Update README and docs post-20.10 release (#2172)

README.md

@@ -32,9 +32,9 @@
 
 **LATEST RELEASE: You are currently on the master branch which tracks
 under-development progress towards the next release. The latest
-release of the Triton Inference Server is 2.3.0 and is available on
+release of the Triton Inference Server is 2.4.0 and is available on
 branch
-[r20.09](https://github.com/triton-inference-server/server/tree/r20.09).**
+[r20.10](https://github.com/triton-inference-server/server/tree/r20.10).**
 
 Triton Inference Server provides a cloud and edge inferencing solution
 optimized for both CPUs and GPUs. Triton supports an HTTP/REST and
@@ -44,11 +44,11 @@ available as a shared library with a C API that allows the full
 functionality of Triton to be included directly in an
 application.
 
-The current release of the Triton Inference Server is 2.3.0 and
-corresponds to the 20.09 release of the tensorrtserver container on
+The current release of the Triton Inference Server is 2.4.0 and
+corresponds to the 20.10 release of the tensorrtserver container on
 [NVIDIA GPU Cloud (NGC)](https://ngc.nvidia.com). The branch for this
 release is
-[r20.09](https://github.com/triton-inference-server/server/tree/r20.09).
+[r20.10](https://github.com/triton-inference-server/server/tree/r20.10).
 
 ## Features
 

deploy/single_server/values.yaml

@@ -27,7 +27,7 @@
 replicaCount: 1
 
 image:
-  imageName: nvcr.io/nvidia/tritonserver:20.08-py3
+  imageName: nvcr.io/nvidia/tritonserver:20.10-py3
   pullPolicy: IfNotPresent
   modelRepositoryPath: gs://triton-inference-server-repository/model_repository
   numGpus: 1

docs/build.md

@@ -74,7 +74,7 @@ $ ./build.py --version=0.0.0 --container-version=20.10dev ...
 If you are building on master/main branch then <container tag> should
 be set to "main". If you are building on a release branch you should
 set the <container tag> to match. For example, if you are building on
-the r20.09 branch you should set <container tag> to be "r20.09". If
+the r20.10 branch you should set <container tag> to be "r20.10". If
 can use a different <container tag> for a component to instead use the
 corresponding branch/tag in the build. For example, if you have a
 branch called "mybranch" in the identity_backend repo that you want to

docs/client_libraries.md

@@ -150,7 +150,7 @@ under-development version). The branch you use for the client build
 should match the version of Triton you are using.
 
 ```bash
-$ git checkout r20.09
+$ git checkout r20.10
 ```
 
 Then, issue the following command to build the C++ client library and
@@ -187,7 +187,7 @@ want to build (or the master branch if you want to build the
 under-development version).
 
 ```bash
-$ git checkout r20.09
+$ git checkout r20.10
 ```
 
 #### Ubuntu 18.04

docs/custom_operations.md

@@ -64,7 +64,7 @@ simple way to ensure you are using the correct version of TensorRT is
 to use the [NGC TensorRT
 container](https://ngc.nvidia.com/catalog/containers/nvidia:tensorrt)
 corresponding to the Triton container. For example, if you are using
-the 20.09 version of Triton, use the 20.09 version of the TensorRT
+the 20.10 version of Triton, use the 20.10 version of the TensorRT
 container.
 
 ## TensorFlow
@@ -108,7 +108,7 @@ simple way to ensure you are using the correct version of TensorFlow
 is to use the [NGC TensorFlow
 container](https://ngc.nvidia.com/catalog/containers/nvidia:tensorflow)
 corresponding to the Triton container. For example, if you are using
-the 20.09 version of Triton, use the 20.09 version of the TensorFlow
+the 20.10 version of Triton, use the 20.10 version of the TensorFlow
 container.
 
 ## PyTorch
@@ -158,7 +158,7 @@ simple way to ensure you are using the correct version of PyTorch is
 to use the [NGC PyTorch
 container](https://ngc.nvidia.com/catalog/containers/nvidia:pytorch)
 corresponding to the Triton container. For example, if you are using
-the 20.09 version of Triton, use the 20.09 version of the PyTorch
+the 20.10 version of Triton, use the 20.10 version of the PyTorch
 container.
 
 ## ONNX