update docs

Author: jathu

backends/apple/coreml/setup.md

@@ -6,16 +6,8 @@ This is a tutorial for setting up the Core ML backend.
 
 1. Follow the instructions described in [Setting Up ExecuTorch](/docs/source/getting-started-setup.md) to set up ExecuTorch environment.
 
-2. Run `install_requirements.sh` to install dependencies required by the **Core ML** backend.
 
-```
-cd executorch
-
-./backends/apple/coreml/scripts/install_requirements.sh
-
-```
-
-3. Run the example script to validate that the **Core ML** backend is set up correctly.
+2. Run the example script to validate that the **Core ML** backend is set up correctly.
 
 ```
 cd executorch
@@ -26,7 +18,7 @@ python3 -m examples.apple.coreml.scripts.export --model_name add
 
 ```
 
-4. You can now integrate the **Core ML** backend in code.
+3. You can now integrate the **Core ML** backend in code.
 
 ```python
 # Delegate to Core ML backend

docs/source/backends-coreml.md

@@ -28,12 +28,6 @@ Before starting, make sure you install the Xcode Command Line Tools:
 xcode-select --install
 ```
 
-Finally you must install the CoreML backend by running the following script:
-```bash
-sh ./backends/apple/coreml/scripts/install_requirements.sh
-```
-
-
 ----
 
 ## Using the CoreML Backend

docs/source/using-executorch-ios.md

@@ -103,19 +103,18 @@ git clone https://github.com/pytorch/executorch.git --depth 1 --recurse-submodul
 3. Set up [Python](https://www.python.org/downloads/macos/) 3.10+ and activate a virtual environment:
 
 ```bash
-python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip
+python3 -m venv .venv && source .venv/bin/activate && ./install_requirements.sh
 ```
 
-4. Install the required dependencies, including those needed for the backends like [Core ML](backends-coreml.md) or [MPS](backends-mps.md), if you plan to build them as well:
+4. Install the required dependencies, including those needed for the backends like [Core ML](backends-coreml.md) or [MPS](backends-mps.md). Choose one:
 
 ```bash
-./install_executorch.sh --pybind coreml mps xnnpack
+# ExecuTorch with xnnpack and CoreML backend
+./install_executorch.sh --pybind xnnpack
 
-# Optional dependencies for Core ML backend.
-./backends/apple/coreml/scripts/install_requirements.sh
-
-# And MPS backend.
+# Optional: ExecuTorch with xnnpack, CoreML, and MPS backend
 ./backends/apple/mps/install_requirements.sh
+./install_executorch.sh --pybind xnnpack mps
 ```
 
 5. Install [CMake](https://cmake.org):

examples/apple/coreml/README.md

@@ -18,16 +18,8 @@ We will walk through an example model to generate a Core ML delegated binary fil
 1. Following the setup guide in [Setting Up ExecuTorch](https://pytorch.org/executorch/stable/getting-started-setup)
 you should be able to get the basic development environment for ExecuTorch working.
 
-2. Run `install_requirements.sh` to install dependencies required by the **Core ML** backend.
 
-```bash
-cd executorch
-
-./backends/apple/coreml/scripts/install_requirements.sh
-
-```
-
-3. Run the export script to generate a Core ML delegated binary file.
+2. Run the export script to generate a Core ML delegated binary file.
 
 ```bash
 cd executorch
@@ -39,11 +31,14 @@ python3 -m examples.portable.scripts.export -h
 python3 -m examples.apple.coreml.scripts.export --model_name add
 ```
 
-4. Run the binary file using the `coreml_executor_runner`.
+3. Run the binary file using the `coreml_executor_runner`.
 
 ```bash
 cd executorch
 
+# Install requirements needed to run the example runner
+./backends/apple/coreml/scripts/install_requirements.sh
+
 # Builds the Core ML executor runner. Generates ./coreml_executor_runner if successful.
 ./examples/apple/coreml/scripts/build_executor_runner.sh