Update README and versions for 23.06 branch (#708) (#720)

* Update README and versions for 23.06 branch

* Update README.md for 23.06

Author: mc-nv

Dockerfile

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver:23.05-py3
-ARG TRITONSDK_BASE_IMAGE=nvcr.io/nvidia/tritonserver:23.05-py3-sdk
+ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver:23.06-py3
+ARG TRITONSDK_BASE_IMAGE=nvcr.io/nvidia/tritonserver:23.06-py3-sdk
 
 ARG MODEL_ANALYZER_VERSION=1.30.0dev
 ARG MODEL_ANALYZER_CONTAINER_VERSION=23.07dev

README.md

@@ -20,9 +20,9 @@ limitations under the License.
 
 **LATEST RELEASE: You are currently on the main branch which tracks
 under-development progress towards the next release. The latest
-release of the Triton Model Analyzer is 1.28.0 and is available on
+release of the Triton Model Analyzer is 1.29.0 and is available on
 branch
-[r23.05](https://github.com/triton-inference-server/model_analyzer/tree/r23.05).**
+[r23.06](https://github.com/triton-inference-server/model_analyzer/tree/r23.06).**
 
 Triton Model Analyzer is a CLI tool which can help you find a more optimal configuration, on a given piece of hardware, for single, multiple, ensemble, or BLS models running on a [Triton Inference Server](https://github.com/triton-inference-server/server/). Model Analyzer will also generate reports to help you better understand the trade-offs of the different configurations along with their compute and memory requirements.
 <br><br>

docs/config.md

@@ -153,7 +153,7 @@ cpu_only_composing_models: <comma-delimited-string-list>
 [ reload_model_disable: <bool> | default: false]
 
 # Triton Docker image tag used when launching using Docker mode
-[ triton_docker_image: <string> | default: nvcr.io/nvidia/tritonserver:23.05-py3 ]
+[ triton_docker_image: <string> | default: nvcr.io/nvidia/tritonserver:23.06-py3 ]
 
 # Triton Server HTTP endpoint url used by Model Analyzer client"
 [ triton_http_endpoint: <string> | default: localhost:8000 ]

docs/kubernetes_deploy.md

@@ -79,7 +79,7 @@ images:
 
   triton:
     image: nvcr.io/nvidia/tritonserver
-    tag: 23.05-py3
+    tag: 23.06-py3
 ```
 
 The model analyzer executable uses the config file defined in `helm-chart/templates/config-map.yaml`. This config can be modified to supply arguments to model analyzer. Only the content under the `config.yaml` section of the file should be modified.

docs/mm_quick_start.md

@@ -49,7 +49,7 @@ git pull origin main
 **1. Pull the SDK container:**
 
 ```
-docker pull nvcr.io/nvidia/tritonserver:23.05-py3-sdk
+docker pull nvcr.io/nvidia/tritonserver:23.06-py3-sdk
 ```
 
 **2. Run the SDK container**
@@ -59,7 +59,7 @@ docker run -it --gpus all \
       -v /var/run/docker.sock:/var/run/docker.sock \
       -v $(pwd)/examples/quick-start:$(pwd)/examples/quick-start \
       -v <path-to-output-model-repo>:<path-to-output-model-repo> \
-      --net=host nvcr.io/nvidia/tritonserver:23.05-py3-sdk
+      --net=host nvcr.io/nvidia/tritonserver:23.06-py3-sdk
 ```
 
 **Replacing** `<path-to-output-model-repo>` with the

docs/quick_start.md

@@ -49,7 +49,7 @@ git pull origin main
 **1. Pull the SDK container:**
 
 ```
-docker pull nvcr.io/nvidia/tritonserver:23.05-py3-sdk
+docker pull nvcr.io/nvidia/tritonserver:23.06-py3-sdk
 ```
 
 **2. Run the SDK container**
@@ -59,7 +59,7 @@ docker run -it --gpus all \
       -v /var/run/docker.sock:/var/run/docker.sock \
       -v $(pwd)/examples/quick-start:$(pwd)/examples/quick-start \
       -v <path-to-output-model-repo>:<path-to-output-model-repo> \
-      --net=host nvcr.io/nvidia/tritonserver:23.05-py3-sdk
+      --net=host nvcr.io/nvidia/tritonserver:23.06-py3-sdk
 ```
 
 **Replacing** `<path-to-output-model-repo>` with the

helm-chart/values.yaml

@@ -41,4 +41,4 @@ images:
 
   triton:
     image: nvcr.io/nvidia/tritonserver
-    tag: 23.05-py3
+    tag: 23.06-py3

model_analyzer/config/input/config_defaults.py

@@ -54,7 +54,7 @@
 DEFAULT_RUN_CONFIG_PROFILE_MODELS_CONCURRENTLY_ENABLE = False
 DEFAULT_REQUEST_RATE_SEARCH_ENABLE = False
 DEFAULT_TRITON_LAUNCH_MODE = 'local'
-DEFAULT_TRITON_DOCKER_IMAGE = 'nvcr.io/nvidia/tritonserver:23.05-py3'
+DEFAULT_TRITON_DOCKER_IMAGE = 'nvcr.io/nvidia/tritonserver:23.06-py3'
 DEFAULT_TRITON_HTTP_ENDPOINT = 'localhost:8000'
 DEFAULT_TRITON_GRPC_ENDPOINT = 'localhost:8001'
 DEFAULT_TRITON_METRICS_URL = 'http://localhost:8002/metrics'