[project]
name = "esrgan-int8-xnnpack-executorch-graviton-g4-runtime"
version = "0.1.0"
description = "Runtime dependencies for example.py (ESRGAN x4 INT8, ExecuTorch + XNNPACK)"
requires-python = ">=3.13,<3.14"
dependencies = [
    "executorch==1.1.0",
    "torch==2.10.0",
    "torchvision==0.25.0",
    "numpy==2.5.2",
    "pillow==12.3.0",
]

[tool.uv]
package = false
# The example runs on Arm-based Linux; it was measured on an AWS Graviton G4
# (aarch64, Neoverse-V2, Ubuntu 24.04, glibc 2.39). 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 = ["sample_output.png", "super_resolution.json"]