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Unverified Commit 0d50fa1d authored by Andreas Karatzas's avatar Andreas Karatzas Committed by GitHub
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[ROCm][CI] Mark gemma3 as large GPU test to avoid OOM on MI250 (#37610) 


Signed-off-by: default avatarAndreas Karatzas <akaratza@amd.com>
parent 1fa1e53a
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.buildkite/test-amd.yaml
View file @ 0d50fa1d
......@@ -39,8 +39,7 @@
#####################################################################################################################################
# #
# IMPORTANT: #
# * Currently AMD CI has MI300 agents, MI325 agents, and MI355 agents. Of those, AMD is using mostly MI325 and MI355. AMD team #
# is actively working on enabling more MI300 machines. All upcoming feature improvements are tracked in: #
# * Currently AMD CI has MI250 agents, MI325 agents, and MI355 agents. All upcoming feature improvements are tracked in: #
# https://github.com/vllm-project/vllm/issues/34994 #
# #
#-----------------------------------------------------------------------------------------------------------------------------------#
......@@ -49,13 +48,15 @@
# * [Pytorch Nightly Dependency Override Check]: if this test fails, it means the nightly torch version is not compatible with #
# some of the dependencies. Please check the error message and add the package to #
# whitelist in `/vllm/tools/pre_commit/generate_nightly_torch_test.py`. #
# * [Entrypoints Integration Test (LLM)]: #
# * [Entrypoints Integration (LLM)]: #
# - {`pytest -v -s entrypoints/llm/test_generate.py`}: It needs a clean process #
# - {`pytest -v -s entrypoints/offline_mode`}: Needs to avoid interference with other tests #
# * [V1 Test e2e + engine]: The test uses 4 GPUs, but we schedule it on 8-GPU machines for stability. See discussion here: #
# https://github.com/vllm-project/vllm/pull/31040 #
# * [V1 others]: #
# - Split the tests to avoid interference #
# * [Engine / Engine (1 GPU) / e2e Scheduling / e2e Core / V1 e2e / Spec Decode / V1 Sample + Logits / V1 Core + KV + Metrics]: #
# - Previously a single "V1 Test e2e + engine" step, now split across multiple groups. #
# - V1 e2e (2/4 GPUs) uses 4 GPUs but is scheduled on 8-GPU machines for stability. See: #
# https://github.com/vllm-project/vllm/pull/31040 #
# * [V1 Sample + Logits / V1 Core + KV + Metrics / V1 others (CPU)]: #
# - Previously a single "V1 others" step, now split to avoid interference. #
# - Integration test for streaming correctness (requires special branch for __harness__ lib). #
# * [V1 others (CPU)]: Split the tests to avoid interference #
# * [PyTorch Compilation Unit Tests]: Run unit tests defined directly under `compile/`, not including subdirectories, which #
......@@ -83,9 +84,9 @@
# run plamo2 model in vLLM. #
# * [Language Models Test (Extended Generation)]: Install fast path packages for testing against transformers (mamba, conv1d) #
# and to run plamo2 model in vLLM. #
# * [Multi-Modal Models (Standard)]: #
# * [Multi-Modal Models (Standard) 1-4]: #
# - Do NOT remove `VLLM_WORKER_MULTIPROC_METHOD=spawn` setting as ROCm requires this for certain models to function. #
# * [Transformers Nightly Models Test]: Whisper needs `VLLM_WORKER_MULTIPROC_METHOD=spawn` to avoid deadlock. #
# * [Transformers Nightly Models]: Whisper needs `VLLM_WORKER_MULTIPROC_METHOD=spawn` to avoid deadlock. #
# * [Plugin Tests (2 GPUs)]: #
# - {`pytest -v -s entrypoints/openai/test_oot_registration.py`}: It needs a clean process #
# - {`pytest -v -s models/test_oot_registration.py`}: It needs a clean process #
......@@ -94,11 +95,11 @@
# - There is some Tensor Parallelism related processing logic in LoRA that requires multi-GPU testing for validation. #
# - {`pytest -v -s -x lora/test_gptoss_tp.py`}: Disabled for now because MXFP4 backend on non-cuda platform doesn't support #
# LoRA yet. #
# * [Distributed Tests (GPU_TAG)]: Don't test llama model here, it seems hf implementation is buggy. See: #
# https://github.com/vllm-project/vllm/pull/5689 #
# * [Distributed Tests (GPU_TAG)]: Some old E2E tests were removed in https://github.com/vllm-project/vllm/pull/33293 in #
# favor of new tests in fusions_e2e. We avoid replicating the new jobs in #
# this file as it's deprecated. #
# * [Distributed Tests (NxGPUs)(HW-TAG)]: Don't test llama model here, it seems hf implementation is buggy. See: #
# https://github.com/vllm-project/vllm/pull/5689 #
# * [Distributed Tests (NxGPUs)(HW-TAG)]: Some old E2E tests were removed in https://github.com/vllm-project/vllm/pull/33293 #
# in favor of new tests in fusions_e2e. We avoid replicating the new jobs in #
# this file as it's deprecated. #
# #
#####################################################################################################################################
......
tests/models/multimodal/generation/test_common.py
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......@@ -220,7 +220,10 @@ VLM_TEST_SETTINGS = {
vllm_runner_kwargs={
"model_impl": "transformers",
},
marks=[pytest.mark.core_model],
marks=[
pytest.mark.core_model,
*([large_gpu_mark(min_gb=80)] if current_platform.is_rocm() else []),
],
),
"idefics3-transformers": VLMTestInfo(
models=["HuggingFaceTB/SmolVLM-256M-Instruct"],
......
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