Update README and docs post-20.07 release

README.rst

@@ -32,16 +32,16 @@ NVIDIA Triton Inference Server
 
     **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 2.0.0 and
-    is available on branch** `r20.06
-    <https://github.com/NVIDIA/triton-inference-server/tree/r20.06>`_.
+    latest release of the Triton Inference Server is 2.1.0 and
+    is available on branch** `r20.07
+    <https://github.com/NVIDIA/triton-inference-server/tree/r20.07>`_.
 
     **Triton V2: Starting with the 20.06 release, Triton moves to
     version 2. The master branch currently tracks V2 development and
     is likely to be more unstable than usual due to the significant
     changes during the transition from V1 to V2. A legacy V1 version
     of Triton will be released from the master-v1 branch. The V1
-    version of Triton is deprecated and no releases beyond 20.06 are
+    version of Triton is deprecated and no releases beyond 20.07 are
     planned. More information on the V1 and V2 transition is available
     in** `Roadmap
     <https://github.com/NVIDIA/triton-inference-server/blob/master/README.rst#roadmap>`_.
@@ -131,11 +131,11 @@ features:
 
 .. overview-end-marker-do-not-remove
 
-The current release of the Triton Inference Server is 2.0.0 and
-corresponds to the 20.06 release of the tensorrtserver container on
+The current release of the Triton Inference Server is 2.1.0 and
+corresponds to the 20.07 release of the tensorrtserver container on
 `NVIDIA GPU Cloud (NGC) <https://ngc.nvidia.com>`_. The branch for
-this release is `r20.06
-<https://github.com/NVIDIA/triton-inference-server/tree/r20.06>`_.
+this release is `r20.07
+<https://github.com/NVIDIA/triton-inference-server/tree/r20.07>`_.
 
 Backwards Compatibility
 -----------------------

deploy/single_server/values.yaml

@@ -27,7 +27,7 @@
 replicaCount: 1
 
 image:
-  imageName: nvcr.io/nvidia/tritonserver:20.06-py3
+  imageName: nvcr.io/nvidia/tritonserver:20.07-py3
   pullPolicy: IfNotPresent
   modelRepositoryPath: gs://triton-inference-server-repository/model_repository
   numGpus: 1

docs/build.rst

@@ -57,7 +57,7 @@ to the root of the repo and checkout the release version of the branch
 that you want to build (or the master branch if you want to build the
 under-development version)::
 
-  $ git checkout r20.06
+  $ git checkout r20.07
 
 Then use docker to build::
 
@@ -104,7 +104,7 @@ the root of the repo and checkout the release version of the branch
 that you want to build (or the master branch if you want to build the
 under-development version)::
 
-  $ git checkout r20.06
+  $ git checkout r20.07
 
 Next you must build or install each framework backend you want to
 enable in Triton, configure the build to enable the desired features,

docs/client_library.rst

@@ -66,7 +66,7 @@ you want to build (or the master branch if you want to build the
 under-development version). The branch you use for the client build
 should match the version of Triton you are using::
 
-  $ git checkout r20.06
+  $ git checkout r20.07
 
 Then, issue the following command to build the C++ client library and
 the Python wheel files for the Python client library::
@@ -104,7 +104,7 @@ of the repo and checkout the release version of the branch that you
 want to build (or the master branch if you want to build the
 under-development version)::
 
-  $ git checkout r20.06
+  $ git checkout r20.07
 
 Ubuntu 18.04
 ............

docs/install.rst

@@ -48,7 +48,7 @@ the most recent version of CUDA, Docker, and nvidia-docker.
 After performing the above setup, you can pull the Triton container
 using the following command::
 
-  docker pull nvcr.io/nvidia/tritonserver:20.06-py3
+  docker pull nvcr.io/nvidia/tritonserver:20.07-py3
 
-Replace *20.06* with the version of inference server that you want to
+Replace *20.07* with the version of inference server that you want to
 pull.

docs/quickstart.rst

@@ -57,7 +57,7 @@ following prerequisite steps:
   be sure to select the r<xx.yy> release branch that corresponds to
   the version of Triton you want to use::
 
-  $ git checkout r20.06
+  $ git checkout r20.07
 
 * Create a model repository containing one or more models that you
   want Triton to serve. An example model repository is included in the
@@ -109,7 +109,7 @@ the GitHub repo and checkout the release version of the branch that
 you want to build (or the master branch if you want to build the
 under-development version)::
 
-  $ git checkout r20.06
+  $ git checkout r20.07
 
 Then use docker to build::
 

docs/run.rst

@@ -64,7 +64,7 @@ sure to checkout the release version of the branch that corresponds to
 the server you are using (or the master branch if you are using a
 server build from master)::
 
-  $ git checkout r20.06
+  $ git checkout r20.07
   $ cd docs/examples
   $ ./fetch_models.sh
 
@@ -105,7 +105,7 @@ you pulled from NGC or built locally::
   $ docker run --gpus=1 --rm -p8000:8000 -p8001:8001 -p8002:8002 -v/path/to/model/repository:/models <tritonserver image name> tritonserver --model-repository=/models
 
 Where *<tritonserver image name>* will be something like
-**nvcr.io/nvidia/tritonserver:20.06-py3** if you :ref:`pulled the
+**nvcr.io/nvidia/tritonserver:20.07-py3** if you :ref:`pulled the
 container from the NGC registry <section-installing-triton>`, or
 **tritonserver** if you :ref:`built it from source
 <section-building>`.