Update install script and building from source docs

README.md

@@ -19,7 +19,7 @@ It supports a wide range of models including LLMs (Large Language Models), CV (C
 Platform Support:
 - Operating Systems:
   - iOS
-  - Mac
+  - MacOS (ARM64)
   - Android
   - Linux
   - Microcontrollers

docs/source/backends-xnnpack.md

@@ -14,7 +14,7 @@ The XNNPACK delegate is the ExecuTorch solution for CPU execution on mobile CPUs
 - ARM64 on Android, iOS, macOS, Linux, and Windows.
 - ARMv7 (with NEON) on Android.
 - ARMv6 (with VFPv2) on Linux.
-- x86 and x86-64 (up to AVX512) on Windows, Linux, macOS, Android, and iOS simulator.
+- x86 and x86-64 (up to AVX512) on Windows, Linux, Android.
 
 ## Development Requirements
 

docs/source/getting-started.md

@@ -10,8 +10,9 @@ The following are required to install the ExecuTorch host libraries, needed to e
 
 - Python 3.10 - 3.12
 - g++ version 7 or higher, clang++ version 5 or higher, or another C++17-compatible toolchain.
-- Linux or MacOS operating system (Arm or x86).
-  - Windows is supported via WSL.
+- Linux (x86_64 or ARM64) or macOS (ARM64).
+    - Intel-based macOS systems require building PyTorch from source (see [Building From Source](using-executorch-building-from-source.md) for instructions).
+    - Windows is supported via WSL.
 
 ## Installation
 To use ExecuTorch, you will need to install both the Python package and the appropriate platform-specific runtime libraries. Pip is the recommended way to install the ExecuTorch python package.

docs/source/using-executorch-building-from-source.md

@@ -16,7 +16,7 @@ Linux (x86_64)
 - Ubuntu 20.04.6 LTS+
 - RHEL 8+
 
-macOS (x86_64/M1/M2)
+macOS (x86_64/ARM64)
 - Big Sur (11.0)+
 
 Windows (x86_64)
@@ -56,13 +56,27 @@ Or alternatively, [install conda on your machine](https://conda.io/projects/cond
    conda create -yn executorch python=3.10.0 && conda activate executorch
    ```
 
-## Install ExecuTorch pip package from Source
+## Install ExecuTorch pip package from source
    ```bash
    # 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.
+   # Intel-based macOS systems require building PyTorch from source (see below)
    ./install_executorch.sh
    ```
+
+   See the [PyTorch instructions](https://github.com/pytorch/pytorch#installation) on how to build PyTorch from source.  
+
+   Use the [`--use-pt-pinned-commit` flag](../../install_executorch.py) to install ExecuTorch with an existing PyTorch build:
+
+   ```bash
+   ./install_executorch.sh --use-pt-pinned-commit
+   ```
+
+   For Intel-based macOS systems, use the [`--use-pt-pinned-commit --minimal` flags](../../install_executorch.py):
+   ```bash
+   ./install_executorch.sh --use-pt-pinned-commit --minimal
+   ```
 
    Not all backends are built into the pip wheel by default. You can link these missing/experimental backends by turning on the corresponding cmake flag. For example, to include the MPS backend:
 

docs/source/using-executorch-ios.md

@@ -4,7 +4,7 @@ ExecuTorch supports both iOS and macOS via Objective-C, Swift, and C++. ExecuTor
 
 ## Integration
 
-The ExecuTorch Runtime for iOS and macOS is distributed as a collection of prebuilt [.xcframework](https://developer.apple.com/documentation/xcode/creating-a-multi-platform-binary-framework-bundle) binary targets. These targets are compatible with both iOS and macOS devices and simulators and are available in both release and debug modes:
+The ExecuTorch Runtime for iOS and macOS (ARM64) is distributed as a collection of prebuilt [.xcframework](https://developer.apple.com/documentation/xcode/creating-a-multi-platform-binary-framework-bundle) binary targets. These targets are compatible with both iOS and macOS devices and simulators and are available in both release and debug modes:
 
 * `executorch` - Main Runtime components
 * `backend_coreml` - Core ML backend

install_requirements.py

@@ -75,6 +75,15 @@ def python_is_compatible():
 
 
 def install_requirements(use_pytorch_nightly):
+    # Skip pip install on Intel macOS if using nightly.
+    if use_pytorch_nightly and is_intel_mac_os():
+        print(
+            "ERROR: Prebuilt PyTorch wheels are no longer available for Intel-based macOS.\n"
+            "Please build from source by following https://docs.pytorch.org/executorch/main/using-executorch-building-from-source.html",
+            file=sys.stderr,
+        )
+        sys.exit(1)
+
     # pip packages needed by exir.
     TORCH_PACKAGE = [
         # Setting use_pytorch_nightly to false to test the pinned PyTorch commit. Note
@@ -163,6 +172,17 @@ def install_optional_example_requirements(use_pytorch_nightly):
     )
 
 
+# Prebuilt binaries for Intel-based macOS are no longer available on PyPI; users must compile from source.
+# PyTorch stopped building macOS x86_64 binaries since version 2.3.0 (January 2024).
+def is_intel_mac_os():
+    # Returns True if running on Intel macOS.
+    return platform.system().lower() == "darwin" and platform.machine().lower() in (
+        "x86",
+        "x86_64",
+        "i386",
+    )
+
+
 def main(args):
     parser = argparse.ArgumentParser()
     parser.add_argument(