Merge pull request #210886 from srasool/main

Update docs for ASE Pro 2 support

Author: prmerger-automator[bot]

articles/cognitive-services/Computer-vision/spatial-analysis-container.md

@@ -26,7 +26,7 @@ The Spatial Analysis container enables you to analyze real-time streaming video
 
 ### Spatial Analysis container requirements
 
-To run the Spatial Analysis container, you need a compute device with an NVIDIA CUDA Compute Capable GPU 6.0 or higher (for example, [NVIDIA Tesla T4](https://www.nvidia.com/en-us/data-center/tesla-t4/), 1080Ti, or 2080Ti). We recommend that you use [Azure Stack Edge](https://azure.microsoft.com/products/azure-stack/edge/) with GPU acceleration, however the container runs on any other desktop machine that meets the minimum requirements. We'll refer to this device as the host computer.
+To run the Spatial Analysis container, you need a compute device with an NVIDIA CUDA Compute Capable GPU 6.0 or higher (for example, [NVIDIA Tesla T4](https://www.nvidia.com/en-us/data-center/tesla-t4/), A2, 1080Ti, or 2080Ti). We recommend that you use [Azure Stack Edge](https://azure.microsoft.com/products/azure-stack/edge/) with GPU acceleration, however the container runs on any other desktop machine that meets the minimum requirements. We'll refer to this device as the host computer.
 
 #### [Azure Stack Edge device](#tab/azure-stack-edge)
 
@@ -39,15 +39,15 @@ Azure Stack Edge is a Hardware-as-a-Service solution and an AI-enabled edge comp
 * 4 GB of system RAM
 * 4 GB of GPU RAM
 * 8 core CPU
-* One NVIDIA CUDA Compute Capable GPU 6.0 or higher (for example, [NVIDIA Tesla T4](https://www.nvidia.com/en-us/data-center/tesla-t4/), 1080Ti, or 2080Ti)
+* One NVIDIA CUDA Compute Capable GPU 6.0 or higher (for example, [NVIDIA Tesla T4](https://www.nvidia.com/en-us/data-center/tesla-t4/), A2, 1080Ti, or 2080Ti)
 * 20 GB of HDD space
 
 #### Recommended hardware
 
 * 32 GB of system RAM
 * 16 GB of GPU RAM
 * 8 core CPU
-* Two NVIDIA CUDA Compute Capable GPUs 6.0 or higher (for example, [NVIDIA Tesla T4](https://www.nvidia.com/en-us/data-center/tesla-t4/), 1080Ti, or 2080Ti)
+* Two NVIDIA CUDA Compute Capable GPUs 6.0 or higher (for example, [NVIDIA Tesla T4](https://www.nvidia.com/en-us/data-center/tesla-t4/), A2, 1080Ti, or 2080Ti)
 * 50 GB of SSD space
 
 In this article, you'll download and install the following software packages. The host computer must be able to run the following (see below for instructions):
@@ -503,8 +503,6 @@ The following table shows the various Environment Variables used by the IoT Edge
 | BILLING | your Endpoint URI| Collect this value from Azure portal from your Computer Vision resource. You can find it in the **Key and endpoint** section for your resource.|
 | EULA | accept | This value needs to be set to *accept* for the container to run |
 | DISPLAY | :1 | This value needs to be same as the output of `echo $DISPLAY` on the host computer. Azure Stack Edge devices do not have a display. This setting is not applicable|
-| ARCHON_GRAPH_READY_TIMEOUT | 600 | Add this environment variable if your GPU is **not** T4 or  NVIDIA 2080 Ti|
-| ORT_TENSORRT_ENGINE_CACHE_ENABLE | 0 | Add this environment variable if your GPU is **not** T4 or  NVIDIA 2080 Ti|
 | KEY_ENV | ASE Encryption key | Add this environment variable if Video_URL is an obfuscated string |
 | IV_ENV | Initialization vector | Add this environment variable if Video_URL is an obfuscated string|