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Alibaba Cloud v3.77.0 published on Friday, May 2, 2025 by Pulumi
pulumi/pulumi-alicloud

alicloud.eflo.ExperimentPlanTemplate

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Alibaba Cloud v3.77.0 published on Friday, May 2, 2025 by Pulumi
pulumi/pulumi-alicloud

    Provides a Eflo Experiment Plan Template resource.

    For information about Eflo Experiment Plan Template and how to use it, see What is Experiment Plan Template.

    NOTE: Available since v1.248.0.

    Example Usage

    Basic Usage

    import * as pulumi from "@pulumi/pulumi";
import * as alicloud from "@pulumi/alicloud";

const config = new pulumi.Config();
const name = config.get("name") || "terraform-example";
const _default = new alicloud.eflo.ExperimentPlanTemplate("default", {
    templatePipelines: [{
        workloadId: 2,
        workloadName: "MatMul",
        envParams: {
            cpuPerWorker: 90,
            gpuPerWorker: 8,
            memoryPerWorker: 500,
            shareMemory: 500,
            workerNum: 1,
            pyTorchVersion: "1",
            gpuDriverVersion: "1",
            cudaVersion: "1",
            ncclVersion: "1",
        },
        pipelineOrder: 1,
        scene: "baseline",
    }],
    privacyLevel: "private",
    templateName: name,
    templateDescription: name,
});

    import pulumi
import pulumi_alicloud as alicloud

config = pulumi.Config()
name = config.get("name")
if name is None:
    name = "terraform-example"
default = alicloud.eflo.ExperimentPlanTemplate("default",
    template_pipelines=[{
        "workload_id": 2,
        "workload_name": "MatMul",
        "env_params": {
            "cpu_per_worker": 90,
            "gpu_per_worker": 8,
            "memory_per_worker": 500,
            "share_memory": 500,
            "worker_num": 1,
            "py_torch_version": "1",
            "gpu_driver_version": "1",
            "cuda_version": "1",
            "nccl_version": "1",
        },
        "pipeline_order": 1,
        "scene": "baseline",
    }],
    privacy_level="private",
    template_name=name,
    template_description=name)

    package main

import (
	"github.com/pulumi/pulumi-alicloud/sdk/v3/go/alicloud/eflo"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi/config"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		cfg := config.New(ctx, "")
		name := "terraform-example"
		if param := cfg.Get("name"); param != "" {
			name = param
		}
		_, err := eflo.NewExperimentPlanTemplate(ctx, "default", &eflo.ExperimentPlanTemplateArgs{
			TemplatePipelines: eflo.ExperimentPlanTemplateTemplatePipelineArray{
				&eflo.ExperimentPlanTemplateTemplatePipelineArgs{
					WorkloadId:   pulumi.Int(2),
					WorkloadName: pulumi.String("MatMul"),
					EnvParams: &eflo.ExperimentPlanTemplateTemplatePipelineEnvParamsArgs{
						CpuPerWorker:     pulumi.Int(90),
						GpuPerWorker:     pulumi.Int(8),
						MemoryPerWorker:  pulumi.Int(500),
						ShareMemory:      pulumi.Int(500),
						WorkerNum:        pulumi.Int(1),
						PyTorchVersion:   pulumi.String("1"),
						GpuDriverVersion: pulumi.String("1"),
						CudaVersion:      pulumi.String("1"),
						NcclVersion:      pulumi.String("1"),
					},
					PipelineOrder: pulumi.Int(1),
					Scene:         pulumi.String("baseline"),
				},
			},
			PrivacyLevel:        pulumi.String("private"),
			TemplateName:        pulumi.String(name),
			TemplateDescription: pulumi.String(name),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AliCloud = Pulumi.AliCloud;

return await Deployment.RunAsync(() => 
{
    var config = new Config();
    var name = config.Get("name") ?? "terraform-example";
    var @default = new AliCloud.Eflo.ExperimentPlanTemplate("default", new()
    {
        TemplatePipelines = new[]
        {
            new AliCloud.Eflo.Inputs.ExperimentPlanTemplateTemplatePipelineArgs
            {
                WorkloadId = 2,
                WorkloadName = "MatMul",
                EnvParams = new AliCloud.Eflo.Inputs.ExperimentPlanTemplateTemplatePipelineEnvParamsArgs
                {
                    CpuPerWorker = 90,
                    GpuPerWorker = 8,
                    MemoryPerWorker = 500,
                    ShareMemory = 500,
                    WorkerNum = 1,
                    PyTorchVersion = "1",
                    GpuDriverVersion = "1",
                    CudaVersion = "1",
                    NcclVersion = "1",
                },
                PipelineOrder = 1,
                Scene = "baseline",
            },
        },
        PrivacyLevel = "private",
        TemplateName = name,
        TemplateDescription = name,
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.alicloud.eflo.ExperimentPlanTemplate;
import com.pulumi.alicloud.eflo.ExperimentPlanTemplateArgs;
import com.pulumi.alicloud.eflo.inputs.ExperimentPlanTemplateTemplatePipelineArgs;
import com.pulumi.alicloud.eflo.inputs.ExperimentPlanTemplateTemplatePipelineEnvParamsArgs;
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) {
        final var config = ctx.config();
        final var name = config.get("name").orElse("terraform-example");
        var default_ = new ExperimentPlanTemplate("default", ExperimentPlanTemplateArgs.builder()
            .templatePipelines(ExperimentPlanTemplateTemplatePipelineArgs.builder()
                .workloadId(2)
                .workloadName("MatMul")
                .envParams(ExperimentPlanTemplateTemplatePipelineEnvParamsArgs.builder()
                    .cpuPerWorker(90)
                    .gpuPerWorker(8)
                    .memoryPerWorker(500)
                    .shareMemory(500)
                    .workerNum(1)
                    .pyTorchVersion("1")
                    .gpuDriverVersion("1")
                    .cudaVersion("1")
                    .ncclVersion("1")
                    .build())
                .pipelineOrder(1)
                .scene("baseline")
                .build())
            .privacyLevel("private")
            .templateName(name)
            .templateDescription(name)
            .build());

    }
}

    configuration:
  name:
    type: string
    default: terraform-example
resources:
  default:
    type: alicloud:eflo:ExperimentPlanTemplate
    properties:
      templatePipelines:
        - workloadId: '2'
          workloadName: MatMul
          envParams:
            cpuPerWorker: '90'
            gpuPerWorker: '8'
            memoryPerWorker: '500'
            shareMemory: '500'
            workerNum: '1'
            pyTorchVersion: '1'
            gpuDriverVersion: '1'
            cudaVersion: '1'
            ncclVersion: '1'
          pipelineOrder: '1'
          scene: baseline
      privacyLevel: private
      templateName: ${name}
      templateDescription: ${name}

    Create ExperimentPlanTemplate Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new ExperimentPlanTemplate(name: string, args: ExperimentPlanTemplateArgs, opts?: CustomResourceOptions);
    @overload
def ExperimentPlanTemplate(resource_name: str,
                           args: ExperimentPlanTemplateArgs,
                           opts: Optional[ResourceOptions] = None)

@overload
def ExperimentPlanTemplate(resource_name: str,
                           opts: Optional[ResourceOptions] = None,
                           privacy_level: Optional[str] = None,
                           template_name: Optional[str] = None,
                           template_pipelines: Optional[Sequence[ExperimentPlanTemplateTemplatePipelineArgs]] = None,
                           template_description: Optional[str] = None)
    func NewExperimentPlanTemplate(ctx *Context, name string, args ExperimentPlanTemplateArgs, opts ...ResourceOption) (*ExperimentPlanTemplate, error)
    public ExperimentPlanTemplate(string name, ExperimentPlanTemplateArgs args, CustomResourceOptions? opts = null)
    public ExperimentPlanTemplate(String name, ExperimentPlanTemplateArgs args)
public ExperimentPlanTemplate(String name, ExperimentPlanTemplateArgs args, CustomResourceOptions options)

    type: alicloud:eflo:ExperimentPlanTemplate
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 ExperimentPlanTemplateArgs
    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 ExperimentPlanTemplateArgs
    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 ExperimentPlanTemplateArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ExperimentPlanTemplateArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ExperimentPlanTemplateArgs
    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 experimentPlanTemplateResource = new AliCloud.Eflo.ExperimentPlanTemplate("experimentPlanTemplateResource", new()
{
    PrivacyLevel = "string",
    TemplateName = "string",
    TemplatePipelines = new[]
    {
        new AliCloud.Eflo.Inputs.ExperimentPlanTemplateTemplatePipelineArgs
        {
            EnvParams = new AliCloud.Eflo.Inputs.ExperimentPlanTemplateTemplatePipelineEnvParamsArgs
            {
                CpuPerWorker = 0,
                GpuPerWorker = 0,
                MemoryPerWorker = 0,
                ShareMemory = 0,
                WorkerNum = 0,
                CudaVersion = "string",
                GpuDriverVersion = "string",
                NcclVersion = "string",
                PyTorchVersion = "string",
            },
            PipelineOrder = 0,
            Scene = "string",
            WorkloadId = 0,
            WorkloadName = "string",
            SettingParams = 
            {
                { "string", "string" },
            },
        },
    },
    TemplateDescription = "string",
});

    example, err := eflo.NewExperimentPlanTemplate(ctx, "experimentPlanTemplateResource", &eflo.ExperimentPlanTemplateArgs{
	PrivacyLevel: pulumi.String("string"),
	TemplateName: pulumi.String("string"),
	TemplatePipelines: eflo.ExperimentPlanTemplateTemplatePipelineArray{
		&eflo.ExperimentPlanTemplateTemplatePipelineArgs{
			EnvParams: &eflo.ExperimentPlanTemplateTemplatePipelineEnvParamsArgs{
				CpuPerWorker:     pulumi.Int(0),
				GpuPerWorker:     pulumi.Int(0),
				MemoryPerWorker:  pulumi.Int(0),
				ShareMemory:      pulumi.Int(0),
				WorkerNum:        pulumi.Int(0),
				CudaVersion:      pulumi.String("string"),
				GpuDriverVersion: pulumi.String("string"),
				NcclVersion:      pulumi.String("string"),
				PyTorchVersion:   pulumi.String("string"),
			},
			PipelineOrder: pulumi.Int(0),
			Scene:         pulumi.String("string"),
			WorkloadId:    pulumi.Int(0),
			WorkloadName:  pulumi.String("string"),
			SettingParams: pulumi.StringMap{
				"string": pulumi.String("string"),
			},
		},
	},
	TemplateDescription: pulumi.String("string"),
})

    var experimentPlanTemplateResource = new ExperimentPlanTemplate("experimentPlanTemplateResource", ExperimentPlanTemplateArgs.builder()
    .privacyLevel("string")
    .templateName("string")
    .templatePipelines(ExperimentPlanTemplateTemplatePipelineArgs.builder()
        .envParams(ExperimentPlanTemplateTemplatePipelineEnvParamsArgs.builder()
            .cpuPerWorker(0)
            .gpuPerWorker(0)
            .memoryPerWorker(0)
            .shareMemory(0)
            .workerNum(0)
            .cudaVersion("string")
            .gpuDriverVersion("string")
            .ncclVersion("string")
            .pyTorchVersion("string")
            .build())
        .pipelineOrder(0)
        .scene("string")
        .workloadId(0)
        .workloadName("string")
        .settingParams(Map.of("string", "string"))
        .build())
    .templateDescription("string")
    .build());

    experiment_plan_template_resource = alicloud.eflo.ExperimentPlanTemplate("experimentPlanTemplateResource",
    privacy_level="string",
    template_name="string",
    template_pipelines=[{
        "env_params": {
            "cpu_per_worker": 0,
            "gpu_per_worker": 0,
            "memory_per_worker": 0,
            "share_memory": 0,
            "worker_num": 0,
            "cuda_version": "string",
            "gpu_driver_version": "string",
            "nccl_version": "string",
            "py_torch_version": "string",
        },
        "pipeline_order": 0,
        "scene": "string",
        "workload_id": 0,
        "workload_name": "string",
        "setting_params": {
            "string": "string",
        },
    }],
    template_description="string")

    const experimentPlanTemplateResource = new alicloud.eflo.ExperimentPlanTemplate("experimentPlanTemplateResource", {
    privacyLevel: "string",
    templateName: "string",
    templatePipelines: [{
        envParams: {
            cpuPerWorker: 0,
            gpuPerWorker: 0,
            memoryPerWorker: 0,
            shareMemory: 0,
            workerNum: 0,
            cudaVersion: "string",
            gpuDriverVersion: "string",
            ncclVersion: "string",
            pyTorchVersion: "string",
        },
        pipelineOrder: 0,
        scene: "string",
        workloadId: 0,
        workloadName: "string",
        settingParams: {
            string: "string",
        },
    }],
    templateDescription: "string",
});

    type: alicloud:eflo:ExperimentPlanTemplate
properties:
    privacyLevel: string
    templateDescription: string
    templateName: string
    templatePipelines:
        - envParams:
            cpuPerWorker: 0
            cudaVersion: string
            gpuDriverVersion: string
            gpuPerWorker: 0
            memoryPerWorker: 0
            ncclVersion: string
            pyTorchVersion: string
            shareMemory: 0
            workerNum: 0
          pipelineOrder: 0
          scene: string
          settingParams:
            string: string
          workloadId: 0
          workloadName: string

    ExperimentPlanTemplate Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The ExperimentPlanTemplate resource accepts the following input properties:

    PrivacyLevel string
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    TemplateName string
    Help users identify and select specific templates.
    TemplatePipelines List<Pulumi.AliCloud.Eflo.Inputs.ExperimentPlanTemplateTemplatePipeline>
    Representative Template Pipeline. See template_pipeline below.
    TemplateDescription string
    Describe the purpose of this template.
    PrivacyLevel string
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    TemplateName string
    Help users identify and select specific templates.
    TemplatePipelines []ExperimentPlanTemplateTemplatePipelineArgs
    Representative Template Pipeline. See template_pipeline below.
    TemplateDescription string
    Describe the purpose of this template.
    privacyLevel String
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    templateName String
    Help users identify and select specific templates.
    templatePipelines List<ExperimentPlanTemplateTemplatePipeline>
    Representative Template Pipeline. See template_pipeline below.
    templateDescription String
    Describe the purpose of this template.
    privacyLevel string
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    templateName string
    Help users identify and select specific templates.
    templatePipelines ExperimentPlanTemplateTemplatePipeline[]
    Representative Template Pipeline. See template_pipeline below.
    templateDescription string
    Describe the purpose of this template.
    privacy_level str
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    template_name str
    Help users identify and select specific templates.
    template_pipelines Sequence[ExperimentPlanTemplateTemplatePipelineArgs]
    Representative Template Pipeline. See template_pipeline below.
    template_description str
    Describe the purpose of this template.
    privacyLevel String
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    templateName String
    Help users identify and select specific templates.
    templatePipelines List<Property Map>
    Representative Template Pipeline. See template_pipeline below.
    templateDescription String
    Describe the purpose of this template.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the ExperimentPlanTemplate resource produces the following output properties:

    CreateTime string
    The creation time of the resource.
    Id string
    The provider-assigned unique ID for this managed resource.
    TemplateId string
    The ID of the template.
    CreateTime string
    The creation time of the resource.
    Id string
    The provider-assigned unique ID for this managed resource.
    TemplateId string
    The ID of the template.
    createTime String
    The creation time of the resource.
    id String
    The provider-assigned unique ID for this managed resource.
    templateId String
    The ID of the template.
    createTime string
    The creation time of the resource.
    id string
    The provider-assigned unique ID for this managed resource.
    templateId string
    The ID of the template.
    create_time str
    The creation time of the resource.
    id str
    The provider-assigned unique ID for this managed resource.
    template_id str
    The ID of the template.
    createTime String
    The creation time of the resource.
    id String
    The provider-assigned unique ID for this managed resource.
    templateId String
    The ID of the template.

    Look up Existing ExperimentPlanTemplate Resource

    Get an existing ExperimentPlanTemplate resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: ExperimentPlanTemplateState, opts?: CustomResourceOptions): ExperimentPlanTemplate
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        create_time: Optional[str] = None,
        privacy_level: Optional[str] = None,
        template_description: Optional[str] = None,
        template_id: Optional[str] = None,
        template_name: Optional[str] = None,
        template_pipelines: Optional[Sequence[ExperimentPlanTemplateTemplatePipelineArgs]] = None) -> ExperimentPlanTemplate
    func GetExperimentPlanTemplate(ctx *Context, name string, id IDInput, state *ExperimentPlanTemplateState, opts ...ResourceOption) (*ExperimentPlanTemplate, error)
    public static ExperimentPlanTemplate Get(string name, Input<string> id, ExperimentPlanTemplateState? state, CustomResourceOptions? opts = null)
    public static ExperimentPlanTemplate get(String name, Output<String> id, ExperimentPlanTemplateState state, CustomResourceOptions options)
    resources:  _:    type: alicloud:eflo:ExperimentPlanTemplate    get:      id: ${id}
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    CreateTime string
    The creation time of the resource.
    PrivacyLevel string
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    TemplateDescription string
    Describe the purpose of this template.
    TemplateId string
    The ID of the template.
    TemplateName string
    Help users identify and select specific templates.
    TemplatePipelines List<Pulumi.AliCloud.Eflo.Inputs.ExperimentPlanTemplateTemplatePipeline>
    Representative Template Pipeline. See template_pipeline below.
    CreateTime string
    The creation time of the resource.
    PrivacyLevel string
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    TemplateDescription string
    Describe the purpose of this template.
    TemplateId string
    The ID of the template.
    TemplateName string
    Help users identify and select specific templates.
    TemplatePipelines []ExperimentPlanTemplateTemplatePipelineArgs
    Representative Template Pipeline. See template_pipeline below.
    createTime String
    The creation time of the resource.
    privacyLevel String
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    templateDescription String
    Describe the purpose of this template.
    templateId String
    The ID of the template.
    templateName String
    Help users identify and select specific templates.
    templatePipelines List<ExperimentPlanTemplateTemplatePipeline>
    Representative Template Pipeline. See template_pipeline below.
    createTime string
    The creation time of the resource.
    privacyLevel string
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    templateDescription string
    Describe the purpose of this template.
    templateId string
    The ID of the template.
    templateName string
    Help users identify and select specific templates.
    templatePipelines ExperimentPlanTemplateTemplatePipeline[]
    Representative Template Pipeline. See template_pipeline below.
    create_time str
    The creation time of the resource.
    privacy_level str
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    template_description str
    Describe the purpose of this template.
    template_id str
    The ID of the template.
    template_name str
    Help users identify and select specific templates.
    template_pipelines Sequence[ExperimentPlanTemplateTemplatePipelineArgs]
    Representative Template Pipeline. See template_pipeline below.
    createTime String
    The creation time of the resource.
    privacyLevel String
    Used to indicate the privacy level of the content or information. It can have the following optional parameters:

    • private: Indicates that the content is private and restricted to specific users or permission groups. Private content is usually not publicly displayed, and only authorized users can view or edit it.
    • public: Indicates that the content is public and can be accessed by anyone. Public content is usually viewable by all users and is suitable for sharing information or resources
    templateDescription String
    Describe the purpose of this template.
    templateId String
    The ID of the template.
    templateName String
    Help users identify and select specific templates.
    templatePipelines List<Property Map>
    Representative Template Pipeline. See template_pipeline below.

    Supporting Types

    ExperimentPlanTemplateTemplatePipeline, ExperimentPlanTemplateTemplatePipelineArgs

    EnvParams Pulumi.AliCloud.Eflo.Inputs.ExperimentPlanTemplateTemplatePipelineEnvParams
    Contains a series of parameters related to the environment. See env_params below.
    PipelineOrder int
    Indicates the sequence number of the pipeline node.
    Scene string
    The use of the template scenario. It can have the following optional parameters:

    • baseline: benchmark evaluation
    WorkloadId int
    Used to uniquely identify a specific payload.
    WorkloadName string
    The name used to represent a specific payload.
    SettingParams Dictionary<string, string>
    Represents additional parameters for the run.
    EnvParams ExperimentPlanTemplateTemplatePipelineEnvParams
    Contains a series of parameters related to the environment. See env_params below.
    PipelineOrder int
    Indicates the sequence number of the pipeline node.
    Scene string
    The use of the template scenario. It can have the following optional parameters:

    • baseline: benchmark evaluation
    WorkloadId int
    Used to uniquely identify a specific payload.
    WorkloadName string
    The name used to represent a specific payload.
    SettingParams map[string]string
    Represents additional parameters for the run.
    envParams ExperimentPlanTemplateTemplatePipelineEnvParams
    Contains a series of parameters related to the environment. See env_params below.
    pipelineOrder Integer
    Indicates the sequence number of the pipeline node.
    scene String
    The use of the template scenario. It can have the following optional parameters:

    • baseline: benchmark evaluation
    workloadId Integer
    Used to uniquely identify a specific payload.
    workloadName String
    The name used to represent a specific payload.
    settingParams Map<String,String>
    Represents additional parameters for the run.
    envParams ExperimentPlanTemplateTemplatePipelineEnvParams
    Contains a series of parameters related to the environment. See env_params below.
    pipelineOrder number
    Indicates the sequence number of the pipeline node.
    scene string
    The use of the template scenario. It can have the following optional parameters:

    • baseline: benchmark evaluation
    workloadId number
    Used to uniquely identify a specific payload.
    workloadName string
    The name used to represent a specific payload.
    settingParams {[key: string]: string}
    Represents additional parameters for the run.
    env_params ExperimentPlanTemplateTemplatePipelineEnvParams
    Contains a series of parameters related to the environment. See env_params below.
    pipeline_order int
    Indicates the sequence number of the pipeline node.
    scene str
    The use of the template scenario. It can have the following optional parameters:

    • baseline: benchmark evaluation
    workload_id int
    Used to uniquely identify a specific payload.
    workload_name str
    The name used to represent a specific payload.
    setting_params Mapping[str, str]
    Represents additional parameters for the run.
    envParams Property Map
    Contains a series of parameters related to the environment. See env_params below.
    pipelineOrder Number
    Indicates the sequence number of the pipeline node.
    scene String
    The use of the template scenario. It can have the following optional parameters:

    • baseline: benchmark evaluation
    workloadId Number
    Used to uniquely identify a specific payload.
    workloadName String
    The name used to represent a specific payload.
    settingParams Map<String>
    Represents additional parameters for the run.

    ExperimentPlanTemplateTemplatePipelineEnvParams, ExperimentPlanTemplateTemplatePipelineEnvParamsArgs

    CpuPerWorker int
    Number of central processing units (CPUs) allocated. This parameter affects the processing power of the computation, especially in tasks that require a large amount of parallel processing.
    GpuPerWorker int
    Number of graphics processing units (GPUs). GPUs are a key component in deep learning and large-scale data processing, so this parameter is very important for tasks that require graphics-accelerated computing.
    MemoryPerWorker int
    The amount of memory available. Memory size has an important impact on the performance and stability of the program, especially when dealing with large data sets or high-dimensional data.
    ShareMemory int
    Shared memory GB allocation
    WorkerNum int
    The total number of nodes. This parameter directly affects the parallelism and computing speed of the task, and a higher number of working nodes usually accelerates the completion of the task.
    CudaVersion string
    The version of CUDA(Compute Unified Device Architecture) used. CUDA is a parallel computing platform and programming model provided by NVIDIA. A specific version may affect the available GPU functions and performance optimization.
    GpuDriverVersion string
    The version of the GPU driver used. Driver version may affect GPU performance and compatibility, so it is important to ensure that the correct version is used
    NcclVersion string
    The NVIDIA Collective Communications Library(NCCL) version used. NCCL is a library for multi-GPU and multi-node communication. This parameter is particularly important for optimizing data transmission in distributed computing.
    PyTorchVersion string
    The version of the PyTorch framework used. PyTorch is a widely used deep learning library, and differences between versions may affect the performance and functional support of model training and inference.
    CpuPerWorker int
    Number of central processing units (CPUs) allocated. This parameter affects the processing power of the computation, especially in tasks that require a large amount of parallel processing.
    GpuPerWorker int
    Number of graphics processing units (GPUs). GPUs are a key component in deep learning and large-scale data processing, so this parameter is very important for tasks that require graphics-accelerated computing.
    MemoryPerWorker int
    The amount of memory available. Memory size has an important impact on the performance and stability of the program, especially when dealing with large data sets or high-dimensional data.
    ShareMemory int
    Shared memory GB allocation
    WorkerNum int
    The total number of nodes. This parameter directly affects the parallelism and computing speed of the task, and a higher number of working nodes usually accelerates the completion of the task.
    CudaVersion string
    The version of CUDA(Compute Unified Device Architecture) used. CUDA is a parallel computing platform and programming model provided by NVIDIA. A specific version may affect the available GPU functions and performance optimization.
    GpuDriverVersion string
    The version of the GPU driver used. Driver version may affect GPU performance and compatibility, so it is important to ensure that the correct version is used
    NcclVersion string
    The NVIDIA Collective Communications Library(NCCL) version used. NCCL is a library for multi-GPU and multi-node communication. This parameter is particularly important for optimizing data transmission in distributed computing.
    PyTorchVersion string
    The version of the PyTorch framework used. PyTorch is a widely used deep learning library, and differences between versions may affect the performance and functional support of model training and inference.
    cpuPerWorker Integer
    Number of central processing units (CPUs) allocated. This parameter affects the processing power of the computation, especially in tasks that require a large amount of parallel processing.
    gpuPerWorker Integer
    Number of graphics processing units (GPUs). GPUs are a key component in deep learning and large-scale data processing, so this parameter is very important for tasks that require graphics-accelerated computing.
    memoryPerWorker Integer
    The amount of memory available. Memory size has an important impact on the performance and stability of the program, especially when dealing with large data sets or high-dimensional data.
    shareMemory Integer
    Shared memory GB allocation
    workerNum Integer
    The total number of nodes. This parameter directly affects the parallelism and computing speed of the task, and a higher number of working nodes usually accelerates the completion of the task.
    cudaVersion String
    The version of CUDA(Compute Unified Device Architecture) used. CUDA is a parallel computing platform and programming model provided by NVIDIA. A specific version may affect the available GPU functions and performance optimization.
    gpuDriverVersion String
    The version of the GPU driver used. Driver version may affect GPU performance and compatibility, so it is important to ensure that the correct version is used
    ncclVersion String
    The NVIDIA Collective Communications Library(NCCL) version used. NCCL is a library for multi-GPU and multi-node communication. This parameter is particularly important for optimizing data transmission in distributed computing.
    pyTorchVersion String
    The version of the PyTorch framework used. PyTorch is a widely used deep learning library, and differences between versions may affect the performance and functional support of model training and inference.
    cpuPerWorker number
    Number of central processing units (CPUs) allocated. This parameter affects the processing power of the computation, especially in tasks that require a large amount of parallel processing.
    gpuPerWorker number
    Number of graphics processing units (GPUs). GPUs are a key component in deep learning and large-scale data processing, so this parameter is very important for tasks that require graphics-accelerated computing.
    memoryPerWorker number
    The amount of memory available. Memory size has an important impact on the performance and stability of the program, especially when dealing with large data sets or high-dimensional data.
    shareMemory number
    Shared memory GB allocation
    workerNum number
    The total number of nodes. This parameter directly affects the parallelism and computing speed of the task, and a higher number of working nodes usually accelerates the completion of the task.
    cudaVersion string
    The version of CUDA(Compute Unified Device Architecture) used. CUDA is a parallel computing platform and programming model provided by NVIDIA. A specific version may affect the available GPU functions and performance optimization.
    gpuDriverVersion string
    The version of the GPU driver used. Driver version may affect GPU performance and compatibility, so it is important to ensure that the correct version is used
    ncclVersion string
    The NVIDIA Collective Communications Library(NCCL) version used. NCCL is a library for multi-GPU and multi-node communication. This parameter is particularly important for optimizing data transmission in distributed computing.
    pyTorchVersion string
    The version of the PyTorch framework used. PyTorch is a widely used deep learning library, and differences between versions may affect the performance and functional support of model training and inference.
    cpu_per_worker int
    Number of central processing units (CPUs) allocated. This parameter affects the processing power of the computation, especially in tasks that require a large amount of parallel processing.
    gpu_per_worker int
    Number of graphics processing units (GPUs). GPUs are a key component in deep learning and large-scale data processing, so this parameter is very important for tasks that require graphics-accelerated computing.
    memory_per_worker int
    The amount of memory available. Memory size has an important impact on the performance and stability of the program, especially when dealing with large data sets or high-dimensional data.
    share_memory int
    Shared memory GB allocation
    worker_num int
    The total number of nodes. This parameter directly affects the parallelism and computing speed of the task, and a higher number of working nodes usually accelerates the completion of the task.
    cuda_version str
    The version of CUDA(Compute Unified Device Architecture) used. CUDA is a parallel computing platform and programming model provided by NVIDIA. A specific version may affect the available GPU functions and performance optimization.
    gpu_driver_version str
    The version of the GPU driver used. Driver version may affect GPU performance and compatibility, so it is important to ensure that the correct version is used
    nccl_version str
    The NVIDIA Collective Communications Library(NCCL) version used. NCCL is a library for multi-GPU and multi-node communication. This parameter is particularly important for optimizing data transmission in distributed computing.
    py_torch_version str
    The version of the PyTorch framework used. PyTorch is a widely used deep learning library, and differences between versions may affect the performance and functional support of model training and inference.
    cpuPerWorker Number
    Number of central processing units (CPUs) allocated. This parameter affects the processing power of the computation, especially in tasks that require a large amount of parallel processing.
    gpuPerWorker Number
    Number of graphics processing units (GPUs). GPUs are a key component in deep learning and large-scale data processing, so this parameter is very important for tasks that require graphics-accelerated computing.
    memoryPerWorker Number
    The amount of memory available. Memory size has an important impact on the performance and stability of the program, especially when dealing with large data sets or high-dimensional data.
    shareMemory Number
    Shared memory GB allocation
    workerNum Number
    The total number of nodes. This parameter directly affects the parallelism and computing speed of the task, and a higher number of working nodes usually accelerates the completion of the task.
    cudaVersion String
    The version of CUDA(Compute Unified Device Architecture) used. CUDA is a parallel computing platform and programming model provided by NVIDIA. A specific version may affect the available GPU functions and performance optimization.
    gpuDriverVersion String
    The version of the GPU driver used. Driver version may affect GPU performance and compatibility, so it is important to ensure that the correct version is used
    ncclVersion String
    The NVIDIA Collective Communications Library(NCCL) version used. NCCL is a library for multi-GPU and multi-node communication. This parameter is particularly important for optimizing data transmission in distributed computing.
    pyTorchVersion String
    The version of the PyTorch framework used. PyTorch is a widely used deep learning library, and differences between versions may affect the performance and functional support of model training and inference.

    Import

    Eflo Experiment Plan Template can be imported using the id, e.g.

    $ pulumi import alicloud:eflo/experimentPlanTemplate:ExperimentPlanTemplate example <id>

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    Alibaba Cloud pulumi/pulumi-alicloud
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the alicloud Terraform Provider.
    alicloud logo
    Alibaba Cloud v3.77.0 published on Friday, May 2, 2025 by Pulumi
    pulumi/pulumi-alicloud