[CI] add diffusion ci

.buildkite/pipeline.yml

@@ -4,3 +4,8 @@ steps:
       - ".buildkite/scripts/simple_test.sh"
     agents:
       queue: "cpu_queue_premerge"
+  - label: "Diffusion Model Test"
+    commands:
+      - ".buildkite/scripts/diffusion_model_test.sh"
+    agents:
+      queue: "gpu_1_queue" # g6.4xlarge instance on AWS, has 1 L4 GPU

.buildkite/scripts/diffusion_model_test.sh

@@ -0,0 +1,57 @@
+#!/usr/bin/env bash
+
+set -euo pipefail
+
+if command -v nvidia-smi >/dev/null 2>&1; then
+  nvidia-smi
+fi
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+REPO_ROOT="$(cd -- "${SCRIPT_DIR}/../.." && pwd)"
+UV_BIN="uv"
+PYTHON_BOOTSTRAP="${PYTHON:-python3}"
+VENV_DIR="${VENV_DIR:-${REPO_ROOT}/.venv-simple-test}"
+TARGET_PY_VERSION="3.12"
+
+if ! command -v "${PYTHON_BOOTSTRAP}" >/dev/null 2>&1; then
+  PYTHON_BOOTSTRAP="python"
+fi
+
+cd "${REPO_ROOT}"
+
+# Ensure pip-installed scripts (including uv) are on PATH
+PYTHON_SCRIPTS="$(${PYTHON_BOOTSTRAP} -c 'import sysconfig; print(sysconfig.get_path("scripts"))')"
+USER_BASE="$(${PYTHON_BOOTSTRAP} -m site --user-base 2>/dev/null || true)"
+PATH="${PYTHON_SCRIPTS}:${PATH}"
+if [[ -n "${USER_BASE}" ]]; then
+  PATH="${USER_BASE}/bin:${PATH}"
+fi
+export HF_HOME=/fsx/hf_cache
+
+if ! command -v "${UV_BIN}" >/dev/null 2>&1; then
+  "${PYTHON_BOOTSTRAP}" -m pip install --upgrade pip
+  "${PYTHON_BOOTSTRAP}" -m pip install uv
+  hash -r
+fi
+
+TARGET_PY_PATH="$(${UV_BIN} python find "${TARGET_PY_VERSION}" 2>/dev/null | head -n1 || true)"
+if [[ -z "${TARGET_PY_PATH}" ]]; then
+  "${UV_BIN}" python install "${TARGET_PY_VERSION}"
+  TARGET_PY_PATH="$(${UV_BIN} python find "${TARGET_PY_VERSION}" 2>/dev/null | head -n1 || true)"
+fi
+
+if [[ -z "${TARGET_PY_PATH}" ]]; then
+  echo "Failed to locate python ${TARGET_PY_VERSION}" >&2
+  exit 1
+fi
+
+if [[ ! -d "${VENV_DIR}" ]]; then
+  "${UV_BIN}" venv --python "${TARGET_PY_PATH}" "${VENV_DIR}"
+fi
+
+VENV_PYTHON="${VENV_DIR}/bin/python"
+[[ -x "${VENV_PYTHON}" ]] || { echo "Python not found in ${VENV_DIR}"; exit 1; }
+
+"${UV_BIN}" pip install --python "${VENV_PYTHON}" vllm==0.11.0
+"${UV_BIN}" pip install --python "${VENV_PYTHON}" -e ".[dev]"
+"${VENV_PYTHON}" -m pytest -s -v tests/test_diffusion_model.py

tests/test_diffusion_model.py

@@ -0,0 +1,28 @@
+import pytest
+import torch
+
+from vllm_omni import Omni
+
+models = ["Tongyi-MAI/Z-Image-Turbo"]
+
+
+@pytest.mark.parametrize("model_name", models)
+def test_diffusion_model(model_name: str):
+    m = Omni(model=model_name)
+    # high resolution may cause OOM on L4
+    height = 256
+    width = 256
+    images = m.generate(
+        "a photo of a cat sitting on a laptop keyboard",
+        height=height,
+        width=width,
+        num_inference_steps=2,
+        guidance_scale=0.0,
+        generator=torch.Generator("cuda").manual_seed(42),
+        num_outputs_per_prompt=2,
+    )
+    assert len(images) == 2
+    # check image size
+    assert images[0].width == width
+    assert images[0].height == height
+    images[0].save("z_image_output.png")