machinelearningservices.UserAssignedIdentityMetaArgs{
ClientId: pulumi.String("string"),
PrincipalId: pulumi.String("string"),
},
},
},
Kind: pulumi.String("string"),
Location: pulumi.String("string"),
Properties: machinelearningservices.BatchDeploymentResponse{
CodeConfiguration: &machinelearningservices.CodeConfigurationArgs{
CodeId: pulumi.String("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/testcode/versions/1"),
ScoringScript: pulumi.String("score.py"),
},
Compute: &machinelearningservices.ComputeConfigurationArgs{
InstanceCount: pulumi.Int(0),
InstanceType: pulumi.String("string"),
IsLocal: pulumi.Bool(false),
Location: pulumi.String("string"),
Properties: pulumi.StringMap{
"additionalProp1": pulumi.String("string"),
"additionalProp2": pulumi.String("string"),
"additionalProp3": pulumi.String("string"),
},
Target: pulumi.String("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/computes/testcompute"),
},
Description: pulumi.String("string"),
EnvironmentId: pulumi.String("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/myenv"),
EnvironmentVariables: pulumi.StringMap{
"additionalProp1": pulumi.String("string"),
"additionalProp2": pulumi.String("string"),
"additionalProp3": pulumi.String("string"),
},
ErrorThreshold: pulumi.Int(0),
LoggingLevel: pulumi.String("Info"),
MiniBatchSize: pulumi.Float64(0),
Model: machinelearningservices.IdAssetReference{
AssetId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/testmodel/versions/1",
ReferenceType: "Id",
},
OutputConfiguration: &machinelearningservices.BatchOutputConfigurationArgs{
AppendRowFileName: pulumi.String("string"),
OutputAction: pulumi.String("SummaryOnly"),
},
PartitionKeys: pulumi.StringArray{
pulumi.String("string"),
},
Properties: pulumi.StringMap{
"additionalProp1": pulumi.String("string"),
"additionalProp2": pulumi.String("string"),
"additionalProp3": pulumi.String("string"),
},
RetrySettings: &machinelearningservices.BatchRetrySettingsArgs{
MaxRetries: pulumi.Int(0),
Timeout: pulumi.String("PT1M"),
},
},
ResourceGroupName: pulumi.String("resourceGroup-1234"),
Tags: pulumi.StringMap{
"additionalProp1": pulumi.String("string"),
"additionalProp2": pulumi.String("string"),
"additionalProp3": pulumi.String("string"),
},
WorkspaceName: pulumi.String("testworkspace"),
})
if err != nil {
return err
}
return nil
})
}
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.BatchDeployment;
import com.pulumi.azurenative.machinelearningservices.BatchDeploymentArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var batchDeployment = new BatchDeployment("batchDeployment", BatchDeploymentArgs.builder()
.deploymentName("testBatchDeployment")
.endpointName("testBatchEndpoint")
.identity(Map.ofEntries(
Map.entry("type", "UserAssigned"),
Map.entry("userAssignedIdentities", Map.of("/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity", Map.ofEntries(
Map.entry("clientId", "string"),
Map.entry("principalId", "string")
)))
))
.kind("string")
.location("string")
.properties(Map.ofEntries(
Map.entry("codeConfiguration", Map.ofEntries(
Map.entry("codeId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/testcode/versions/1"),
Map.entry("scoringScript", "score.py")
)),
Map.entry("compute", Map.ofEntries(
Map.entry("instanceCount", 0),
Map.entry("instanceType", "string"),
Map.entry("isLocal", false),
Map.entry("location", "string"),
Map.entry("properties", Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
)),
Map.entry("target", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/computes/testcompute")
)),
Map.entry("description", "string"),
Map.entry("environmentId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/myenv"),
Map.entry("environmentVariables", Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
)),
Map.entry("errorThreshold", 0),
Map.entry("loggingLevel", "Info"),
Map.entry("miniBatchSize", 0),
Map.entry("model", Map.ofEntries(
Map.entry("assetId", "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/testmodel/versions/1"),
Map.entry("referenceType", "Id")
)),
Map.entry("outputConfiguration", Map.ofEntries(
Map.entry("appendRowFileName", "string"),
Map.entry("outputAction", "SummaryOnly")
)),
Map.entry("partitionKeys", "string"),
Map.entry("properties", Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
)),
Map.entry("retrySettings", Map.ofEntries(
Map.entry("maxRetries", 0),
Map.entry("timeout", "PT1M")
))
))
.resourceGroupName("resourceGroup-1234")
.tags(Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
))
.workspaceName("testworkspace")
.build());
}
}
import pulumi
import pulumi_azure_native as azure_native
batch_deployment = azure_native.machinelearningservices.BatchDeployment("batchDeployment",
deployment_name="testBatchDeployment",
endpoint_name="testBatchEndpoint",
identity=azure_native.machinelearningservices.ResourceIdentityResponseArgs(
type="UserAssigned",
user_assigned_identities={
"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity": azure_native.machinelearningservices.UserAssignedIdentityMetaArgs(
client_id="string",
principal_id="string",
),
},
),
kind="string",
location="string",
properties=azure_native.machinelearningservices.BatchDeploymentResponseArgs(
code_configuration=azure_native.machinelearningservices.CodeConfigurationArgs(
code_id="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/testcode/versions/1",
scoring_script="score.py",
),
compute=azure_native.machinelearningservices.ComputeConfigurationArgs(
instance_count=0,
instance_type="string",
is_local=False,
location="string",
properties={
"additionalProp1": "string",
"additionalProp2": "string",
"additionalProp3": "string",
},
target="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/computes/testcompute",
),
description="string",
environment_id="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/myenv",
environment_variables={
"additionalProp1": "string",
"additionalProp2": "string",
"additionalProp3": "string",
},
error_threshold=0,
logging_level="Info",
mini_batch_size=0,
model=azure_native.machinelearningservices.IdAssetReferenceArgs(
asset_id="/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/testmodel/versions/1",
reference_type="Id",
),
output_configuration=azure_native.machinelearningservices.BatchOutputConfigurationArgs(
append_row_file_name="string",
output_action="SummaryOnly",
),
partition_keys=["string"],
properties={
"additionalProp1": "string",
"additionalProp2": "string",
"additionalProp3": "string",
},
retry_settings=azure_native.machinelearningservices.BatchRetrySettingsArgs(
max_retries=0,
timeout="PT1M",
),
),
resource_group_name="resourceGroup-1234",
tags={
"additionalProp1": "string",
"additionalProp2": "string",
"additionalProp3": "string",
},
workspace_name="testworkspace")
import * as pulumi from "@pulumi/pulumi";
import * as azure_native from "@pulumi/azure-native";
const batchDeployment = new azure_native.machinelearningservices.BatchDeployment("batchDeployment", {
deploymentName: "testBatchDeployment",
endpointName: "testBatchEndpoint",
identity: {
type: "UserAssigned",
userAssignedIdentities: {
"/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity": {
clientId: "string",
principalId: "string",
},
},
},
kind: "string",
location: "string",
properties: {
codeConfiguration: {
codeId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/testcode/versions/1",
scoringScript: "score.py",
},
compute: {
instanceCount: 0,
instanceType: "string",
isLocal: false,
location: "string",
properties: {
additionalProp1: "string",
additionalProp2: "string",
additionalProp3: "string",
},
target: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/computes/testcompute",
},
description: "string",
environmentId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/myenv",
environmentVariables: {
additionalProp1: "string",
additionalProp2: "string",
additionalProp3: "string",
},
errorThreshold: 0,
loggingLevel: "Info",
miniBatchSize: 0,
model: {
assetId: "/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/testmodel/versions/1",
referenceType: "Id",
},
outputConfiguration: {
appendRowFileName: "string",
outputAction: "SummaryOnly",
},
partitionKeys: ["string"],
properties: {
additionalProp1: "string",
additionalProp2: "string",
additionalProp3: "string",
},
retrySettings: {
maxRetries: 0,
timeout: "PT1M",
},
},
resourceGroupName: "resourceGroup-1234",
tags: {
additionalProp1: "string",
additionalProp2: "string",
additionalProp3: "string",
},
workspaceName: "testworkspace",
});
resources:
batchDeployment:
type: azure-native:machinelearningservices:BatchDeployment
properties:
deploymentName: testBatchDeployment
endpointName: testBatchEndpoint
identity:
type: UserAssigned
userAssignedIdentities:
? /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.ManagedIdentity/userAssignedIdentities/myuseridentity
: clientId: string
principalId: string
kind: string
location: string
properties:
codeConfiguration:
codeId: /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/testcode/versions/1
scoringScript: score.py
compute:
instanceCount: 0
instanceType: string
isLocal: false
location: string
properties:
additionalProp1: string
additionalProp2: string
additionalProp3: string
target: /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/computes/testcompute
description: string
environmentId: /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/myenv
environmentVariables:
additionalProp1: string
additionalProp2: string
additionalProp3: string
errorThreshold: 0
loggingLevel: Info
miniBatchSize: 0
model:
assetId: /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/models/testmodel/versions/1
referenceType: Id
outputConfiguration:
appendRowFileName: string
outputAction: SummaryOnly
partitionKeys:
- string
properties:
additionalProp1: string
additionalProp2: string
additionalProp3: string
retrySettings:
maxRetries: 0
timeout: PT1M
resourceGroupName: resourceGroup-1234
tags:
additionalProp1: string
additionalProp2: string
additionalProp3: string
workspaceName: testworkspace
Create BatchDeployment Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new BatchDeployment(name: string, args: BatchDeploymentArgs, opts?: CustomResourceOptions);
@overload
def BatchDeployment(resource_name: str,
args: BatchDeploymentInitArgs,
opts: Optional[ResourceOptions] = None)
@overload
def BatchDeployment(resource_name: str,
opts: Optional[ResourceOptions] = None,
endpoint_name: Optional[str] = None,
properties: Optional[BatchDeploymentArgs] = None,
resource_group_name: Optional[str] = None,
workspace_name: Optional[str] = None,
deployment_name: Optional[str] = None,
identity: Optional[ResourceIdentityArgs] = None,
kind: Optional[str] = None,
location: Optional[str] = None,
tags: Optional[Mapping[str, str]] = None)
func NewBatchDeployment(ctx *Context, name string, args BatchDeploymentArgs, opts ...ResourceOption) (*BatchDeployment, error)
public BatchDeployment(string name, BatchDeploymentArgs args, CustomResourceOptions? opts = null)
public BatchDeployment(String name, BatchDeploymentArgs args)
public BatchDeployment(String name, BatchDeploymentArgs args, CustomResourceOptions options)
type: azure-native:machinelearningservices:BatchDeployment
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args BatchDeploymentArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args BatchDeploymentInitArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args BatchDeploymentArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args BatchDeploymentArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args BatchDeploymentArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var batchDeploymentResource = new AzureNative.Machinelearningservices.BatchDeployment("batchDeploymentResource", new()
{
EndpointName = "string",
Properties =
{
{ "codeConfiguration",
{
{ "scoringScript", "string" },
{ "codeId", "string" },
} },
{ "compute",
{
{ "instanceCount", 0 },
{ "instanceType", "string" },
{ "isLocal", false },
{ "location", "string" },
{ "properties",
{
{ "string", "string" },
} },
{ "target", "string" },
} },
{ "description", "string" },
{ "environmentId", "string" },
{ "environmentVariables",
{
{ "string", "string" },
} },
{ "errorThreshold", 0 },
{ "loggingLevel", "string" },
{ "miniBatchSize", 0 },
{ "model",
{
{ "referenceType", "DataPath" },
{ "datastoreId", "string" },
{ "path", "string" },
} },
{ "outputConfiguration",
{
{ "appendRowFileName", "string" },
{ "outputAction", "string" },
} },
{ "partitionKeys", new[]
{
"string",
} },
{ "properties",
{
{ "string", "string" },
} },
{ "retrySettings",
{
{ "maxRetries", 0 },
{ "timeout", "string" },
} },
},
ResourceGroupName = "string",
WorkspaceName = "string",
DeploymentName = "string",
Identity =
{
{ "type", "string" },
{ "userAssignedIdentities",
{
{ "string",
{
{ "clientId", "string" },
{ "principalId", "string" },
} },
} },
},
Kind = "string",
Location = "string",
Tags =
{
{ "string", "string" },
},
});
example, err := machinelearningservices.NewBatchDeployment(ctx, "batchDeploymentResource", &machinelearningservices.BatchDeploymentArgs{
EndpointName: "string",
Properties: map[string]interface{}{
"codeConfiguration": map[string]interface{}{
"scoringScript": "string",
"codeId": "string",
},
"compute": map[string]interface{}{
"instanceCount": 0,
"instanceType": "string",
"isLocal": false,
"location": "string",
"properties": map[string]interface{}{
"string": "string",
},
"target": "string",
},
"description": "string",
"environmentId": "string",
"environmentVariables": map[string]interface{}{
"string": "string",
},
"errorThreshold": 0,
"loggingLevel": "string",
"miniBatchSize": 0,
"model": map[string]interface{}{
"referenceType": "DataPath",
"datastoreId": "string",
"path": "string",
},
"outputConfiguration": map[string]interface{}{
"appendRowFileName": "string",
"outputAction": "string",
},
"partitionKeys": []string{
"string",
},
"properties": map[string]interface{}{
"string": "string",
},
"retrySettings": map[string]interface{}{
"maxRetries": 0,
"timeout": "string",
},
},
ResourceGroupName: "string",
WorkspaceName: "string",
DeploymentName: "string",
Identity: map[string]interface{}{
"type": "string",
"userAssignedIdentities": map[string]interface{}{
"string": map[string]interface{}{
"clientId": "string",
"principalId": "string",
},
},
},
Kind: "string",
Location: "string",
Tags: map[string]interface{}{
"string": "string",
},
})
var batchDeploymentResource = new BatchDeployment("batchDeploymentResource", BatchDeploymentArgs.builder()
.endpointName("string")
.properties(%!v(PANIC=Format method: runtime error: invalid memory address or nil pointer dereference))
.resourceGroupName("string")
.workspaceName("string")
.deploymentName("string")
.identity(%!v(PANIC=Format method: runtime error: invalid memory address or nil pointer dereference))
.kind("string")
.location("string")
.tags(%!v(PANIC=Format method: runtime error: invalid memory address or nil pointer dereference))
.build());
batch_deployment_resource = azure_native.machinelearningservices.BatchDeployment("batchDeploymentResource",
endpoint_name=string,
properties={
codeConfiguration: {
scoringScript: string,
codeId: string,
},
compute: {
instanceCount: 0,
instanceType: string,
isLocal: False,
location: string,
properties: {
string: string,
},
target: string,
},
description: string,
environmentId: string,
environmentVariables: {
string: string,
},
errorThreshold: 0,
loggingLevel: string,
miniBatchSize: 0,
model: {
referenceType: DataPath,
datastoreId: string,
path: string,
},
outputConfiguration: {
appendRowFileName: string,
outputAction: string,
},
partitionKeys: [string],
properties: {
string: string,
},
retrySettings: {
maxRetries: 0,
timeout: string,
},
},
resource_group_name=string,
workspace_name=string,
deployment_name=string,
identity={
type: string,
userAssignedIdentities: {
string: {
clientId: string,
principalId: string,
},
},
},
kind=string,
location=string,
tags={
string: string,
})
const batchDeploymentResource = new azure_native.machinelearningservices.BatchDeployment("batchDeploymentResource", {
endpointName: "string",
properties: {
codeConfiguration: {
scoringScript: "string",
codeId: "string",
},
compute: {
instanceCount: 0,
instanceType: "string",
isLocal: false,
location: "string",
properties: {
string: "string",
},
target: "string",
},
description: "string",
environmentId: "string",
environmentVariables: {
string: "string",
},
errorThreshold: 0,
loggingLevel: "string",
miniBatchSize: 0,
model: {
referenceType: "DataPath",
datastoreId: "string",
path: "string",
},
outputConfiguration: {
appendRowFileName: "string",
outputAction: "string",
},
partitionKeys: ["string"],
properties: {
string: "string",
},
retrySettings: {
maxRetries: 0,
timeout: "string",
},
},
resourceGroupName: "string",
workspaceName: "string",
deploymentName: "string",
identity: {
type: "string",
userAssignedIdentities: {
string: {
clientId: "string",
principalId: "string",
},
},
},
kind: "string",
location: "string",
tags: {
string: "string",
},
});
type: azure-native:machinelearningservices:BatchDeployment
properties:
deploymentName: string
endpointName: string
identity:
type: string
userAssignedIdentities:
string:
clientId: string
principalId: string
kind: string
location: string
properties:
codeConfiguration:
codeId: string
scoringScript: string
compute:
instanceCount: 0
instanceType: string
isLocal: false
location: string
properties:
string: string
target: string
description: string
environmentId: string
environmentVariables:
string: string
errorThreshold: 0
loggingLevel: string
miniBatchSize: 0
model:
datastoreId: string
path: string
referenceType: DataPath
outputConfiguration:
appendRowFileName: string
outputAction: string
partitionKeys:
- string
properties:
string: string
retrySettings:
maxRetries: 0
timeout: string
resourceGroupName: string
tags:
string: string
workspaceName: string
BatchDeployment Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
The BatchDeployment resource accepts the following input properties:
- Endpoint
Name string - Inference endpoint name
- Properties
Pulumi.
Azure Native. Machine Learning Services. Inputs. Batch Deployment - [Required] Additional attributes of the entity.
- Resource
Group stringName - The name of the resource group. The name is case insensitive.
- Workspace
Name string - Name of Azure Machine Learning workspace.
- Deployment
Name string - The identifier for the Batch inference deployment.
- Identity
Pulumi.
Azure Native. Machine Learning Services. Inputs. Resource Identity - Service identity associated with a resource.
- Kind string
- Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
- Location string
- The geo-location where the resource lives
- Dictionary<string, string>
- Resource tags.
- Endpoint
Name string - Inference endpoint name
- Properties
Batch
Deployment Type Args - [Required] Additional attributes of the entity.
- Resource
Group stringName - The name of the resource group. The name is case insensitive.
- Workspace
Name string - Name of Azure Machine Learning workspace.
- Deployment
Name string - The identifier for the Batch inference deployment.
- Identity
Resource
Identity Args - Service identity associated with a resource.
- Kind string
- Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
- Location string
- The geo-location where the resource lives
- map[string]string
- Resource tags.
- endpoint
Name String - Inference endpoint name
- properties
Batch
Deployment - [Required] Additional attributes of the entity.
- resource
Group StringName - The name of the resource group. The name is case insensitive.
- workspace
Name String - Name of Azure Machine Learning workspace.
- deployment
Name String - The identifier for the Batch inference deployment.
- identity
Resource
Identity - Service identity associated with a resource.
- kind String
- Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
- location String
- The geo-location where the resource lives
- Map<String,String>
- Resource tags.
- endpoint
Name string - Inference endpoint name
- properties
Batch
Deployment - [Required] Additional attributes of the entity.
- resource
Group stringName - The name of the resource group. The name is case insensitive.
- workspace
Name string - Name of Azure Machine Learning workspace.
- deployment
Name string - The identifier for the Batch inference deployment.
- identity
Resource
Identity - Service identity associated with a resource.
- kind string
- Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
- location string
- The geo-location where the resource lives
- {[key: string]: string}
- Resource tags.
- endpoint_
name str - Inference endpoint name
- properties
Batch
Deployment Args - [Required] Additional attributes of the entity.
- resource_
group_ strname - The name of the resource group. The name is case insensitive.
- workspace_
name str - Name of Azure Machine Learning workspace.
- deployment_
name str - The identifier for the Batch inference deployment.
- identity
Resource
Identity Args - Service identity associated with a resource.
- kind str
- Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
- location str
- The geo-location where the resource lives
- Mapping[str, str]
- Resource tags.
- endpoint
Name String - Inference endpoint name
- properties Property Map
- [Required] Additional attributes of the entity.
- resource
Group StringName - The name of the resource group. The name is case insensitive.
- workspace
Name String - Name of Azure Machine Learning workspace.
- deployment
Name String - The identifier for the Batch inference deployment.
- identity Property Map
- Service identity associated with a resource.
- kind String
- Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.
- location String
- The geo-location where the resource lives
- Map<String>
- Resource tags.
Outputs
All input properties are implicitly available as output properties. Additionally, the BatchDeployment resource produces the following output properties:
- Id string
- The provider-assigned unique ID for this managed resource.
- Name string
- The name of the resource
- System
Data Pulumi.Azure Native. Machine Learning Services. Outputs. System Data Response - System data associated with resource provider
- Type string
- The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
- Id string
- The provider-assigned unique ID for this managed resource.
- Name string
- The name of the resource
- System
Data SystemData Response - System data associated with resource provider
- Type string
- The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
- id String
- The provider-assigned unique ID for this managed resource.
- name String
- The name of the resource
- system
Data SystemData Response - System data associated with resource provider
- type String
- The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
- id string
- The provider-assigned unique ID for this managed resource.
- name string
- The name of the resource
- system
Data SystemData Response - System data associated with resource provider
- type string
- The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
- id str
- The provider-assigned unique ID for this managed resource.
- name str
- The name of the resource
- system_
data SystemData Response - System data associated with resource provider
- type str
- The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
- id String
- The provider-assigned unique ID for this managed resource.
- name String
- The name of the resource
- system
Data Property Map - System data associated with resource provider
- type String
- The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
Supporting Types
BatchDeployment, BatchDeploymentArgs
- Code
Configuration Pulumi.Azure Native. Machine Learning Services. Inputs. Code Configuration - Code configuration for the endpoint deployment.
- Compute
Pulumi.
Azure Native. Machine Learning Services. Inputs. Compute Configuration - Configuration for compute binding.
- Description string
- Description of the endpoint deployment.
- Environment
Id string - ARM resource ID of the environment specification for the endpoint deployment.
- Environment
Variables Dictionary<string, string> - Environment variables configuration for the deployment.
- Error
Threshold int - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- Logging
Level string | Pulumi.Azure Native. Machine Learning Services. Batch Logging Level - Logging level for batch inference operation.
- Mini
Batch doubleSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- Model
Pulumi.
Azure | Pulumi.Native. Machine Learning Services. Inputs. Data Path Asset Reference Azure | Pulumi.Native. Machine Learning Services. Inputs. Id Asset Reference Azure Native. Machine Learning Services. Inputs. Output Path Asset Reference - Reference to the model asset for the endpoint deployment.
- Output
Configuration Pulumi.Azure Native. Machine Learning Services. Inputs. Batch Output Configuration - Output configuration for the batch inference operation.
- Partition
Keys List<string> - Partition keys list used for Named partitioning.
- Properties Dictionary<string, string>
- Property dictionary. Properties can be added, but not removed or altered.
- Retry
Settings Pulumi.Azure Native. Machine Learning Services. Inputs. Batch Retry Settings - Retry Settings for the batch inference operation.
- Code
Configuration CodeConfiguration - Code configuration for the endpoint deployment.
- Compute
Compute
Configuration - Configuration for compute binding.
- Description string
- Description of the endpoint deployment.
- Environment
Id string - ARM resource ID of the environment specification for the endpoint deployment.
- Environment
Variables map[string]string - Environment variables configuration for the deployment.
- Error
Threshold int - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- Logging
Level string | BatchLogging Level - Logging level for batch inference operation.
- Mini
Batch float64Size - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- Model
Data
Path | IdAsset Reference Asset | OutputReference Path Asset Reference - Reference to the model asset for the endpoint deployment.
- Output
Configuration BatchOutput Configuration - Output configuration for the batch inference operation.
- Partition
Keys []string - Partition keys list used for Named partitioning.
- Properties map[string]string
- Property dictionary. Properties can be added, but not removed or altered.
- Retry
Settings BatchRetry Settings - Retry Settings for the batch inference operation.
- code
Configuration CodeConfiguration - Code configuration for the endpoint deployment.
- compute
Compute
Configuration - Configuration for compute binding.
- description String
- Description of the endpoint deployment.
- environment
Id String - ARM resource ID of the environment specification for the endpoint deployment.
- environment
Variables Map<String,String> - Environment variables configuration for the deployment.
- error
Threshold Integer - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging
Level String | BatchLogging Level - Logging level for batch inference operation.
- mini
Batch DoubleSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model
Data
Path | IdAsset Reference Asset | OutputReference Path Asset Reference - Reference to the model asset for the endpoint deployment.
- output
Configuration BatchOutput Configuration - Output configuration for the batch inference operation.
- partition
Keys List<String> - Partition keys list used for Named partitioning.
- properties Map<String,String>
- Property dictionary. Properties can be added, but not removed or altered.
- retry
Settings BatchRetry Settings - Retry Settings for the batch inference operation.
- code
Configuration CodeConfiguration - Code configuration for the endpoint deployment.
- compute
Compute
Configuration - Configuration for compute binding.
- description string
- Description of the endpoint deployment.
- environment
Id string - ARM resource ID of the environment specification for the endpoint deployment.
- environment
Variables {[key: string]: string} - Environment variables configuration for the deployment.
- error
Threshold number - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging
Level string | BatchLogging Level - Logging level for batch inference operation.
- mini
Batch numberSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model
Data
Path | IdAsset Reference Asset | OutputReference Path Asset Reference - Reference to the model asset for the endpoint deployment.
- output
Configuration BatchOutput Configuration - Output configuration for the batch inference operation.
- partition
Keys string[] - Partition keys list used for Named partitioning.
- properties {[key: string]: string}
- Property dictionary. Properties can be added, but not removed or altered.
- retry
Settings BatchRetry Settings - Retry Settings for the batch inference operation.
- code_
configuration CodeConfiguration - Code configuration for the endpoint deployment.
- compute
Compute
Configuration - Configuration for compute binding.
- description str
- Description of the endpoint deployment.
- environment_
id str - ARM resource ID of the environment specification for the endpoint deployment.
- environment_
variables Mapping[str, str] - Environment variables configuration for the deployment.
- error_
threshold int - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging_
level str | BatchLogging Level - Logging level for batch inference operation.
- mini_
batch_ floatsize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model
Data
Path | IdAsset Reference Asset | OutputReference Path Asset Reference - Reference to the model asset for the endpoint deployment.
- output_
configuration BatchOutput Configuration - Output configuration for the batch inference operation.
- partition_
keys Sequence[str] - Partition keys list used for Named partitioning.
- properties Mapping[str, str]
- Property dictionary. Properties can be added, but not removed or altered.
- retry_
settings BatchRetry Settings - Retry Settings for the batch inference operation.
- code
Configuration Property Map - Code configuration for the endpoint deployment.
- compute Property Map
- Configuration for compute binding.
- description String
- Description of the endpoint deployment.
- environment
Id String - ARM resource ID of the environment specification for the endpoint deployment.
- environment
Variables Map<String> - Environment variables configuration for the deployment.
- error
Threshold Number - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging
Level String | "Info" | "Warning" | "Debug" - Logging level for batch inference operation.
- mini
Batch NumberSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model Property Map | Property Map | Property Map
- Reference to the model asset for the endpoint deployment.
- output
Configuration Property Map - Output configuration for the batch inference operation.
- partition
Keys List<String> - Partition keys list used for Named partitioning.
- properties Map<String>
- Property dictionary. Properties can be added, but not removed or altered.
- retry
Settings Property Map - Retry Settings for the batch inference operation.
BatchDeploymentResponse, BatchDeploymentResponseArgs
- Code
Configuration Pulumi.Azure Native. Machine Learning Services. Inputs. Code Configuration Response - Code configuration for the endpoint deployment.
- Compute
Pulumi.
Azure Native. Machine Learning Services. Inputs. Compute Configuration Response - Configuration for compute binding.
- Description string
- Description of the endpoint deployment.
- Environment
Id string - ARM resource ID of the environment specification for the endpoint deployment.
- Environment
Variables Dictionary<string, string> - Environment variables configuration for the deployment.
- Error
Threshold int - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- Logging
Level string - Logging level for batch inference operation.
- Mini
Batch doubleSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- Model
Pulumi.
Azure | Pulumi.Native. Machine Learning Services. Inputs. Data Path Asset Reference Response Azure | Pulumi.Native. Machine Learning Services. Inputs. Id Asset Reference Response Azure Native. Machine Learning Services. Inputs. Output Path Asset Reference Response - Reference to the model asset for the endpoint deployment.
- Output
Configuration Pulumi.Azure Native. Machine Learning Services. Inputs. Batch Output Configuration Response - Output configuration for the batch inference operation.
- Partition
Keys List<string> - Partition keys list used for Named partitioning.
- Properties Dictionary<string, string>
- Property dictionary. Properties can be added, but not removed or altered.
- Retry
Settings Pulumi.Azure Native. Machine Learning Services. Inputs. Batch Retry Settings Response - Retry Settings for the batch inference operation.
- Code
Configuration CodeConfiguration Response - Code configuration for the endpoint deployment.
- Compute
Compute
Configuration Response - Configuration for compute binding.
- Description string
- Description of the endpoint deployment.
- Environment
Id string - ARM resource ID of the environment specification for the endpoint deployment.
- Environment
Variables map[string]string - Environment variables configuration for the deployment.
- Error
Threshold int - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- Logging
Level string - Logging level for batch inference operation.
- Mini
Batch float64Size - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- Model
Data
Path | IdAsset Reference Response Asset | OutputReference Response Path Asset Reference Response - Reference to the model asset for the endpoint deployment.
- Output
Configuration BatchOutput Configuration Response - Output configuration for the batch inference operation.
- Partition
Keys []string - Partition keys list used for Named partitioning.
- Properties map[string]string
- Property dictionary. Properties can be added, but not removed or altered.
- Retry
Settings BatchRetry Settings Response - Retry Settings for the batch inference operation.
- code
Configuration CodeConfiguration Response - Code configuration for the endpoint deployment.
- compute
Compute
Configuration Response - Configuration for compute binding.
- description String
- Description of the endpoint deployment.
- environment
Id String - ARM resource ID of the environment specification for the endpoint deployment.
- environment
Variables Map<String,String> - Environment variables configuration for the deployment.
- error
Threshold Integer - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging
Level String - Logging level for batch inference operation.
- mini
Batch DoubleSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model
Data
Path | IdAsset Reference Response Asset | OutputReference Response Path Asset Reference Response - Reference to the model asset for the endpoint deployment.
- output
Configuration BatchOutput Configuration Response - Output configuration for the batch inference operation.
- partition
Keys List<String> - Partition keys list used for Named partitioning.
- properties Map<String,String>
- Property dictionary. Properties can be added, but not removed or altered.
- retry
Settings BatchRetry Settings Response - Retry Settings for the batch inference operation.
- code
Configuration CodeConfiguration Response - Code configuration for the endpoint deployment.
- compute
Compute
Configuration Response - Configuration for compute binding.
- description string
- Description of the endpoint deployment.
- environment
Id string - ARM resource ID of the environment specification for the endpoint deployment.
- environment
Variables {[key: string]: string} - Environment variables configuration for the deployment.
- error
Threshold number - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging
Level string - Logging level for batch inference operation.
- mini
Batch numberSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model
Data
Path | IdAsset Reference Response Asset | OutputReference Response Path Asset Reference Response - Reference to the model asset for the endpoint deployment.
- output
Configuration BatchOutput Configuration Response - Output configuration for the batch inference operation.
- partition
Keys string[] - Partition keys list used for Named partitioning.
- properties {[key: string]: string}
- Property dictionary. Properties can be added, but not removed or altered.
- retry
Settings BatchRetry Settings Response - Retry Settings for the batch inference operation.
- code_
configuration CodeConfiguration Response - Code configuration for the endpoint deployment.
- compute
Compute
Configuration Response - Configuration for compute binding.
- description str
- Description of the endpoint deployment.
- environment_
id str - ARM resource ID of the environment specification for the endpoint deployment.
- environment_
variables Mapping[str, str] - Environment variables configuration for the deployment.
- error_
threshold int - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging_
level str - Logging level for batch inference operation.
- mini_
batch_ floatsize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model
Data
Path | IdAsset Reference Response Asset | OutputReference Response Path Asset Reference Response - Reference to the model asset for the endpoint deployment.
- output_
configuration BatchOutput Configuration Response - Output configuration for the batch inference operation.
- partition_
keys Sequence[str] - Partition keys list used for Named partitioning.
- properties Mapping[str, str]
- Property dictionary. Properties can be added, but not removed or altered.
- retry_
settings BatchRetry Settings Response - Retry Settings for the batch inference operation.
- code
Configuration Property Map - Code configuration for the endpoint deployment.
- compute Property Map
- Configuration for compute binding.
- description String
- Description of the endpoint deployment.
- environment
Id String - ARM resource ID of the environment specification for the endpoint deployment.
- environment
Variables Map<String> - Environment variables configuration for the deployment.
- error
Threshold Number - Error threshold, if the error count for the entire input goes above this value, the batch inference will be aborted. Range is [-1, int.MaxValue]. For FileDataset, this value is the count of file failures. For TabularDataset, this value is the count of record failures. If set to -1 (the lower bound), all failures during batch inference will be ignored.
- logging
Level String - Logging level for batch inference operation.
- mini
Batch NumberSize - Size of the mini-batch passed to each batch invocation. For FileDataset, this is the number of files per mini-batch. For TabularDataset, this is the size of the records in bytes, per mini-batch.
- model Property Map | Property Map | Property Map
- Reference to the model asset for the endpoint deployment.
- output
Configuration Property Map - Output configuration for the batch inference operation.
- partition
Keys List<String> - Partition keys list used for Named partitioning.
- properties Map<String>
- Property dictionary. Properties can be added, but not removed or altered.
- retry
Settings Property Map - Retry Settings for the batch inference operation.
BatchLoggingLevel, BatchLoggingLevelArgs
- Info
- Info
- Warning
- Warning
- Debug
- Debug
- Batch
Logging Level Info - Info
- Batch
Logging Level Warning - Warning
- Batch
Logging Level Debug - Debug
- Info
- Info
- Warning
- Warning
- Debug
- Debug
- Info
- Info
- Warning
- Warning
- Debug
- Debug
- INFO
- Info
- WARNING
- Warning
- DEBUG
- Debug
- "Info"
- Info
- "Warning"
- Warning
- "Debug"
- Debug
BatchOutputAction, BatchOutputActionArgs
- Summary
Only - SummaryOnly
- Append
Row - AppendRow
- Batch
Output Action Summary Only - SummaryOnly
- Batch
Output Action Append Row - AppendRow
- Summary
Only - SummaryOnly
- Append
Row - AppendRow
- Summary
Only - SummaryOnly
- Append
Row - AppendRow
- SUMMARY_ONLY
- SummaryOnly
- APPEND_ROW
- AppendRow
- "Summary
Only" - SummaryOnly
- "Append
Row" - AppendRow
BatchOutputConfiguration, BatchOutputConfigurationArgs
- Append
Row stringFile Name - Customized output file name for append_row output action.
- Output
Action string | Pulumi.Azure Native. Machine Learning Services. Batch Output Action - Indicates how the output will be organized.
- Append
Row stringFile Name - Customized output file name for append_row output action.
- Output
Action string | BatchOutput Action - Indicates how the output will be organized.
- append
Row StringFile Name - Customized output file name for append_row output action.
- output
Action String | BatchOutput Action - Indicates how the output will be organized.
- append
Row stringFile Name - Customized output file name for append_row output action.
- output
Action string | BatchOutput Action - Indicates how the output will be organized.
- append_
row_ strfile_ name - Customized output file name for append_row output action.
- output_
action str | BatchOutput Action - Indicates how the output will be organized.
- append
Row StringFile Name - Customized output file name for append_row output action.
- output
Action String | "SummaryOnly" | "Append Row" - Indicates how the output will be organized.
BatchOutputConfigurationResponse, BatchOutputConfigurationResponseArgs
- Append
Row stringFile Name - Customized output file name for append_row output action.
- Output
Action string - Indicates how the output will be organized.
- Append
Row stringFile Name - Customized output file name for append_row output action.
- Output
Action string - Indicates how the output will be organized.
- append
Row StringFile Name - Customized output file name for append_row output action.
- output
Action String - Indicates how the output will be organized.
- append
Row stringFile Name - Customized output file name for append_row output action.
- output
Action string - Indicates how the output will be organized.
- append_
row_ strfile_ name - Customized output file name for append_row output action.
- output_
action str - Indicates how the output will be organized.
- append
Row StringFile Name - Customized output file name for append_row output action.
- output
Action String - Indicates how the output will be organized.
BatchRetrySettings, BatchRetrySettingsArgs
- Max
Retries int - Maximum retry count for a mini-batch
- Timeout string
- Invocation timeout for a mini-batch, in ISO 8601 format.
- Max
Retries int - Maximum retry count for a mini-batch
- Timeout string
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max
Retries Integer - Maximum retry count for a mini-batch
- timeout String
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max
Retries number - Maximum retry count for a mini-batch
- timeout string
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max_
retries int - Maximum retry count for a mini-batch
- timeout str
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max
Retries Number - Maximum retry count for a mini-batch
- timeout String
- Invocation timeout for a mini-batch, in ISO 8601 format.
BatchRetrySettingsResponse, BatchRetrySettingsResponseArgs
- Max
Retries int - Maximum retry count for a mini-batch
- Timeout string
- Invocation timeout for a mini-batch, in ISO 8601 format.
- Max
Retries int - Maximum retry count for a mini-batch
- Timeout string
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max
Retries Integer - Maximum retry count for a mini-batch
- timeout String
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max
Retries number - Maximum retry count for a mini-batch
- timeout string
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max_
retries int - Maximum retry count for a mini-batch
- timeout str
- Invocation timeout for a mini-batch, in ISO 8601 format.
- max
Retries Number - Maximum retry count for a mini-batch
- timeout String
- Invocation timeout for a mini-batch, in ISO 8601 format.
CodeConfiguration, CodeConfigurationArgs
- Scoring
Script string - [Required] The script to execute on startup. eg. "score.py"
- Code
Id string - ARM resource ID of the code asset.
- Scoring
Script string - [Required] The script to execute on startup. eg. "score.py"
- Code
Id string - ARM resource ID of the code asset.
- scoring
Script String - [Required] The script to execute on startup. eg. "score.py"
- code
Id String - ARM resource ID of the code asset.
- scoring
Script string - [Required] The script to execute on startup. eg. "score.py"
- code
Id string - ARM resource ID of the code asset.
- scoring_
script str - [Required] The script to execute on startup. eg. "score.py"
- code_
id str - ARM resource ID of the code asset.
- scoring
Script String - [Required] The script to execute on startup. eg. "score.py"
- code
Id String - ARM resource ID of the code asset.
CodeConfigurationResponse, CodeConfigurationResponseArgs
- Scoring
Script string - [Required] The script to execute on startup. eg. "score.py"
- Code
Id string - ARM resource ID of the code asset.
- Scoring
Script string - [Required] The script to execute on startup. eg. "score.py"
- Code
Id string - ARM resource ID of the code asset.
- scoring
Script String - [Required] The script to execute on startup. eg. "score.py"
- code
Id String - ARM resource ID of the code asset.
- scoring
Script string - [Required] The script to execute on startup. eg. "score.py"
- code
Id string - ARM resource ID of the code asset.
- scoring_
script str - [Required] The script to execute on startup. eg. "score.py"
- code_
id str - ARM resource ID of the code asset.
- scoring
Script String - [Required] The script to execute on startup. eg. "score.py"
- code
Id String - ARM resource ID of the code asset.
ComputeConfiguration, ComputeConfigurationArgs
- Instance
Count int - Number of instances or nodes.
- Instance
Type string - SKU type to run on.
- Is
Local bool - Set to true for jobs running on local compute.
- Location string
- Location for virtual cluster run.
- Properties Dictionary<string, string>
- Additional properties.
- Target string
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- Instance
Count int - Number of instances or nodes.
- Instance
Type string - SKU type to run on.
- Is
Local bool - Set to true for jobs running on local compute.
- Location string
- Location for virtual cluster run.
- Properties map[string]string
- Additional properties.
- Target string
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance
Count Integer - Number of instances or nodes.
- instance
Type String - SKU type to run on.
- is
Local Boolean - Set to true for jobs running on local compute.
- location String
- Location for virtual cluster run.
- properties Map<String,String>
- Additional properties.
- target String
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance
Count number - Number of instances or nodes.
- instance
Type string - SKU type to run on.
- is
Local boolean - Set to true for jobs running on local compute.
- location string
- Location for virtual cluster run.
- properties {[key: string]: string}
- Additional properties.
- target string
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance_
count int - Number of instances or nodes.
- instance_
type str - SKU type to run on.
- is_
local bool - Set to true for jobs running on local compute.
- location str
- Location for virtual cluster run.
- properties Mapping[str, str]
- Additional properties.
- target str
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance
Count Number - Number of instances or nodes.
- instance
Type String - SKU type to run on.
- is
Local Boolean - Set to true for jobs running on local compute.
- location String
- Location for virtual cluster run.
- properties Map<String>
- Additional properties.
- target String
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
ComputeConfigurationResponse, ComputeConfigurationResponseArgs
- Instance
Count int - Number of instances or nodes.
- Instance
Type string - SKU type to run on.
- Is
Local bool - Set to true for jobs running on local compute.
- Location string
- Location for virtual cluster run.
- Properties Dictionary<string, string>
- Additional properties.
- Target string
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- Instance
Count int - Number of instances or nodes.
- Instance
Type string - SKU type to run on.
- Is
Local bool - Set to true for jobs running on local compute.
- Location string
- Location for virtual cluster run.
- Properties map[string]string
- Additional properties.
- Target string
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance
Count Integer - Number of instances or nodes.
- instance
Type String - SKU type to run on.
- is
Local Boolean - Set to true for jobs running on local compute.
- location String
- Location for virtual cluster run.
- properties Map<String,String>
- Additional properties.
- target String
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance
Count number - Number of instances or nodes.
- instance
Type string - SKU type to run on.
- is
Local boolean - Set to true for jobs running on local compute.
- location string
- Location for virtual cluster run.
- properties {[key: string]: string}
- Additional properties.
- target string
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance_
count int - Number of instances or nodes.
- instance_
type str - SKU type to run on.
- is_
local bool - Set to true for jobs running on local compute.
- location str
- Location for virtual cluster run.
- properties Mapping[str, str]
- Additional properties.
- target str
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
- instance
Count Number - Number of instances or nodes.
- instance
Type String - SKU type to run on.
- is
Local Boolean - Set to true for jobs running on local compute.
- location String
- Location for virtual cluster run.
- properties Map<String>
- Additional properties.
- target String
- ARM resource ID of the Compute you are targeting. If not provided the resource will be deployed as Managed.
DataPathAssetReference, DataPathAssetReferenceArgs
- Datastore
Id string - ARM resource ID of the datastore where the asset is located.
- Path string
- The path of the file/directory in the datastore.
- Datastore
Id string - ARM resource ID of the datastore where the asset is located.
- Path string
- The path of the file/directory in the datastore.
- datastore
Id String - ARM resource ID of the datastore where the asset is located.
- path String
- The path of the file/directory in the datastore.
- datastore
Id string - ARM resource ID of the datastore where the asset is located.
- path string
- The path of the file/directory in the datastore.
- datastore_
id str - ARM resource ID of the datastore where the asset is located.
- path str
- The path of the file/directory in the datastore.
- datastore
Id String - ARM resource ID of the datastore where the asset is located.
- path String
- The path of the file/directory in the datastore.
DataPathAssetReferenceResponse, DataPathAssetReferenceResponseArgs
- Datastore
Id string - ARM resource ID of the datastore where the asset is located.
- Path string
- The path of the file/directory in the datastore.
- Datastore
Id string - ARM resource ID of the datastore where the asset is located.
- Path string
- The path of the file/directory in the datastore.
- datastore
Id String - ARM resource ID of the datastore where the asset is located.
- path String
- The path of the file/directory in the datastore.
- datastore
Id string - ARM resource ID of the datastore where the asset is located.
- path string
- The path of the file/directory in the datastore.
- datastore_
id str - ARM resource ID of the datastore where the asset is located.
- path str
- The path of the file/directory in the datastore.
- datastore
Id String - ARM resource ID of the datastore where the asset is located.
- path String
- The path of the file/directory in the datastore.
IdAssetReference, IdAssetReferenceArgs
- Asset
Id string - [Required] ARM resource ID of the asset.
- Asset
Id string - [Required] ARM resource ID of the asset.
- asset
Id String - [Required] ARM resource ID of the asset.
- asset
Id string - [Required] ARM resource ID of the asset.
- asset_
id str - [Required] ARM resource ID of the asset.
- asset
Id String - [Required] ARM resource ID of the asset.
IdAssetReferenceResponse, IdAssetReferenceResponseArgs
- Asset
Id string - [Required] ARM resource ID of the asset.
- Asset
Id string - [Required] ARM resource ID of the asset.
- asset
Id String - [Required] ARM resource ID of the asset.
- asset
Id string - [Required] ARM resource ID of the asset.
- asset_
id str - [Required] ARM resource ID of the asset.
- asset
Id String - [Required] ARM resource ID of the asset.
OutputPathAssetReference, OutputPathAssetReferenceArgs
OutputPathAssetReferenceResponse, OutputPathAssetReferenceResponseArgs
ResourceIdentity, ResourceIdentityArgs
- Type
string | Pulumi.
Azure Native. Machine Learning Services. Resource Identity Assignment - Defines values for a ResourceIdentity's type.
- User
Assigned Dictionary<string, Pulumi.Identities Azure Native. Machine Learning Services. Inputs. User Assigned Identity Meta> - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- Type
string | Resource
Identity Assignment - Defines values for a ResourceIdentity's type.
- User
Assigned map[string]UserIdentities Assigned Identity Meta - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- type
String | Resource
Identity Assignment - Defines values for a ResourceIdentity's type.
- user
Assigned Map<String,UserIdentities Assigned Identity Meta> - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- type
string | Resource
Identity Assignment - Defines values for a ResourceIdentity's type.
- user
Assigned {[key: string]: UserIdentities Assigned Identity Meta} - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- type
str | Resource
Identity Assignment - Defines values for a ResourceIdentity's type.
- user_
assigned_ Mapping[str, Useridentities Assigned Identity Meta] - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- type
String | "System
Assigned" | "User Assigned" | "System Assigned,User Assigned" | "None" - Defines values for a ResourceIdentity's type.
- user
Assigned Map<Property Map>Identities - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
ResourceIdentityAssignment, ResourceIdentityAssignmentArgs
- System
Assigned - SystemAssigned
- User
Assigned - UserAssigned
- System
Assigned_User Assigned - SystemAssigned,UserAssigned
- None
- None
- Resource
Identity Assignment System Assigned - SystemAssigned
- Resource
Identity Assignment User Assigned - UserAssigned
- Resource
Identity Assignment_System Assigned_User Assigned - SystemAssigned,UserAssigned
- Resource
Identity Assignment None - None
- System
Assigned - SystemAssigned
- User
Assigned - UserAssigned
- System
Assigned_User Assigned - SystemAssigned,UserAssigned
- None
- None
- System
Assigned - SystemAssigned
- User
Assigned - UserAssigned
- System
Assigned_User Assigned - SystemAssigned,UserAssigned
- None
- None
- SYSTEM_ASSIGNED
- SystemAssigned
- USER_ASSIGNED
- UserAssigned
- SYSTEM_ASSIGNED_USER_ASSIGNED
- SystemAssigned,UserAssigned
- NONE
- None
- "System
Assigned" - SystemAssigned
- "User
Assigned" - UserAssigned
- "System
Assigned,User Assigned" - SystemAssigned,UserAssigned
- "None"
- None
ResourceIdentityResponse, ResourceIdentityResponseArgs
- Principal
Id string - Client ID that is used when authenticating.
- Tenant
Id string - AAD Tenant where this identity lives.
- Type string
- Defines values for a ResourceIdentity's type.
- User
Assigned Dictionary<string, Pulumi.Identities Azure Native. Machine Learning Services. Inputs. User Assigned Identity Meta Response> - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- Principal
Id string - Client ID that is used when authenticating.
- Tenant
Id string - AAD Tenant where this identity lives.
- Type string
- Defines values for a ResourceIdentity's type.
- User
Assigned map[string]UserIdentities Assigned Identity Meta Response - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- principal
Id String - Client ID that is used when authenticating.
- tenant
Id String - AAD Tenant where this identity lives.
- type String
- Defines values for a ResourceIdentity's type.
- user
Assigned Map<String,UserIdentities Assigned Identity Meta Response> - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- principal
Id string - Client ID that is used when authenticating.
- tenant
Id string - AAD Tenant where this identity lives.
- type string
- Defines values for a ResourceIdentity's type.
- user
Assigned {[key: string]: UserIdentities Assigned Identity Meta Response} - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- principal_
id str - Client ID that is used when authenticating.
- tenant_
id str - AAD Tenant where this identity lives.
- type str
- Defines values for a ResourceIdentity's type.
- user_
assigned_ Mapping[str, Useridentities Assigned Identity Meta Response] - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
- principal
Id String - Client ID that is used when authenticating.
- tenant
Id String - AAD Tenant where this identity lives.
- type String
- Defines values for a ResourceIdentity's type.
- user
Assigned Map<Property Map>Identities - Dictionary of the user assigned identities, key is ARM resource ID of the UAI.
SystemDataResponse, SystemDataResponseArgs
- Created
At string - The timestamp of resource creation (UTC)
- Created
By string - An identifier for the identity that created the resource
- Created
By stringType - The type of identity that created the resource
- Last
Modified stringAt - The timestamp of resource last modification (UTC)
- Last
Modified stringBy - An identifier for the identity that last modified the resource
- Last
Modified stringBy Type - The type of identity that last modified the resource
- Created
At string - The timestamp of resource creation (UTC)
- Created
By string - An identifier for the identity that created the resource
- Created
By stringType - The type of identity that created the resource
- Last
Modified stringAt - The timestamp of resource last modification (UTC)
- Last
Modified stringBy - An identifier for the identity that last modified the resource
- Last
Modified stringBy Type - The type of identity that last modified the resource
- created
At String - The timestamp of resource creation (UTC)
- created
By String - An identifier for the identity that created the resource
- created
By StringType - The type of identity that created the resource
- last
Modified StringAt - The timestamp of resource last modification (UTC)
- last
Modified StringBy - An identifier for the identity that last modified the resource
- last
Modified StringBy Type - The type of identity that last modified the resource
- created
At string - The timestamp of resource creation (UTC)
- created
By string - An identifier for the identity that created the resource
- created
By stringType - The type of identity that created the resource
- last
Modified stringAt - The timestamp of resource last modification (UTC)
- last
Modified stringBy - An identifier for the identity that last modified the resource
- last
Modified stringBy Type - The type of identity that last modified the resource
- created_
at str - The timestamp of resource creation (UTC)
- created_
by str - An identifier for the identity that created the resource
- created_
by_ strtype - The type of identity that created the resource
- last_
modified_ strat - The timestamp of resource last modification (UTC)
- last_
modified_ strby - An identifier for the identity that last modified the resource
- last_
modified_ strby_ type - The type of identity that last modified the resource
- created
At String - The timestamp of resource creation (UTC)
- created
By String - An identifier for the identity that created the resource
- created
By StringType - The type of identity that created the resource
- last
Modified StringAt - The timestamp of resource last modification (UTC)
- last
Modified StringBy - An identifier for the identity that last modified the resource
- last
Modified StringBy Type - The type of identity that last modified the resource
UserAssignedIdentityMeta, UserAssignedIdentityMetaArgs
- Client
Id string - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- Principal
Id string - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- Client
Id string - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- Principal
Id string - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client
Id String - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal
Id String - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client
Id string - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal
Id string - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client_
id str - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal_
id str - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client
Id String - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal
Id String - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
UserAssignedIdentityMetaResponse, UserAssignedIdentityMetaResponseArgs
- Client
Id string - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- Principal
Id string - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- Client
Id string - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- Principal
Id string - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client
Id String - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal
Id String - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client
Id string - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal
Id string - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client_
id str - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal_
id str - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
- client
Id String - Aka application ID, a unique identifier generated by Azure AD that is tied to an application and service principal during its initial provisioning.
- principal
Id String - The object ID of the service principal object for your managed identity that is used to grant role-based access to an Azure resource.
Import
An existing resource can be imported using its type token, name, and identifier, e.g.
$ pulumi import azure-native:machinelearningservices:BatchDeployment testBatchDeployment /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/testrg123/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/batchEndpoints/testBatchEndpoint/deployments/testBatchDeployment
To learn more about importing existing cloud resources, see Importing resources.
Package Details
- Repository
- azure-native-v1 pulumi/pulumi-azure-native
- License
- Apache-2.0