Updates README.md to include instructions for launching Triton (nv-mo…

…rpheus#289)

Also updates:
* Git LFS instructions
* Software requirements
* Specifics that apply to all users were moved from `CONTRIBUTING.md` to `README.md`
* Default version of Triton used by Validation scripts updated to 22.06 

Fixes nv-morpheus#288

Authors:
  - David Gardner (https://github.com/dagardner-nv)

Approvers:
  - Michael Demoret (https://github.com/mdemoret-nv)
  - Pete MacKinnon (https://github.com/pdmack)

URL: nv-morpheus#289

CONTRIBUTING.md

@@ -65,44 +65,15 @@ cd $MORPHEUS_ROOT
 ```
 The large model and data files in this repo are stored using [Git Large File Storage (LFS)](https://git-lfs.github.com/). These files will be required for running the training/validation scripts and example pipelines for the Morpheus pre-trained models.
 
-By default only those files stored in LFS strictly needed for running Morpheus are included when the Morpheus repository is cloned. Additional datasets can be downloaded using the `scripts/fetch_data.py` script. Usage of the script is as follows:
-```bash
-scripts/fetch_data.py fetch <dataset> [<dataset>...]
-```
-
-At time of writing the defined datasets are:
-* all - Metaset includes all others
-* examples - Data needed by scripts in the `examples` subdir
-* models - Morpheus models (largest dataset)
-* tests - Data used by unittests
-* validation - Subset of the models dataset needed by some unittests
-
-To download just the examples and models:
-```bash
-scripts/fetch_data.py fetch examples models
-```
-
-To download the data needed for unittests:
-```bash
-scripts/fetch_data.py fetch tests validation
-```
-
-If `Git LFS` is not installed before cloning the repository, the large files will not be pulled. If this is the case, follow the instructions for installing `Git LFS` from [here](https://git-lfs.github.com/), and then run the following command.
-```bash
-scripts/fetch_data.py fetch all
-```
+By default only those files stored in LFS strictly needed for running Morpheus are included when the Morpheus repository is cloned. Additional datasets can be downloaded using the `scripts/fetch_data.py` script. See the section [Git LFS](README.md#git-lfs) of the [README.md](README.md) file for details on this.
 
 ### Build in Docker Container
 
 This workflow utilizes a docker container to set up most dependencies ensuring a consistent environment.
 
 #### Prerequisites
 
-- Pascal architecture or better
-- NVIDIA driver `450.80.02` or higher
-- [Docker](https://docs.docker.com/get-docker/)
-- [The NVIDIA container toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker)
-
+1. Ensure all [requirements](README.md#requirements) from [README.md](README.md) are met.
 1. Build the development container
    ```bash
    ./docker/build_container_dev.sh
@@ -177,9 +148,9 @@ Note: These instructions assume the user is using `mamba` instead of `conda` sin
 
 #### Prerequisites
 
-- Pascal architecture or better
+- Pascal architecture GPU or better
 - NVIDIA driver `450.80.02` or higher
-- [CUDA 11.0+](https://developer.nvidia.com/cuda-downloads)
+- [CUDA 11.5](https://developer.nvidia.com/cuda-11-5-2-download-archive)
 - `conda` and `mamba`
   - See the [Getting Started Guide](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) if `conda` is not already installed
   - Install `mamba`:
@@ -329,22 +300,6 @@ Launching a full production Kafka cluster is outside the scope of this project.
 
       **Note:** This will consume messages.
 
-### Launching Triton Server
-
-Many of the validation tests and example workflows require a Triton server to function. To launch Triton server, use the following command:
-
-```bash
-docker run --rm -ti --gpus=all -p8000:8000 -p8001:8001 -p8002:8002 -v $PWD/models:/models \
-  nvcr.io/nvidia/tritonserver:21.12-py3 \
-    tritonserver --model-repository=/models/triton-model-repo \
-                 --exit-on-error=false \
-                 --model-control-mode=explicit \
-                 --load-model abp-nvsmi-xgb \
-                 --load-model sid-minibert-onnx \
-                 --load-model phishing-bert-onnx
-```
-This will launch Triton using port 8001 for the GRPC server. This needs to match the Morpheus configuration.
-
 ### Pipeline Validation
 
 To verify that all pipelines are working correctly, validation scripts have been added at `${MORPHEUS_ROOT}/scripts/validation`. There are scripts for each of the main workflows: Anomalous Behavior Profiling (ABP), Humans-as-Machines-Machines-as-Humans (HAMMAH), Phishing Detection (Phishing), and Sensitive Information Detection (SID).

README.md

@@ -21,33 +21,53 @@ More advanced users, or those who are interested in using the latest pre-release
 The following sections must be followed prior to building the Morpheus container or building Morpheus from source.
 
 #### Requirements
-- Pascal architecture or better
+- Pascal architecture GPU or better
 - NVIDIA driver `450.80.02` or higher
 - [Docker](https://docs.docker.com/get-docker/)
 - [The NVIDIA container toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker)
+- [NVIDIA Triton Inference Server](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/tritonserver) `22.06` or higher
 - [Git LFS](https://git-lfs.github.com/)
 
+
+#### Clone the Repository
+
+```bash
+MORPHEUS_ROOT=$(pwd)/morpheus
+git clone https://github.com/NVIDIA/Morpheus.git $MORPHEUS_ROOT
+cd $MORPHEUS_ROOT
+```
+
 #### Git LFS
 
-The large model and data files in this repo are stored using [Git Large File Storage (LFS)](https://git-lfs.github.com/). These files will be required for running the training/validation scripts and example pipelines for the Morpheus pre-trained models.
+The large model and data files in this repo are stored using [Git Large File Storage (LFS)](https://git-lfs.github.com/). Only those files which are strictly needed to run Morpheus are downloaded by default when the repository is cloned.
 
-If `Git LFS` is not installed before cloning the repository, the large files will not be pulled. If this is the case, follow the instructions for installing `Git LFS` from [here](https://git-lfs.github.com/), and then run the following command:
+The `scripts/fetch_data.py` script can be used to fetch the Morpheus pre-trained models, and other files required for running the training/validation scripts and example pipelines.
+
+Usage of the script is as follows:
 ```bash
-git lfs install
+scripts/fetch_data.py fetch <dataset> [<dataset>...]
 ```
 
-#### Clone the Repository
+At time of writing the defined datasets are:
+* all - Metaset includes all others
+* examples - Data needed by scripts in the `examples` subdir
+* models - Morpheus models (largest dataset)
+* tests - Data used by unittests
+* validation - Subset of the models dataset needed by some unittests
 
+To download just the examples and models:
 ```bash
-MORPHEUS_ROOT=$(pwd)/morpheus
-git clone https://github.com/NVIDIA/Morpheus.git $MORPHEUS_ROOT
-cd $MORPHEUS_ROOT
+scripts/fetch_data.py fetch examples models
 ```
 
-**Note:** If the repository was cloned before `Git LFS` was installed, you can ensure you have downloaded the LFS files with the command:
+To download the data needed for unittests:
+```bash
+scripts/fetch_data.py fetch tests validation
+```
 
+If `Git LFS` is not installed the before cloning the repository, the `scripts/fetch_data.py` script will fail. If this is the case follow the instructions for installing `Git LFS` from [here](https://git-lfs.github.com/), and then run the following command:
 ```bash
-git lfs pull
+git lfs install
 ```
 
 ### Build Morpheus Container
@@ -76,6 +96,22 @@ DOCKER_IMAGE_TAG="v22.06.00a-runtime" ./docker/run_container_release.sh
 
 It's possible to build from source outside of a container. However, due to the large number of dependencies, this can be complex and is only necessary for developers. Instructions for developers and contributors can be found in [CONTRIBUTING.md](./CONTRIBUTING.md).
 
+## Launching Triton Server
+
+Many of the validation tests and example workflows require a Triton server to function.
+Use the following command to launch a Docker container for Triton loading all of the included pre-trained models:
+
+```bash
+docker run --rm -ti --gpus=all -p8000:8000 -p8001:8001 -p8002:8002 \
+	-v $PWD/models:/models \
+	nvcr.io/nvidia/tritonserver:22.06-py3 \
+	tritonserver --model-repository=/models/triton-model-repo \
+		--exit-on-error=false \
+		--log-info=true \
+		--strict-readiness=false
+```
+This will launch Triton using the default network ports (8000 for HTTP, 8001 for GRPC, and 8002 for metrics).
+
 ## Running Morpheus
 
 To run Morpheus, users will need to choose from the Morpheus Command Line Interface (CLI) or Python interface. Which interface to use depends on the user's needs, amount of customization, and operating environment. More information on each interface can be found below.

scripts/validation/val-globals.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# SPDX-FileCopyrightText: Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
@@ -26,7 +26,7 @@ export e="\033[0;90m"
 export y="\033[0;33m"
 export x="\033[0m"
 
-export TRITON_IMAGE=${TRITON_IMAGE:-"nvcr.io/nvidia/tritonserver:22.02-py3"}
+export TRITON_IMAGE=${TRITON_IMAGE:-"nvcr.io/nvidia/tritonserver:22.06-py3"}
 
 # TRITON_GRPC_PORT is only used when TRITON_URL is undefined
 export TRITON_GRPC_PORT=${TRITON_GRPC_PORT:-"8001"}

scripts/validation/val-utils.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# SPDX-FileCopyrightText: Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
@@ -68,7 +68,7 @@ function wait_for_triton {
 
 function ensure_triton_running {
 
-   TRITON_IMAGE=${TRITON_IMAGE:-"nvcr.io/nvidia/tritonserver:22.02-py3"}
+   TRITON_IMAGE=${TRITON_IMAGE:-"nvcr.io/nvidia/tritonserver:22.06-py3"}
 
    IS_RUNNING=$(is_triton_running)