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Add documentation on request cancellation (#6403) (#6407)
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* Add documentation on request cancellation

* Include python backend

* Update docs/user_guide/request_cancellation.md



* Update docs/user_guide/request_cancellation.md



* Update docs/README.md



* Update docs/user_guide/request_cancellation.md



* Remove inflight term from the main documentation

* Address review comments

* Fix

* Update docs/user_guide/request_cancellation.md



* Fix

---------

Co-authored-by: Iman Tabrizian <iman.tabrizian@gmail.com>
Co-authored-by: Neelay Shah <neelays@nvidia.com>
Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>
Co-authored-by: Jacky <18255193+kthui@users.noreply.github.com>
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3 changes: 3 additions & 0 deletions docs/README.md
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Expand Up @@ -69,6 +69,7 @@ The User Guide describes how to configure Triton, organize and configure your mo
* Collecting Server Metrics [[Overview](README.md#metrics) || [Details](user_guide/metrics.md)]
* Supporting Custom Ops/layers [[Overview](README.md#framework-custom-operations) || [Details](user_guide/custom_operations.md)]
* Using the Client API [[Overview](README.md#client-libraries-and-examples) || [Details](https://github.com/triton-inference-server/client)]
* Cancelling Inference Requests [[Overview](README.md#cancelling-inference-requests) || [Details](user_guide/request_cancellation.md)]
* Analyzing Performance [[Overview](README.md#performance-analysis)]
* Deploying on edge (Jetson) [[Overview](README.md#jetson-and-jetpack)]
* Debugging Guide [Details](./user_guide/debugging_guide.md)
Expand Down Expand Up @@ -165,6 +166,8 @@ Use the [Triton Client](https://github.com/triton-inference-server/client) API t
- [Java/Scala](https://github.com/triton-inference-server/client/tree/main/src/grpc_generated/java)
- [Javascript](https://github.com/triton-inference-server/client/tree/main/src/grpc_generated/javascript)
- [Shared Memory Extension](protocol/extension_shared_memory.md)
### Cancelling Inference Requests
Triton can detect and handle requests that have been cancelled from the client-side. This [document](user_guide/request_cancellation.md) discusses scope and limitations of the feature.
### Performance Analysis
Understanding Inference performance is key to better resource utilization. Use Triton's Tools to costomize your deployment.
- [Performance Tuning Guide](user_guide/performance_tuning.md)
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101 changes: 101 additions & 0 deletions docs/user_guide/request_cancellation.md
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# Request Cancellation

Starting from 23.10, Triton supports handling request cancellation received
from the gRPC client or a C API user. Long running inference requests such
as for auto generative large language models may run for an indeterminate
amount of time or indeterminate number of steps. Additionally clients may
enqueue a large number of requests as part of a sequence or request stream
and later determine the results are no longer needed. Continuing to process
requests whose results are no longer required can significantly impact server
resources.

## Issuing Request Cancellation

### Triton C API

[In-Process Triton Server C API](../customization_guide/inference_protocols.md#in-process-triton-server-api) has been enhanced with `TRITONSERVER_InferenceRequestCancel`
and `TRITONSERVER_InferenceRequestIsCancelled` to issue cancellation and query
whether cancellation has been issued on an inflight request respectively. Read more
about the APIs in [tritonserver.h](https://github.com/triton-inference-server/core/blob/main/include/triton/core/tritonserver.h).


### gRPC Endpoint

In addition, [gRPC endpoint](../customization_guide/inference_protocols.md#httprest-and-grpc-protocols) can
now detect cancellation from the client and attempt to terminate request.
At present, only gRPC python client supports issuing request cancellation
to the server endpoint. See [request-cancellation](https://github.com/triton-inference-server/client#request-cancellation)
for more details on how to issue requests from the client-side.
See gRPC guide on RPC [cancellation](https://grpc.io/docs/guides/cancellation/) for
finer details.

## Handling in Triton Core

Triton core checks for requests that have been cancelled at some critical points
when using [dynamic](./model_configuration.md#dynamic-batcher) or
[sequence](./model_configuration.md#sequence-batcher) batching. The checking is
also performed between each
[ensemble](./model_configuration.md#ensemble-scheduler) steps and terminates
further processing if the request is cancelled.

On detecting a cancelled request, Triton core responds with CANCELLED status. If a request
is cancelled when using [sequence_batching](./model_configuration.md#sequence-batcher),
then all the pending requests in the same sequence will also be cancelled. The sequence
is represented by the requests that has identical sequence id.

**Note**: Currently, Triton core does not detect cancellation status of a request once
it is forwarded to [rate limiter](./rate_limiter.md). Improving the request cancellation
detection and handling within Triton core is work in progress.

## Handling in Backend

Upon receiving request cancellation, triton does its best to terminate request
at various points. However, once a request has been given to the backend
for execution, it is upto the individual backends to detect and handle
request termination.
Currently, the following backends support early termination:
- [vLLM backend](https://github.com/triton-inference-server/vllm_backend)
- [python backend](https://github.com/triton-inference-server/python_backend)

Python backend is a special case where we expose the APIs to detect cancellation
status of the request but it is up to the `model.py` developer to detect whether
the request is cancelled and terminate further execution.

**For the backend developer**: The backend APIs have also been enhanced to let the
backend detect whether the request received from Triton core has been cancelled.
See `TRITONBACKEND_RequestIsCancelled` and `TRITONBACKEND_ResponseFactoryIsCancelled`
in [tritonbackend.h](https://github.com/triton-inference-server/core/blob/main/include/triton/core/tritonbackend.h)
for more details. The backend upon detecting request cancellation can stop processing
it any further.
The Python models running behind Python backend can also query the cancellation status
of request and response_sender. See [this](https://github.com/triton-inference-server/python_backend#request-cancellation-handling)
section in python backend documentation for more details.

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