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[ROCm] [CI] [Bugfix] Resurface CI Signal, fix MHA AR selection, sync with cuda tests (#2340)

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Signed-off-by: tjtanaa <tunjian.tan@embeddedllm.com>
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TJian authored and GitHub committed 2026-04-11 19:54:22 +08:00
1 parent c9e8411d91
commit 25c0566393
8 files changed
+256 -129
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.buildkite/test-amd-merge.yml
+61 -55
View File
@@ -32,7 +32,6 @@ steps:
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- |
@@ -63,13 +62,12 @@ steps:
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- timeout 15m pytest -s -v -m "core_model and cache and diffusion and not distributed_cuda and L4"
- label: "Diffusion Sequence Parallelism Test"
agent_pool: mi325_2
- label: "Diffusion Sequence Parallelism Test (Need 4 GPUs)"
agent_pool: mi325_4
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
@@ -77,6 +75,7 @@ steps:
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- timeout 20m pytest -s -v tests/e2e/offline_inference/test_sequence_parallel.py
- timeout 20m pytest -s -v tests/diffusion/distributed/test_ulysses_uaa_perf.py
# merge-only tests
- label: "Diffusion Tensor Parallelism Test"
@@ -95,22 +94,14 @@ steps:
commands:
- timeout 20m pytest -s -v tests/diffusion/test_diffusion_worker.py
- label: "Benchmark & Engine Test"
agent_pool: mi325_2
- label: "Engine Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- |
timeout 20m bash -c '
set +e
pytest -s -v tests/benchmarks/test_serve_cli.py
EXIT1=\$?
pytest -s -v tests/engine/test_async_omni_engine_abort.py
EXIT2=\$?
exit \$((EXIT1 | EXIT2))
'
- timeout 20m pytest -s -v tests/engine/test_async_omni_engine_abort.py
- label: "Omni Model Test Qwen2-5-Omni"
agent_pool: mi325_2
@@ -121,6 +112,7 @@ steps:
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- timeout 20m pytest -s -v tests/e2e/offline_inference/test_qwen2_5_omni.py
- timeout 20m pytest -s -v tests/e2e/online_serving/test_qwen2_5_omni.py -m "advanced_model" --run-level "advanced_model"
- label: "Omni Model Test Qwen3-Omni"
agent_pool: mi325_2
@@ -131,11 +123,10 @@ steps:
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- timeout 10m pytest -s -v tests/e2e/offline_inference/test_qwen3_omni.py
- timeout 20m pytest -s -v tests/e2e/online_serving/test_qwen3_omni.py -m "advanced_model" --run-level "advanced_model"
- timeout 30m pytest -s -v tests/e2e/offline_inference/test_qwen3_omni.py tests/e2e/online_serving/test_qwen3_omni.py tests/e2e/online_serving/test_mimo_audio.py -m "advanced_model" --run-level "advanced_model"
- label: "Qwen3-TTS CustomVoice E2E Test"
agent_pool: mi325_2
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
@@ -145,21 +136,21 @@ steps:
export VLLM_LOGGING_LEVEL=DEBUG
export VLLM_WORKER_MULTIPROC_METHOD=spawn
export VLLM_ALLOW_LONG_MAX_MODEL_LEN="1"
pytest -s -v tests/e2e/online_serving/test_qwen3_tts_customvoice.py -m "advanced_model" --run-level "advanced_model" && pytest -s -v tests/e2e/offline_inference/test_qwen3_tts_customvoice.py
pytest -s -v tests/e2e/online_serving/test_qwen3_tts_customvoice.py tests/e2e/offline_inference/test_qwen3_tts_customvoice.py -m "advanced_model" --run-level "advanced_model"
'
- label: "Qwen3-TTS Base E2E Test"
agent_pool: mi325_2
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- |
timeout 20m bash -c '
timeout 30m bash -c '
export VLLM_LOGGING_LEVEL=DEBUG
export VLLM_WORKER_MULTIPROC_METHOD=spawn
export VLLM_ALLOW_LONG_MAX_MODEL_LEN="1"
pytest -s -v tests/e2e/online_serving/test_qwen3_tts_base.py -m "advanced_model" --run-level "advanced_model" && pytest -s -v tests/e2e/offline_inference/test_qwen3_tts_base.py
pytest -s -v tests/e2e/online_serving/test_qwen3_tts_base.py tests/e2e/offline_inference/test_qwen3_tts_base.py -m "advanced_model" --run-level "advanced_model"
'
- label: "Diffusion Image Edit Test"
@@ -173,43 +164,58 @@ steps:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- timeout 20m pytest -s -v tests/e2e/online_serving/test_image_gen_edit.py
# split Bagel Model Test with H100 (Real Weights) into three tests
- label: "Bagel Text2Img Model Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_ROCM_USE_AITER_RMSNORM=0
- timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_text2img.py -m "advanced_model" --run-level "advanced_model" -k "shared_memory" -k "rocm"
# TODO: Bagel test on ROCm is very unstable. @tjtanaa
# Need to debug before reneable numerical changes across large PRs
# # split Bagel Model Test with H100 (Real Weights) into three tests
# - label: "Bagel Text2Img Model Test (1/3)"
# agent_pool: mi325_1
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export GPU_ARCHS=gfx942
# - export VLLM_TEST_CLEAN_GPU_MEMORY=1
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - export VLLM_ROCM_USE_AITER_RMSNORM=0
# - timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_text2img.py -m "advanced_model" --run-level "advanced_model" -k "shared_memory" -k "rocm"
- label: "Bagel Img2Img Model Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_ROCM_USE_AITER_RMSNORM=0
- timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_img2img.py -m "advanced_model" --run-level "advanced_model" -k "rocm"
# - label: "Bagel Img2Img Model Test (2/3)"
# agent_pool: mi325_1
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export GPU_ARCHS=gfx942
# - export VLLM_TEST_CLEAN_GPU_MEMORY=1
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - export VLLM_ROCM_USE_AITER_RMSNORM=0
# - timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_img2img.py -m "advanced_model" --run-level "advanced_model" -k "rocm"
- label: "Bagel Online Serving Test"
# - label: "Bagel Online Serving Test (3/3)"
# agent_pool: mi325_1
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export GPU_ARCHS=gfx942
# - export VLLM_TEST_CLEAN_GPU_MEMORY=1
# - export VLLM_IMAGE_FETCH_TIMEOUT=60
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - export VLLM_ROCM_USE_AITER_RMSNORM=0
# - timeout 40m pytest -s -v tests/e2e/online_serving/test_bagel_online.py -m "advanced_model" --run-level "advanced_model" -k "rocm"
- label: "Voxtral-TTS E2E Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- export VLLM_IMAGE_FETCH_TIMEOUT=60
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_ROCM_USE_AITER_RMSNORM=0
- timeout 40m pytest -s -v tests/e2e/online_serving/test_bagel_online.py -m "advanced_model" --run-level "advanced_model" -k "rocm"
- |
timeout 20m bash -c '
export VLLM_LOGGING_LEVEL=DEBUG
export VLLM_WORKER_MULTIPROC_METHOD=spawn
pytest -s -v tests/e2e/online_serving/test_voxtral_tts.py tests/e2e/offline_inference/test_voxtral_tts.py -m "advanced_model" --run-level "advanced_model"
'
.buildkite/test-amd-ready.yaml
+124 -63
View File
@@ -9,13 +9,37 @@ steps:
- export VLLM_ROCM_USE_AITER=0
- "timeout 20m pytest -v -s -m 'core_model and cpu' --cov=vllm_omni --cov-branch --cov-report=term-missing --cov-report=html --cov-report=xml"
- label: "Diffusion Model Test"
agent_pool: mi325_2
- label: "Voxtral TTS CUDA Unit Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- timeout 20m pytest -s -v tests/e2e/offline_inference/test_t2i_model.py -m "core_model and diffusion" --run-level "core_model"
- timeout 10m pytest -s -v tests/model_executor/models/voxtral_tts/test_cuda_graph_acoustic_transformer.py
- label: "Diffusion Model Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- timeout 30m pytest -s -v tests/e2e/offline_inference/test_t2i_model.py -m "core_model and diffusion" --run-level "core_model"
- label: "Diffusion Batching Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- timeout 20m pytest -s -v tests/e2e/offline_inference/test_qwen_image_diffusion_batching.py -m "core_model and diffusion" --run-level "core_model"
- label: "Custom Pipeline Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- timeout 20m pytest -s -v tests/e2e/offline_inference/custom_pipeline/ -m "core_model"
- label: "Diffusion Model CPU offloading Test"
agent_pool: mi325_1
@@ -23,7 +47,6 @@ steps:
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- |
@@ -77,47 +100,58 @@ steps:
commands:
- timeout 20m pytest -s -v tests/diffusion/test_diffusion_worker.py
- label: "Benchmark & Engine Test"
agent_pool: mi325_2
- label: "Engine Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- |
timeout 30m bash -c '
set +e
pytest -s -v tests/benchmarks/test_serve_cli.py
EXIT1=\$?
pytest -s -v tests/engine/test_async_omni_engine_abort.py
EXIT2=\$?
exit \$((EXIT1 | EXIT2))
timeout 15m bash -c '
pytest -s -v tests/engine/test_async_omni_engine_abort.py
'
- label: "Omni Model Test Qwen2-5-Omni"
agent_pool: mi325_2
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- timeout 17m pytest -s -v tests/e2e/offline_inference/test_qwen2_5_omni.py
- label: "Omni Model Test Qwen3-Omni"
agent_pool: mi325_2
# NOTE: This test is not running any thing. It is skipped and deselected.
# Currently it is = 1 skipped, 1 deselected, 17 warnings in 0.03s ======
# - label: "Omni Model Test Qwen2-5-Omni"
# agent_pool: mi325_2
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - timeout 20m pytest -s -v tests/e2e/offline_inference/test_qwen2_5_omni.py -m "core_model" --run-level "core_model"
# - label: "Omni Model Test Qwen3-Omni"
# agent_pool: mi325_2
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - export VLLM_TEST_CLEAN_GPU_MEMORY=1
# - timeout 10m pytest -s -v tests/e2e/offline_inference/test_qwen3_omni.py
# - timeout 20m pytest -s -v tests/e2e/online_serving/test_qwen3_omni.py -m "core_model" --run-level "core_model"
- label: "MiMo-Audio E2E Test with H100"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- timeout 10m pytest -s -v tests/e2e/offline_inference/test_qwen3_omni.py
- timeout 10m pytest -s -v tests/e2e/online_serving/test_qwen3_omni.py -m "core_model" --run-level "core_model"
- |
timeout 30m bash -c '
export VLLM_LOGGING_LEVEL=DEBUG
export VLLM_WORKER_MULTIPROC_METHOD=spawn
pytest -s -v tests/e2e/online_serving/test_mimo_audio.py -m "core_model" --run-level "core_model"
'
- label: "Qwen3-TTS E2E Test"
agent_pool: mi325_2
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
@@ -125,7 +159,21 @@ steps:
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_ALLOW_LONG_MAX_MODEL_LEN="1"
- timeout 20m pytest -s -v tests/e2e/online_serving/test_qwen3_tts_customvoice.py -m "core_model" --run-level "core_model"
- timeout 30m pytest -s -v tests/e2e/online_serving/test_qwen3_tts_customvoice.py -m "core_model" --run-level "core_model"
- label: "Voxtral-TTS E2E Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- |
timeout 20m bash -c '
export VLLM_LOGGING_LEVEL=DEBUG
export VLLM_WORKER_MULTIPROC_METHOD=spawn
pytest -s -v tests/e2e/online_serving/test_voxtral_tts.py -m "advanced_model" --run-level "advanced_model"
pytest -s -v tests/e2e/offline_inference/test_voxtral_tts.py -m "advanced_model" --run-level "advanced_model"
'
- label: "Diffusion Image Edit Test"
agent_pool: mi325_1
@@ -138,42 +186,55 @@ steps:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- timeout 20m pytest -s -v tests/e2e/online_serving/test_image_gen_edit.py
- label: "Bagel Text2Img Model Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_ROCM_USE_AITER_RMSNORM=0
- timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_text2img.py -m "core_model" --run-level "core_model" -k "rocm"
# TODO: Bagel test on ROCm is very unstable. @tjtanaa
# Need to debug before reneable numerical changes across large PRs
# - label: "Bagel Text2Img Model Test"
# agent_pool: mi325_1
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export GPU_ARCHS=gfx942
# - export VLLM_TEST_CLEAN_GPU_MEMORY=1
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - export VLLM_ROCM_USE_AITER_RMSNORM=0
# - timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_text2img.py -m "core_model" --run-level "core_model" -k "rocm"
- label: "Bagel Img2Img Model Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_ROCM_USE_AITER_RMSNORM=0
- timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_img2img.py -m "core_model" --run-level "core_model" -k "rocm"
# - label: "Bagel Img2Img Model Test"
# agent_pool: mi325_1
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export GPU_ARCHS=gfx942
# - export VLLM_TEST_CLEAN_GPU_MEMORY=1
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - export VLLM_ROCM_USE_AITER_RMSNORM=0
# - timeout 30m pytest -s -v tests/e2e/offline_inference/test_bagel_img2img.py -m "core_model" --run-level "core_model" -k "rocm"
- label: "Bagel Online Serving Test"
# - label: "Bagel Online Serving Test"
# agent_pool: mi325_1
# depends_on: amd-build
# mirror_hardwares: [amdproduction]
# grade: Blocking
# commands:
# - export GPU_ARCHS=gfx942
# - export VLLM_TEST_CLEAN_GPU_MEMORY=1
# - export VLLM_IMAGE_FETCH_TIMEOUT=60
# - export VLLM_LOGGING_LEVEL=DEBUG
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - export VLLM_ROCM_USE_AITER_RMSNORM=0
# - timeout 40m pytest -s -v tests/e2e/online_serving/test_bagel_online.py -m "core_model" --run-level "core_model" -k "rocm"
- label: "CosyVoice3-TTS E2E Test"
agent_pool: mi325_1
depends_on: amd-build
mirror_hardwares: [amdproduction]
grade: Blocking
commands:
- export GPU_ARCHS=gfx942
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- export VLLM_IMAGE_FETCH_TIMEOUT=60
- export VLLM_LOGGING_LEVEL=DEBUG
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export VLLM_ROCM_USE_AITER_RMSNORM=0
- timeout 40m pytest -s -v tests/e2e/online_serving/test_bagel_online.py -m "core_model" --run-level "core_model" -k "rocm"
- |
timeout 20m bash -c '
pytest -s -v tests/e2e/online_serving/test_cosyvoice3_tts.py -m "core_model" --run-level "core_model"
'
.buildkite/test-template-amd-omni.j2
+3
View File
@@ -48,6 +48,9 @@
DOCKER_BUILDKIT: "1"
TEST_COMMAND: |-
(command rocm-smi || true) && cd {{ (step.working_dir or default_working_dir) | safe }}
{% if "mi250" in step.agent_pool %}
python3 -m pip uninstall -y amd-aiter
{% endif %}
{{ indented_cmd | safe }}
priority: 100
{% if step.grade and step.grade == "Blocking" %}
docker/Dockerfile.rocm
+18
View File
@@ -39,6 +39,24 @@ RUN if [ "${USE_NIGHTLY_BUILD}" = "1" ]; then \
# Step 3: Copy vllm-omni code and install without uv
RUN mkdir -p ${COMMON_WORKDIR}/vllm-omni
COPY . ${COMMON_WORKDIR}/vllm-omni
# This is a workaround to ensure pytest exits with the correct status code in CI tests.
RUN printf '%s\n' \
'import os' \
'' \
'_exit_code = 1' \
'' \
'def pytest_sessionfinish(session, exitstatus):' \
' global _exit_code' \
' _exit_code = int(exitstatus)' \
'' \
'def pytest_unconfigure(config):' \
' import sys' \
' sys.stdout.flush()' \
' sys.stderr.flush()' \
' os._exit(_exit_code)' \
> ${COMMON_WORKDIR}/vllm-omni/conftest.py
RUN cd ${COMMON_WORKDIR}/vllm-omni && uv pip install --python "$(python3 -c 'import sys; print(sys.executable)')" --no-cache-dir ".[dev]" --no-build-isolation
RUN ln -sf /usr/bin/python3 /usr/bin/python
tests/e2e/offline_inference/test_t2i_model.py
+1 -6
View File
@@ -26,17 +26,12 @@ models = ["Tongyi-MAI/Z-Image-Turbo", "riverclouds/qwen_image_random"]
# TODO: When NPU support is ready, remove this branch.
if current_omni_platform.is_npu():
models = ["Tongyi-MAI/Z-Image-Turbo", "Qwen/Qwen-Image"]
elif current_omni_platform.is_rocm():
# TODO: When ROCm support is ready, remove this branch.
# Current upstream vLLM has issues running riverclouds/qwen_image_random
# on ROCm
models = ["Tongyi-MAI/Z-Image-Turbo"]
@pytest.mark.core_model
@pytest.mark.advanced_model
@pytest.mark.diffusion
@hardware_test(res={"cuda": "L4", "rocm": "MI325", "xpu": "B60"}, num_cards={"cuda": 1, "rocm": 2, "xpu": 2})
@hardware_test(res={"cuda": "L4", "rocm": "MI325", "xpu": "B60"}, num_cards={"cuda": 1, "rocm": 1, "xpu": 2})
@pytest.mark.parametrize("model_name", models)
def test_diffusion_model(model_name: str, run_level):
if run_level == "core_model" and model_name != "riverclouds/qwen_image_random":
tests/e2e/offline_inference/test_zimage_parallelism.py
+7 -5
View File
@@ -159,8 +159,8 @@ def _run_zimage_generate(
@pytest.mark.parallel
@hardware_test(res={"cuda": "L4", "rocm": "MI325"}, num_cards={"cuda": 4, "rocm": 2})
def test_zimage_tensor_parallel_tp2(tmp_path: Path):
if current_omni_platform.is_npu() or current_omni_platform.is_rocm():
pytest.skip("Z-Image TP e2e test is only supported on CUDA for now.")
if current_omni_platform.is_npu():
pytest.skip("Z-Image TP e2e test is only supported on CUDA and ROCm for now.")
if not current_omni_platform.is_available() or current_omni_platform.device_count() < 2:
pytest.skip("Z-Image TP=2 requires >= 2 devices.")
@@ -211,7 +211,9 @@ def test_zimage_tensor_parallel_tp2(tmp_path: Path):
)
print(f"Z-Image TP perf (lower is better): tp1_time_s={tp1_time_s:.6f}, tp2_time_s={tp2_time_s:.6f}")
assert tp2_time_s < tp1_time_s, f"Expected TP=2 to be faster than TP=1 (tp1={tp1_time_s}, tp2={tp2_time_s})"
# ROCm is not optimized TP2 can be slower than TP1
if not current_omni_platform.is_rocm():
assert tp2_time_s < tp1_time_s, f"Expected TP=2 to be faster than TP=1 (tp1={tp1_time_s}, tp2={tp2_time_s})"
print(f"Z-Image TP peak memory (MB): tp1_peak_mem={tp1_peak_mem:.2f}, tp2_peak_mem={tp2_peak_mem:.2f}")
assert tp2_peak_mem < tp1_peak_mem, (
@@ -221,8 +223,8 @@ def test_zimage_tensor_parallel_tp2(tmp_path: Path):
@pytest.mark.integration
def test_zimage_vae_patch_parallel_tp2(tmp_path: Path):
if current_omni_platform.is_npu() or current_omni_platform.is_rocm():
pytest.skip("Z-Image VAE patch parallel e2e test is only supported on CUDA for now.")
if current_omni_platform.is_npu():
pytest.skip("Z-Image VAE patch parallel e2e test is only supported on CUDA and ROCm for now.")
if not current_omni_platform.is_available() or current_omni_platform.device_count() < 2:
pytest.skip("Z-Image VAE patch parallel TP=2 requires >= 2 devices.")
vllm_omni/engine/stage_init_utils.py
+14
View File
@@ -168,6 +168,20 @@ def extract_stage_metadata(stage_config: Any) -> StageMetadata:
stage_id: int = stage_config.stage_id
stage_type: Literal["llm", "diffusion"] = getattr(stage_config, "stage_type", "llm")
engine_args = stage_config.engine_args
if current_omni_platform.is_rocm():
if engine_args.get("attention_backend") is None:
from vllm._aiter_ops import rocm_aiter_ops
if rocm_aiter_ops.is_enabled():
engine_args["attention_backend"] = "ROCM_AITER_FA"
# Before vLLM v0.19.0, the default attention backend is TRITON_ATTN for ROCm.
# Since vLLM v0.19.0, the default attention backend is ROCM_ATTN for ROCm.
# However, the compatibility of ROCM_ATTN with Omni is not guaranteed.
# Therefore, we still use TRITON_ATTN as the default attention backend,
# when the selected_backend is not specified.
engine_args["attention_backend"] = "TRITON_ATTN"
runtime_cfg = getattr(stage_config, "runtime", {})
engine_input_source: list[int] = getattr(stage_config, "engine_input_source", [])
final_output: bool = getattr(stage_config, "final_output", False)
vllm_omni/platforms/rocm/platform.py
+28
View File
@@ -16,6 +16,34 @@ class RocmOmniPlatform(OmniPlatform, RocmPlatform):
Inherits all ROCm-specific implementations from vLLM's RocmPlatform,
and adds Omni-specific interfaces from OmniPlatform.
NOTE: AR Attention Backend Overriding Logic:
------------------------------------------
Since vLLM v0.19.0, the default attention backend is ROCM_ATTN for ROCm.
However, the compatibility of ROCM_ATTN with Omni is not guaranteed.
Therefore, we still use TRITON_ATTN as the default attention backend,
when the selected_backend is not specified.
So the behaviour of the attention backend overriding logic currently lives in
extract_stage_metadata in `vllm_omni/engine/stage_init_utils.py`
```
if current_omni_platform.is_rocm():
print(f"engine_args: {str(engine_args)}")
if engine_args.get("attention_backend") is None:
from vllm._aiter_ops import rocm_aiter_ops
if rocm_aiter_ops.is_enabled():
engine_args["attention_backend"] = "ROCM_AITER_FA"
# Before vLLM v0.19.0, the default attention backend is TRITON_ATTN for ROCm.
# Since vLLM v0.19.0, the default attention backend is ROCM_ATTN for ROCm.
# However, the compatibility of ROCM_ATTN with Omni is not guaranteed.
# Therefore, we still use TRITON_ATTN as the default attention backend,
# when the selected_backend is not specified.
engine_args["attention_backend"] = "TRITON_ATTN"
```
"""
_omni_enum = OmniPlatformEnum.ROCM