rename top-level install_requirements.{py,sh,bat} to install_executorch

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like

.ci/scripts/utils.sh

@@ -17,17 +17,17 @@ retry () {
 }
 
 clean_executorch_install_folders() {
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 }
 
 install_executorch() {
  which pip
  # Install executorch, this assumes that Executorch is checked out in the
  # current directory.
  if [[ "${1:-}" == "use-pt-pinned-commit" ]]; then
- ./install_requirements.sh --pybind xnnpack --use-pt-pinned-commit
+ ./install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
  else
- ./install_requirements.sh --pybind xnnpack
+ ./install_executorch.sh --pybind xnnpack
  fi
  # Just print out the list of packages for debugging
  pip list

.github/workflows/apple.yml

@@ -9,7 +9,7 @@ on:
  paths:
  - .ci/scripts/setup-ios.sh
  - .github/workflows/apple.yml
- - install_requirements.sh
+ - install_executorch.sh
  - backends/apple/**
  - build/build_apple_frameworks.sh
  - build/build_apple_llm_demo.sh

.github/workflows/pull.yml

@@ -200,7 +200,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install Llava requirements
  bash examples/models/llama/install_requirements.sh
@@ -436,7 +436,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install phi-3-mini requirements
  bash examples/models/phi-3-mini/install_requirements.sh
@@ -463,7 +463,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -490,7 +490,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh
@@ -517,7 +517,7 @@ jobs:
  PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
 
  # install pybind
- bash install_requirements.sh --pybind xnnpack
+ bash install_executorch.sh --pybind xnnpack
 
  # install llama requirements
  bash examples/models/llama/install_requirements.sh

backends/apple/mps/setup.md

@@ -97,7 +97,7 @@ I 00:00:00.122615 executorch:mps_executor_runner.mm:501] Model verified successf
 ### [Optional] Run the generated model directly using pybind
 1. Make sure `pybind` MPS support was installed:
 ```bash
-./install_requirements.sh --pybind mps
+./install_executorch.sh --pybind mps
 ```
 2. Run the `mps_example` script to trace the model and run it directly from python:
 ```bash

backends/cadence/build_cadence_fusionG3.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=FCV_FG3GP
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/cadence/build_cadence_hifi4.sh

@@ -12,7 +12,7 @@ unset XTENSA_CORE
 export XTENSA_CORE=nxp_rt600_RI23_11_newlib
 git submodule sync
 git submodule update --init
-./install_requirements.sh
+./install_executorch.sh
 
 rm -rf cmake-out
 

backends/vulkan/docs/android_demo.md

@@ -81,7 +81,7 @@ First, build and install ExecuTorch libraries, then build the LLaMA runner
 binary using the Android NDK toolchain.
 
 ```shell
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-android-out && \
  cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \

backends/xnnpack/README.md

@@ -98,7 +98,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

build/test_ios.sh

@@ -63,7 +63,7 @@ say "Installing Requirements"
 
 pip install --upgrade cmake pip setuptools wheel zstd
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 export PATH="$(realpath third-party/flatbuffers/cmake-out):$PATH"
 ./build/install_flatc.sh
 

docs/README.md

@@ -65,7 +65,7 @@ To build the documentation locally:
 1. Run:
 
  ```bash
- bash install_requirements.sh
+ bash install_executorch.sh
  ```
 
 1. Go to the `docs/` directory.

docs/source/apple-runtime.md

@@ -109,7 +109,7 @@ python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
 4. Install the required dependencies, including those needed for the backends like [Core ML](build-run-coreml.md) or [MPS](build-run-mps.md), if you plan to build them as well:
 
 ```bash
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 
 # Optional dependencies for Core ML backend.
 ./backends/apple/coreml/scripts/install_requirements.sh

docs/source/build-run-xtensa.md

@@ -162,7 +162,7 @@ In order to run the CMake build, you need the path to the following:
 
 ```bash
 cd executorch
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 # prebuild and install executorch library
 cmake -DCMAKE_TOOLCHAIN_FILE=<path_to_executorch>/backends/cadence/cadence.cmake \

docs/source/getting-started-setup.md

@@ -92,23 +92,23 @@ Alternatively, if you would like to experiment with ExecuTorch quickly and easil
  # Install ExecuTorch pip package and its dependencies, as well as
  # development tools like CMake.
  # If developing on a Mac, make sure to install the Xcode Command Line Tools first.
- ./install_requirements.sh
+ ./install_executorch.sh
  ```
 
- Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_requirements.sh#L26-L29) to install with pybindings and dependencies for other backends.
+ Use the [`--pybind` flag](https://github.com/pytorch/executorch/blob/main/install_executorch.sh#L26-L29) to install with pybindings and dependencies for other backends.
  ```bash
- ./install_requirements.sh --pybind <coreml | mps | xnnpack>
+ ./install_executorch.sh --pybind <coreml | mps | xnnpack>
 
  # Example: pybindings with CoreML *only*
- ./install_requirements.sh --pybind coreml
+ ./install_executorch.sh --pybind coreml
 
  # Example: pybinds with CoreML *and* XNNPACK
- ./install_requirements.sh --pybind coreml xnnpack
+ ./install_executorch.sh --pybind coreml xnnpack
  ```
 
- By default, `./install_requirements.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
+ By default, `./install_executorch.sh` command installs pybindings for XNNPACK. To disable any pybindings altogether:
  ```bash
- ./install_requirements.sh --pybind off
+ ./install_executorch.sh --pybind off
  ```
 
 After setting up your environment, you are ready to convert your PyTorch programs
@@ -125,7 +125,7 @@ to ExecuTorch.
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```
@@ -208,7 +208,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
  ```bash
  # Clean and configure the CMake build system. Compiled programs will
  # appear in the executorch/cmake-out directory we create here.
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
  (mkdir cmake-out && cd cmake-out && cmake ..)
 
  # Build the executor_runner target
@@ -226,7 +226,7 @@ The ExecuTorch repo uses CMake to build its C++ code. Here, we'll configure it t
 >
 > ```bash
 > # From the root of the executorch repo:
-> ./install_requirements.sh --clean
+> ./install_executorch.sh --clean
 > git submodule sync
 > git submodule update --init
 > ```

docs/source/llm/getting-started.md

@@ -52,7 +52,7 @@ git submodule update --init
 # Create a conda environment and install requirements.
 conda create -yn executorch python=3.10.0
 conda activate executorch
-./install_requirements.sh
+./install_executorch.sh
 
 cd ../..
 ```
@@ -83,7 +83,7 @@ cd third-party/executorch
 git submodule update --init
 
 # Install requirements.
-PYTHON_EXECUTABLE=python ./install_requirements.sh
+PYTHON_EXECUTABLE=python ./install_executorch.sh
 
 cd ../..
 ```
@@ -396,7 +396,7 @@ At this point, the working directory should contain the following files:
 
 If all of these are present, you can now build and run:
 ```bash
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 cmake --build cmake-out -j10
 ./cmake-out/nanogpt_runner

docs/source/runtime-build-and-cross-compilation.md

@@ -45,7 +45,7 @@ cd executorch
 
 # Clean and configure the CMake build system. It's good practice to do this
 # whenever cloning or pulling the upstream repo.
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 (mkdir cmake-out && cd cmake-out && cmake ..)
 ```
 
@@ -122,7 +122,7 @@ Following are instruction on how to perform cross compilation for Android and iO
 Assuming Android NDK is available, run:
 ```bash
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out && cd cmake-android-out
 
 # point -DCMAKE_TOOLCHAIN_FILE to the location where ndk is installed

docs/source/tutorial-xnnpack-delegate-lowering.md

@@ -147,7 +147,7 @@ After exporting the XNNPACK Delegated model, we can now try running it with exam
 cd executorch
 
 # Get a clean cmake-out directory
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-out
 
 # Configure cmake

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

@@ -70,7 +70,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 
 # Run the following lines from the `executorch/` folder
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 
 # Build the core executorch library
@@ -114,7 +114,7 @@ export ANDROID_NDK=<path-to-android-ndk>
 export ANDROID_ABI=arm64-v8a
 export QNN_SDK_ROOT=<path-to-qnn-sdk>
 
-./install_requirements.sh --clean
+./install_executorch.sh --clean
 mkdir cmake-android-out
 cmake . -DCMAKE_INSTALL_PREFIX=cmake-android-out \
  -DCMAKE_TOOLCHAIN_FILE="${ANDROID_NDK}/build/cmake/android.toolchain.cmake" \

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

@@ -36,7 +36,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 ## Setup Environment Variables
 ### Download Buck2 and make executable

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

@@ -34,7 +34,7 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Setup QNN

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

@@ -36,12 +36,12 @@ git submodule update --init
 ```
 Install dependencies
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 
 

examples/demo-apps/apple_ios/ExecuTorchDemo/README.md

@@ -51,7 +51,7 @@ python3 -m venv .venv && source .venv/bin/activate
 
 pip install --upgrade cmake pip setuptools wheel
 
-./install_requirements.sh --pybind coreml mps xnnpack
+./install_executorch.sh --pybind coreml mps xnnpack
 ```
 
 ### 4. Backend Dependencies

examples/demo-apps/apple_ios/LLaMA/docs/delegates/mps_README.md

@@ -33,7 +33,7 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 
 ## Prepare Models

examples/demo-apps/apple_ios/LLaMA/docs/delegates/xnnpack_README.md

@@ -32,11 +32,11 @@ git submodule update --init
 Install dependencies
 
 ```
-./install_requirements.sh
+./install_executorch.sh
 ```
 Optional: Use the --pybind flag to install with pybindings.
 ```
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --pybind xnnpack
 ```
 ## Prepare Models
 In this demo app, we support text-only inference with up-to-date Llama models and image reasoning inference with LLaVA 1.5.

examples/demo-apps/react-native/rnllama/README.md

@@ -26,7 +26,7 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 3. Pull submodules: `git submodule sync && git submodule update --init`
 
-4. Install dependencies: `./install_requirements.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
+4. Install dependencies: `./install_executorch.sh --pybind xnnpack && ./examples/models/llama/install_requirements.sh`
 
 5. Follow the instructions in the [README](https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#option-a-download-and-export-llama32-1b3b-model) to export a model as `.pte`
 
@@ -40,4 +40,4 @@ A React Native mobile application for running LLaMA language models using ExecuT
 
 10. Select the model and tokenizer in the app to start chatting:
 
-[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)
+[![rnllama]](https://github.com/user-attachments/assets/b339f1ec-8b80-41f0-b3f6-ded6698ac926)

examples/devtools/build_example_runner.sh

@@ -37,7 +37,7 @@ done
 main() {
  cd "${EXECUTORCH_ROOT}"
 
- ./install_requirements.sh --clean
+ ./install_executorch.sh --clean
 
  if [[ "${BUILD_COREML}" == "ON" ]]; then
  cmake -DCMAKE_INSTALL_PREFIX=cmake-out \

examples/models/llama/README.md

@@ -148,7 +148,7 @@ Llama 3 8B performance was measured on the Samsung Galaxy S22, S24, and OnePlus
 ## Step 1: Setup
 > :warning: **double check your python environment**: make sure `conda activate <VENV>` is run before all the bash and python scripts.
 
-1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_requirements.sh --pybind xnnpack`
+1. Follow the [tutorial](https://pytorch.org/executorch/main/getting-started-setup) to set up ExecuTorch. For installation run `./install_executorch.sh --pybind xnnpack`
 2. Run `examples/models/llama/install_requirements.sh` to install a few dependencies.
 
 
@@ -440,8 +440,8 @@ This example tries to reuse the Python code, with minimal modifications to make
 ```
 git clean -xfd
 pip uninstall executorch
-./install_requirements.sh --clean
-./install_requirements.sh --pybind xnnpack
+./install_executorch.sh --clean
+./install_executorch.sh --pybind xnnpack
 ```
 - If you encounter `pthread` related issues during link time, add `pthread` in `target_link_libraries` in `CMakeLists.txt`
 - On Mac, if there is linking error in Step 4 with error message like