[project]
name = "deit-tiny-int8-xnnpack-executorch-runtime"
version = "0.1.0"
description = "Runtime dependencies for example.py (DeiT-Tiny INT8, ExecuTorch + XNNPACK)"
requires-python = ">=3.13,<3.14"
dependencies = [
    "executorch==1.1.0",
    "torch==2.10.0",
    "torchvision==0.25.0",
    "pillow==12.3.0",
]

[tool.uv]
package = false
# The example only runs on Arm-based Edge Linux; it was measured on a Raspberry
# Pi 5 (aarch64, Debian 13 trixie). Restricting the resolution environment keeps
# the lock to the wheels that device actually installs.
environments = ["sys_platform == 'linux' and platform_machine == 'aarch64'"]
# coremltools targets Apple Core ML, which this XNNPACK-on-Arm-Linux example
# never uses. Nothing in example.py imports it.
exclude-dependencies = [
    { package = { name = "executorch", version = "1.1.0" }, dependencies = ["coremltools"] },
]

[tool.ai-portal.deployment]
schema-version = "1"
runtime = "executorch"
required-capabilities = ["XnnpackBackend"]

[tool.ai-portal.deployment.ubuntu]
packages = []

[tool.ai-portal.deployment.raspbian]
packages = []

[tool.ai-portal.deployment.files]
expected = ["predictions.json"]