mirror of
https://github.com/azaion/gps-denied-onboard.git
synced 2026-06-21 20:41:13 +00:00
Oleksandr Bezdieniezhnykh
6586208f83
Operator-reported: `nvcr.io/nvidia/l4t-base:r36.4.0` fails to pull.
Investigation against the live registries confirmed:
* `nvcr.io/nvidia/l4t-base` — deprecated in JetPack 6, no r36 tags
(forum thread "L4T Base docker image for Jetpack 6.2 (r36.4.3)",
GitHub dusty-nv/jetson-containers#883).
* `nvcr.io/nvidia/l4t-pytorch` — no r36 tags at all. Newest is
r35.2.1-pth2.0-py3 (too old for our torch>=2.2 floor).
* `nvcr.io/nvidia/l4t-jetpack:r36.4.0` — exists but ships no PyTorch.
* `dustynv/l4t-pytorch:r36.4.0` (Docker Hub) — exists, ~6.3 GB ARM64,
PyTorch + torchvision + opencv pre-baked, maintained by dusty-nv
(NVIDIA's Jetson containers maintainer).
Switched Dockerfile.jetson base to `dustynv/l4t-pytorch:r36.4.0`.
Forward-compatible with the host's R36.5 BSP (NVIDIA containers
tolerate one minor BSP ahead on the host side).
Setup doc fixes:
* smoke-test command now uses `l4t-jetpack:r36.4.0` (the official
replacement for the deprecated `l4t-base`)
* keygen step explicitly states it produces BOTH halves (private +
.pub) in one go
* ssh-copy-id + ssh config show how to specify a custom port
* troubleshooting table gets a new row for the `l4t-base not found`
case so the next dev hits the answer in 30 seconds
Co-authored-by: Cursor <cursoragent@cursor.com>
96 lines
4.5 KiB
Docker
96 lines
4.5 KiB
Docker
# Tier-2 e2e-runner image — Jetson Orin Nano (JetPack 6.x, L4T R36.x).
|
|
#
|
|
# AZ-615: companion image to `tests/e2e/Dockerfile` (Colima/Tier-1 smoke
|
|
# harness) that runs the full Reality Gate — including C3 matcher + C7
|
|
# inference — against a CUDA-capable GPU.
|
|
#
|
|
# Hardware contract (operator-confirmed, 2026-05-17):
|
|
# * Jetson Orin Nano, JetPack 6.2.2+b24, L4T R36.5.0
|
|
# * nvidia-container-toolkit ≥ 1.16
|
|
# * `docker run --runtime=nvidia ... nvidia-smi` returns the GPU
|
|
#
|
|
# Image layout mirrors the Colima Dockerfile (so AC-4 AST scan + bind
|
|
# mounts work the same way):
|
|
# /opt/pyproject.toml
|
|
# /opt/src/gps_denied_onboard/... (SUT package, editable install)
|
|
# /opt/tests/... (bind-mounted from host)
|
|
# /opt/_docs/00_problem/input_data/ (bind-mounted from host)
|
|
#
|
|
# Build context is the repo root (see `docker-compose.test.jetson.yml`
|
|
# → `services.e2e-runner.build.context`).
|
|
#
|
|
# BUILD HOST: this image MUST be built ON the Jetson — cross-building
|
|
# from x86 macOS produces images that miss Tegra-specific shared libs
|
|
# the nvidia-container-runtime later mounts at run time.
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Base — dustynv/l4t-pytorch ships JetPack runtime + PyTorch wheel for `.cuda()`
|
|
#
|
|
# Tag selection rationale (verified 2026-05-17 against the live registries):
|
|
#
|
|
# - `nvcr.io/nvidia/l4t-base` was deprecated in JetPack 6 (forums:
|
|
# "L4T Base docker image for Jetpack 6.2 (r36.4.3)" / Issue #883 in
|
|
# dusty-nv/jetson-containers). The image no longer publishes r36 tags.
|
|
# - `nvcr.io/nvidia/l4t-pytorch` has NO r36 tags published. The newest
|
|
# official l4t-pytorch tag is r35.2.1-pth2.0-py3 — too old for our
|
|
# torch >= 2.2 floor in pyproject.toml `[inference]`.
|
|
# - `nvcr.io/nvidia/l4t-jetpack:r36.4.0` exists (CUDA + cuDNN + TensorRT
|
|
# bundled) but ships NO PyTorch — we'd have to install the Jetson
|
|
# PyTorch wheel from developer.download.nvidia.com manually.
|
|
# - `dustynv/l4t-pytorch:r36.4.0` (Docker Hub) is the de-facto Jetson
|
|
# PyTorch image: maintained by dusty-nv (NVIDIA's Jetson containers
|
|
# maintainer), bakes torch / torchvision / opencv / ONNX runtime for
|
|
# JetPack 6, ARM64, ~6.3 GB. Forward-compatible with the host's
|
|
# slightly newer R36.5 BSP (NVIDIA containers tolerate one minor BSP
|
|
# ahead on the host side).
|
|
#
|
|
# Verify availability before build:
|
|
# docker pull dustynv/l4t-pytorch:r36.4.0
|
|
FROM dustynv/l4t-pytorch:r36.4.0 AS runtime
|
|
|
|
ARG DEBIAN_FRONTEND=noninteractive
|
|
# System deps mirror tests/e2e/Dockerfile + the Jetson runtime stack:
|
|
# * build-essential / libpq-dev / libspatialindex-dev — same as Colima
|
|
# * python3-pip / python3-venv — l4t-pytorch ships python but not always venv
|
|
# * libgl1 + libglib2.0-0 — OpenCV runtime libs (same reason as Colima)
|
|
# * libpq5 + libspatialindex-c6 — runtime side of psycopg + rtree
|
|
# Note: CUDA / cuDNN / TensorRT come pre-baked in the base image — do NOT
|
|
# attempt to apt-install them (would conflict with the Tegra-specific libs
|
|
# the runtime mounts).
|
|
RUN apt-get update && apt-get install -y --no-install-recommends \
|
|
ca-certificates \
|
|
build-essential \
|
|
libpq-dev \
|
|
libspatialindex-dev \
|
|
libpq5 \
|
|
libspatialindex-c6 \
|
|
libgl1 \
|
|
libglib2.0-0 \
|
|
python3-pip \
|
|
python3-venv \
|
|
&& rm -rf /var/lib/apt/lists/*
|
|
|
|
WORKDIR /opt
|
|
|
|
# Editable SUT install. Skipping the `[inference]` extra because PyTorch +
|
|
# torchvision are already provided by the l4t-pytorch base image with
|
|
# Tegra-specific CUDA builds; reinstalling them from PyPI would clobber
|
|
# the Tegra wheels with x86-compatible ones that lack the cuDNN / cuBLAS
|
|
# linkage required by Orin.
|
|
COPY pyproject.toml README.md ./
|
|
COPY src ./src
|
|
|
|
# `--break-system-packages` is needed because the l4t-pytorch base image
|
|
# uses an externally-managed Python environment (PEP 668). The alternative
|
|
# would be to layer a venv on top of the pre-installed torch, but that
|
|
# would shadow the Tegra-tuned torch wheel and break `.cuda()`. The image
|
|
# IS the environment; embracing system-pip is the path of least drift.
|
|
RUN pip3 install --no-cache-dir --break-system-packages -e ".[dev]"
|
|
|
|
# ENTRYPOINT mirrors the Colima Dockerfile — pytest discovers both
|
|
# `tests/e2e/replay/` (heavy tier2 ACs run with GPS_DENIED_TIER=2) and
|
|
# any future `tests/e2e/scenarios/` additions. Rootdir resolves to /opt
|
|
# via the COPY'd pyproject.toml so `from tests.e2e.replay._helpers import ...`
|
|
# works inside the test files.
|
|
ENTRYPOINT ["pytest", "-q", "/opt/tests/e2e/"]
|