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2 changes: 1 addition & 1 deletion .ci/docker/build.sh
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ case "${IMAGE_NAME}" in
LINTRUNNER=""
CLANG_VERSION=12
# From https://developer.android.com/ndk/downloads
ANDROID_NDK_VERSION=r26c
ANDROID_NDK_VERSION=r27b
;;
*)
echo "Invalid image name ${IMAGE_NAME}"
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2 changes: 1 addition & 1 deletion .github/workflows/android.yml
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Expand Up @@ -53,7 +53,7 @@ jobs:
# NB: Use metal install for KVM support to run the emulator faster
runs-on: linux.24xl.spr-metal
env:
ANDROID_NDK_VERSION: r26c
ANDROID_NDK_VERSION: r27b
API_LEVEL: 34
steps:
- name: Setup SSH (Click me for login details)
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2 changes: 1 addition & 1 deletion backends/vulkan/README.md
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Expand Up @@ -150,7 +150,7 @@ when building with CMake.

First, make sure that you have the Android NDK installed; any NDK version past
NDK r19c should work. Note that the examples in this doc have been validated with
NDK r25. The Android SDK should also be installed so that you have access to `adb`.
NDK r27b. The Android SDK should also be installed so that you have access to `adb`.

The instructions in this page assumes that the following environment variables
are set.
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Expand Up @@ -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 r26c.
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 r27b.

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 [r26](https://developer.android.com/ndk/downloads)
* Download and unzip Android SDK [r27b](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)).

Expand Down Expand Up @@ -40,7 +40,7 @@ Install dependencies
## Setup QNN
```
# Set these variables correctly for your environment
export ANDROID_NDK_ROOT=$HOME/android-ndk-r26 # Download android SDK and unzip to home directory
export ANDROID_NDK_ROOT=$HOME/android-ndk-r27b # 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
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2 changes: 1 addition & 1 deletion examples/models/llama2/README.md
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Expand Up @@ -356,7 +356,7 @@ To build for CoreML backend and validate on Mac, replace `-DEXECUTORCH_BUILD_XNN

**1. Build llama runner binary for Android**

*Pre-requisite*: Android NDK (tested with r26c) which can be downloaded from [here](https://developer.android.com/ndk/downloads). Note that the mac binary can be unpackaged and you can locate NDK folder from it.
*Pre-requisite*: Android NDK (tested with r27b) which can be downloaded from [here](https://developer.android.com/ndk/downloads). Note that the mac binary can be unpackaged and you can locate NDK folder from it.

**1.1 Set Android NDK**
```
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