CreateStreamGroupFluentBuilder

aws_sdk_gameliftstreams::operation::create_stream_group::builders

Struct CreateStreamGroupFluentBuilder 

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pub struct CreateStreamGroupFluentBuilder { /* private fields */ }
Expand description

Fluent builder constructing a request to CreateStreamGroup.

Manage how Amazon GameLift Streams streams your applications by using a stream group. A stream group is a collection of resources that Amazon GameLift Streams uses to stream your application to end-users. When you create a stream group, you specify an application to stream by default and the type of hardware to use, such as the graphical processing unit (GPU). You can also link additional applications, which allows you to stream those applications using this stream group. Depending on your expected users, you also scale the number of concurrent streams you want to support at one time, and in what locations.

Stream capacity represents the number of concurrent streams that can be active at a time. You set stream capacity per location, per stream group. There are two types of capacity, always-on and on-demand:

  • Always-on: The streaming capacity that is allocated and ready to handle stream requests without delay. You pay for this capacity whether it's in use or not. Best for quickest time from streaming request to streaming session. Default is 1 when creating a stream group or adding a location.

  • On-demand: The streaming capacity that Amazon GameLift Streams can allocate in response to stream requests, and then de-allocate when the session has terminated. This offers a cost control measure at the expense of a greater startup time (typically under 5 minutes). Default is 0 when creating a stream group or adding a location.

To adjust the capacity of any ACTIVE stream group, call UpdateStreamGroup.

If the request is successful, Amazon GameLift Streams begins creating the stream group. Amazon GameLift Streams assigns a unique ID to the stream group resource and sets the status to ACTIVATING. When the stream group reaches ACTIVE status, you can start stream sessions by using StartStreamSession. To check the stream group's status, call GetStreamGroup.

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impl CreateStreamGroupFluentBuilder

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pub fn as_input(&self) -> &CreateStreamGroupInputBuilder

Access the CreateStreamGroup as a reference.

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pub async fn send( self, ) -> Result<CreateStreamGroupOutput, SdkError<CreateStreamGroupError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

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pub fn customize( self, ) -> CustomizableOperation<CreateStreamGroupOutput, CreateStreamGroupError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

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pub fn description(self, input: impl Into<String>) -> Self

A descriptive label for the stream group.

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pub fn set_description(self, input: Option<String>) -> Self

A descriptive label for the stream group.

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pub fn get_description(&self) -> &Option<String>

A descriptive label for the stream group.

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pub fn stream_class(self, input: StreamClass) -> Self

The target stream quality for sessions that are hosted in this stream group. Set a stream class that is appropriate to the type of content that you're streaming. Stream class determines the type of computing resources Amazon GameLift Streams uses and impacts the cost of streaming. The following options are available:

A stream class can be one of the following:

  • gen5n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen5n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 12 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen5n_ultra (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 8 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen4n_ultra (NVIDIA, ultra) Supports applications with high 3D scene complexity. Uses dedicated NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

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pub fn set_stream_class(self, input: Option<StreamClass>) -> Self

The target stream quality for sessions that are hosted in this stream group. Set a stream class that is appropriate to the type of content that you're streaming. Stream class determines the type of computing resources Amazon GameLift Streams uses and impacts the cost of streaming. The following options are available:

A stream class can be one of the following:

  • gen5n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen5n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 12 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen5n_ultra (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 8 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen4n_ultra (NVIDIA, ultra) Supports applications with high 3D scene complexity. Uses dedicated NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

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pub fn get_stream_class(&self) -> &Option<StreamClass>

The target stream quality for sessions that are hosted in this stream group. Set a stream class that is appropriate to the type of content that you're streaming. Stream class determines the type of computing resources Amazon GameLift Streams uses and impacts the cost of streaming. The following options are available:

A stream class can be one of the following:

  • gen5n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen5n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 12 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen5n_ultra (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Uses dedicated NVIDIA A10G Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 24 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_win2022 (NVIDIA, ultra) Supports applications with extremely high 3D scene complexity. Runs applications on Microsoft Windows Server 2022 Base and supports DirectX 12. Compatible with Unreal Engine versions up through 5.4, 32 and 64-bit applications, and anti-cheat technology. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

  • gen4n_high (NVIDIA, high) Supports applications with moderate to high 3D scene complexity. Uses NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 4 vCPUs, 16 GB RAM, 8 GB VRAM

    • Tenancy: Supports up to 2 concurrent stream sessions

  • gen4n_ultra (NVIDIA, ultra) Supports applications with high 3D scene complexity. Uses dedicated NVIDIA T4 Tensor GPU.

    • Reference resolution: 1080p

    • Reference frame rate: 60 fps

    • Workload specifications: 8 vCPUs, 32 GB RAM, 16 GB VRAM

    • Tenancy: Supports 1 concurrent stream session

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pub fn default_application_identifier(self, input: impl Into<String>) -> Self

The unique identifier of the Amazon GameLift Streams application that you want to set as the default application in a stream group. The application that you specify must be in READY status. The default application is pre-cached on always-on compute resources, reducing stream startup times. Other applications are automatically cached as needed.

If you do not link an application when you create a stream group, you will need to link one later, before you can start streaming, using AssociateApplications.

This value is an Amazon Resource Name (ARN) or ID that uniquely identifies the application resource. Example ARN: arn:aws:gameliftstreams:us-west-2:111122223333:application/a-9ZY8X7Wv6. Example ID: a-9ZY8X7Wv6.

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pub fn set_default_application_identifier(self, input: Option<String>) -> Self

The unique identifier of the Amazon GameLift Streams application that you want to set as the default application in a stream group. The application that you specify must be in READY status. The default application is pre-cached on always-on compute resources, reducing stream startup times. Other applications are automatically cached as needed.

If you do not link an application when you create a stream group, you will need to link one later, before you can start streaming, using AssociateApplications.

This value is an Amazon Resource Name (ARN) or ID that uniquely identifies the application resource. Example ARN: arn:aws:gameliftstreams:us-west-2:111122223333:application/a-9ZY8X7Wv6. Example ID: a-9ZY8X7Wv6.

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pub fn get_default_application_identifier(&self) -> &Option<String>

The unique identifier of the Amazon GameLift Streams application that you want to set as the default application in a stream group. The application that you specify must be in READY status. The default application is pre-cached on always-on compute resources, reducing stream startup times. Other applications are automatically cached as needed.

If you do not link an application when you create a stream group, you will need to link one later, before you can start streaming, using AssociateApplications.

This value is an Amazon Resource Name (ARN) or ID that uniquely identifies the application resource. Example ARN: arn:aws:gameliftstreams:us-west-2:111122223333:application/a-9ZY8X7Wv6. Example ID: a-9ZY8X7Wv6.

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pub fn location_configurations(self, input: LocationConfiguration) -> Self

Appends an item to LocationConfigurations.

To override the contents of this collection use set_location_configurations.

A set of one or more locations and the streaming capacity for each location.

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pub fn set_location_configurations( self, input: Option<Vec<LocationConfiguration>>, ) -> Self

A set of one or more locations and the streaming capacity for each location.

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pub fn get_location_configurations(&self) -> &Option<Vec<LocationConfiguration>>

A set of one or more locations and the streaming capacity for each location.

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pub fn tags(self, k: impl Into<String>, v: impl Into<String>) -> Self

Adds a key-value pair to Tags.

To override the contents of this collection use set_tags.

A list of labels to assign to the new stream group resource. Tags are developer-defined key-value pairs. Tagging Amazon Web Services resources is useful for resource management, access management and cost allocation. See Tagging Amazon Web Services Resources in the Amazon Web Services General Reference. You can use TagResource to add tags, UntagResource to remove tags, and ListTagsForResource to view tags on existing resources.

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pub fn set_tags(self, input: Option<HashMap<String, String>>) -> Self

A list of labels to assign to the new stream group resource. Tags are developer-defined key-value pairs. Tagging Amazon Web Services resources is useful for resource management, access management and cost allocation. See Tagging Amazon Web Services Resources in the Amazon Web Services General Reference. You can use TagResource to add tags, UntagResource to remove tags, and ListTagsForResource to view tags on existing resources.

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pub fn get_tags(&self) -> &Option<HashMap<String, String>>

A list of labels to assign to the new stream group resource. Tags are developer-defined key-value pairs. Tagging Amazon Web Services resources is useful for resource management, access management and cost allocation. See Tagging Amazon Web Services Resources in the Amazon Web Services General Reference. You can use TagResource to add tags, UntagResource to remove tags, and ListTagsForResource to view tags on existing resources.

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pub fn client_token(self, input: impl Into<String>) -> Self

A unique identifier that represents a client request. The request is idempotent, which ensures that an API request completes only once. When users send a request, Amazon GameLift Streams automatically populates this field.

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pub fn set_client_token(self, input: Option<String>) -> Self

A unique identifier that represents a client request. The request is idempotent, which ensures that an API request completes only once. When users send a request, Amazon GameLift Streams automatically populates this field.

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pub fn get_client_token(&self) -> &Option<String>

A unique identifier that represents a client request. The request is idempotent, which ensures that an API request completes only once. When users send a request, Amazon GameLift Streams automatically populates this field.

Trait Implementations§

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impl Clone for CreateStreamGroupFluentBuilder

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fn clone(&self) -> CreateStreamGroupFluentBuilder

Returns a duplicate of the value. Read more
1.0.0 · Source§

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for CreateStreamGroupFluentBuilder

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

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Enable wrapping using .quirk():

use yansi::{Paint, Quirk};

painted.quirk(Quirk::Wrap);

Enable wrapping using wrap().

use yansi::Paint;

painted.wrap();
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fn mask(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: Mask].

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println!("{}", value.mask());
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fn wrap(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: Wrap].

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println!("{}", value.wrap());
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fn linger(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: Linger].

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println!("{}", value.linger());
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fn clear(&self) -> Painted<&T>

👎Deprecated since 1.0.1: renamed to resetting() due to conflicts with Vec::clear(). The clear() method will be removed in a future release.

Returns self with the quirk() set to [Quirk :: Clear].

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println!("{}", value.clear());
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fn resetting(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: Resetting].

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println!("{}", value.resetting());
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fn bright(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: Bright].

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println!("{}", value.bright());
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fn on_bright(&self) -> Painted<&T>

Returns self with the quirk() set to [Quirk :: OnBright].

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println!("{}", value.on_bright());
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fn whenever(&self, value: Condition) -> Painted<&T>

Conditionally enable styling based on whether the Condition value applies. Replaces any previous condition.

See the crate level docs for more details.

§Example

Enable styling painted only when both stdout and stderr are TTYs:

use yansi::{Paint, Condition};

painted.red().on_yellow().whenever(Condition::STDOUTERR_ARE_TTY);
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fn new(self) -> Painted<Self>
where Self: Sized,

Create a new Painted with a default Style. Read more
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fn paint<S>(&self, style: S) -> Painted<&Self>
where S: Into<Style>,

Apply a style wholesale to self. Any previous style is replaced. Read more
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impl<T> Same for T

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type Output = T

Should always be Self
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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.
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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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impl<T, U> TryFrom<U> for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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impl<T> WithSubscriber for T

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fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self>
where S: Into<Dispatch>,

Attaches the provided Subscriber to this type, returning a WithDispatch wrapper. Read more
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fn with_current_subscriber(self) -> WithDispatch<Self>

Attaches the current default Subscriber to this type, returning a WithDispatch wrapper. Read more
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impl<T> ErasedDestructor for T
where T: 'static,