test_ios.sh

#!/bin/bash
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.

# Usage:
#   ./test_ios.sh [output]
# Arguments:
#   output - The directory where the repository will be cloned and built.
#            Default is 'executorch'.

set -e

OUTPUT="${1:-executorch}"
EXIT_STATUS=0
APP_PATH="executorch-examples/mv3/apple/ExecuTorchDemo/ExecuTorchDemo"
MODEL_NAME="mv3"
SIMULATOR_NAME="executorch"

finish() {
  EXIT_STATUS=$?
  if xcrun simctl list | grep -q "$SIMULATOR_NAME"; then
    say "Deleting Simulator"
    xcrun simctl delete "$SIMULATOR_NAME"
  fi
  if [ -d "$OUTPUT" ]; then
    popd > /dev/null
    say "Deleting Output Directory"
    rm -rf "$OUTPUT"
  fi
  if [ $EXIT_STATUS -eq 0 ]; then
    say "SUCCEEDED"
  else
    say "FAILED"
  fi
  exit $EXIT_STATUS
}

trap finish EXIT

say() {
  echo -e "\033[1m\n\t** $1 **\n\033[0m"
}

say "Activating a Virtual Environment"

python3 -m venv .venv && source .venv/bin/activate && pip install --upgrade pip

say "Installing Requirements"

./install_executorch.sh

say "Cloning the Demo App"

git clone --depth 1 https://github.com/meta-pytorch/executorch-examples.git

say "Installing CoreML Backend Requirements"

./backends/apple/coreml/scripts/install_requirements.sh

say "Exporting Models"

python3 -m examples.portable.scripts.export --model_name="$MODEL_NAME"
python3 -m examples.apple.coreml.scripts.export --model_name="$MODEL_NAME"
python3 -m examples.xnnpack.aot_compiler --model_name="$MODEL_NAME" --delegate

# No generic examples/ entry point takes a model name and lowers it to MLX, so do
# it here. Assert MLX claimed the graph before writing: the partitioner only warns
# when it delegates nothing. This needs the MLX backend built, which the installer
# does only on Apple Silicon with the Metal compiler present.
python3 - "$MODEL_NAME" <<'PY'
import sys

import torch
from executorch.backends.mlx import MLXPartitioner
from executorch.examples.models import MODEL_NAME_TO_MODEL
from executorch.examples.models.model_factory import EagerModelFactory
from executorch.exir import EdgeCompileConfig, to_edge_transform_and_lower

model_name = sys.argv[1]
model, example_inputs, _, _ = EagerModelFactory.create_model(
    *MODEL_NAME_TO_MODEL[model_name]
)
program = to_edge_transform_and_lower(
    torch.export.export(model.eval(), example_inputs),
    partitioner=[MLXPartitioner()],
    compile_config=EdgeCompileConfig(_skip_dim_order=True),
).to_executorch()

segments = sum(
    delegate.id == "MLXBackend"
    for plan in program.executorch_program.execution_plan
    for delegate in plan.delegates
)
if segments == 0:
    raise SystemExit(f"error: {model_name} produced no MLX delegate")

path = f"{model_name}_mlx.pte"
with open(path, "wb") as file:
    program.write_to_file(file)
print(f"{path}: {segments} MLX delegate segment(s)")
PY

mkdir -p "$APP_PATH/Resources/Models/MobileNet/"
mv $MODEL_NAME*.pte "$APP_PATH/Resources/Models/MobileNet/"

say "Downloading Labels"

curl https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt \
  -o "$APP_PATH/Resources/Models/MobileNet/imagenet_classes.txt"

say "Creating Simulator"

xcrun simctl create "$SIMULATOR_NAME" "iPhone 15"

say "Running Tests"

xcodebuild test \
  -project "$APP_PATH.xcodeproj" \
  -scheme MobileNetClassifierTest \
  -destination name="$SIMULATOR_NAME"