Specify NDK version 26 (#5855)

Summary: Pull Request resolved: #5855

Reviewed By: larryliu0820

Differential Revision: D63861692

Pulled By: kirklandsign

fbshipit-source-id: 94ba5ccab0f619bc905788ba60affd67a136a489

Author: kirklandsign

backends/mediatek/scripts/README.md

@@ -16,7 +16,7 @@ Before you begin, ensure you have the following prerequisites installed and conf
 
 ### 2. Android NDK
 
-- **Download Android NDK**: Acquire the Android NDK from the [Android developer site](https://developer.android.com/ndk/downloads).
+- **Download Android NDK**: Acquire the Android NDK version 26.3.11579264 from the [Android developer site](https://developer.android.com/ndk/downloads).
 - **Set NDK Path**: Ensure that the `$ANDROID_NDK` environment variable is set to the path where the NDK is located.
    ```bash
    export ANDROID_NDK=<path_to_android_ndk>

examples/demo-apps/android/LlamaDemo/README.md

@@ -34,6 +34,12 @@ First it’s important to note that currently ExecuTorch provides support across
 | QNN (Qualcomm AI Accelerators)  | [link](https://github.com/pytorch/executorch/blob/main/examples/demo-apps/android/LlamaDemo/docs/delegates/qualcomm_README.md) |
 | MediaTek (MediaTek AI Accelerators)  | [link](https://github.com/pytorch/executorch/blob/main/examples/demo-apps/android/LlamaDemo/docs/delegates/mediatek_README.md)  |
 
+**WARNING** NDK r27 will cause issues like:
+  ```
+  java.lang.UnsatisfiedLinkError: dlopen failed: cannot locate symbol "_ZTVNSt6__ndk114basic_ifstreamIcNS_11char_traitsIcEEEE" referenced by "/data/app/~~F5IwquaXUZPdLpSEYA-JGA==/com.example.executorchllamademo-FSyx80gEhsQCsxz7hvS2Ew==/lib/arm64/libexecutorch.so"...
+  ```
+  Please use NDK version 26.3.11579264.
+
 ## How to Use the App
 
 This section will provide the main steps to use the app, along with a code snippet of the ExecuTorch API.

examples/demo-apps/android/LlamaDemo/docs/delegates/qualcomm_README.md

@@ -6,13 +6,13 @@ More specifically, it covers:
 2. Building and linking libraries that are required to inference on-device for Android platform using Qualcomm AI accelerators.
 3. Building the Android demo app itself.
 
-Verified on Linux CentOS, QNN SDK [v2.26](https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.26.0.240828.zip), python 3.10, Android SDK r27 and r26b.
+Verified on Linux CentOS, QNN SDK [v2.26](https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.26.0.240828.zip), python 3.10, Android SDK r26c.
 
 Phone verified: OnePlus 12, Samsung 24+, Samsung 23
 
 ## Prerequisites
 * Download and unzip QNN SDK [v2.26](https://softwarecenter.qualcomm.com/api/download/software/qualcomm_neural_processing_sdk/v2.26.0.240828.zip)
-* Download and unzip Android SDK [r27](https://developer.android.com/ndk/downloads)
+* Download and unzip Android SDK [r26](https://developer.android.com/ndk/downloads)
 * Android phone with Snapdragon8 Gen3 (SM8650) or Gen2 (SM8550). Gen 1 and lower SoC might be supported but not fully validated.
 * Desired Llama model weights in .PTH format. You can download them on HuggingFace ([Example](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)).
 
@@ -40,7 +40,7 @@ Install dependencies
 ## Setup QNN
 ```
 # Set these variables correctly for your environment
-export ANDROID_NDK_ROOT=$HOME/android-ndk-r27 # Download android SDK and unzip to home directory
+export ANDROID_NDK_ROOT=$HOME/android-ndk-r26 # Download android SDK and unzip to home directory
 export QNN_SDK_ROOT=$HOME/Your-SDK-Root #Folder contains lib
 export EXECUTORCH_ROOT=$HOME/repos/executorch
 export LD_LIBRARY_PATH=$QNN_SDK_ROOT/lib/x86_64-linux-clang/:$LD_LIBRARY_PATH