Commit 3b50924c authored by raojy's avatar raojy
Browse files

raw_vllm

parent fbeb8a6f
Pipeline #3455 canceled with stages
group: Basic Correctness
depends_on:
- image-build
steps:
- label: Basic Correctness
timeout_in_minutes: 30
source_file_dependencies:
- vllm/
- tests/basic_correctness/test_basic_correctness
- tests/basic_correctness/test_cpu_offload
- tests/basic_correctness/test_cumem.py
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s basic_correctness/test_cumem.py
- pytest -v -s basic_correctness/test_basic_correctness.py
- pytest -v -s basic_correctness/test_cpu_offload.py
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
group: Benchmarks
depends_on:
- image-build
steps:
- label: Benchmarks
timeout_in_minutes: 20
working_dir: "/vllm-workspace/.buildkite"
source_file_dependencies:
- benchmarks/
commands:
- bash scripts/run-benchmarks.sh
- label: Benchmarks CLI Test
timeout_in_minutes: 20
source_file_dependencies:
- vllm/
- tests/benchmarks/
commands:
- pytest -v -s benchmarks/
- label: Attention Benchmarks Smoke Test (B200)
device: b200
num_gpus: 2
optional: true
working_dir: "/vllm-workspace/"
timeout_in_minutes: 10
source_file_dependencies:
- benchmarks/attention_benchmarks/
- vllm/v1/attention/
commands:
- python3 benchmarks/attention_benchmarks/benchmark.py --backends flash flashinfer --batch-specs "8q1s1k" --repeats 1 --warmup-iters 1
group: Compile
depends_on:
- image-build
steps:
- label: Sequence Parallel Correctness Tests (2 GPUs)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
num_devices: 2
source_file_dependencies:
- vllm/model_executor/layers/
- vllm/compilation/
- vllm/v1/worker/
- vllm/v1/cudagraph_dispatcher.py
- tests/compile/correctness_e2e/test_sequence_parallel.py
commands:
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- pytest -v -s tests/compile/correctness_e2e/test_sequence_parallel.py
- label: Sequence Parallel Correctness Tests (2xH100)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: h100
optional: true
num_devices: 2
commands:
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- pytest -v -s tests/compile/correctness_e2e/test_sequence_parallel.py
- label: AsyncTP Correctness Tests (2xH100)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: h100
optional: true
num_devices: 2
commands:
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- pytest -v -s tests/compile/correctness_e2e/test_async_tp.py
- label: Distributed Compile Unit Tests (2xH100)
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: h100
num_devices: 2
source_file_dependencies:
- vllm/compilation/
- vllm/model_executor/layers
- tests/compile/passes/distributed/
commands:
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
- pytest -s -v tests/compile/passes/distributed
- label: Fusion and Compile Unit Tests (B200)
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: b200
source_file_dependencies:
- csrc/quantization/fp4/
- vllm/model_executor/layers/quantization/
- vllm/model_executor/layers/layernorm.py
- vllm/model_executor/layers/activation.py
- vllm/model_executor/layers/attention/attention.py
- vllm/v1/attention/backends/flashinfer.py
- vllm/compilation/ # TODO(luka) limit to vllm/compilation/passes
- tests/compile/passes/test_fusion_attn.py
- tests/compile/passes/test_silu_mul_quant_fusion.py
- tests/compile/passes/distributed/test_fusion_all_reduce.py
- tests/compile/fullgraph/test_full_graph.py
commands:
# b200 runners are limited, so we limit the tests to the minimum set only supported on Blackwell
- nvidia-smi
- pytest -v -s tests/compile/passes/test_fusion_attn.py -k FLASHINFER
- pytest -v -s tests/compile/passes/test_silu_mul_quant_fusion.py
# this runner has 2 GPUs available even though num_devices=2 is not set
- pytest -v -s tests/compile/passes/distributed/test_fusion_all_reduce.py
# test_fp8_kv_scale_compile requires FlashAttention (not supported on default L4/L40)
# TODO(luka) move to H100 once pass tests run on H100
- pytest -v -s tests/compile/fullgraph/test_full_graph.py::test_fp8_kv_scale_compile
- label: Fusion E2E Quick (H100)
timeout_in_minutes: 15
working_dir: "/vllm-workspace/"
device: h100
num_devices: 1
source_file_dependencies:
- csrc/quantization/
- vllm/model_executor/
- vllm/v1/attention/
- vllm/compilation/
- tests/compile/fusions_e2e/
commands:
- nvidia-smi
# Run all models and attn backends but only Inductor partition and native custom ops
- pytest -v -s tests/compile/fusions_e2e/test_tp1_quant.py -k "inductor_partition and not +rms_norm and not +quant_fp8"
# Qwen requires +quant_fp8 as -quant_fp8 rms+quant fusion is not supported
- pytest -v -s tests/compile/fusions_e2e/test_tp1_quant.py -k "inductor_partition and not +rms_norm and +quant_fp8 and qwen3"
- label: Fusion E2E Config Sweep (H100)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: h100
num_devices: 1
source_file_dependencies:
- csrc/quantization/
- vllm/compilation/
# can affect pattern matching
- vllm/model_executor/layers/layernorm.py
- vllm/model_executor/layers/activation.py
- vllm/model_executor/layers/attention/attention.py
- vllm/model_executor/layers/quantization/input_quant_fp8.py
- tests/compile/fusions_e2e/
commands:
- nvidia-smi
# Run just llama3 (fp8) for all config combinations
- pytest -v -s tests/compile/fusions_e2e/test_tp1_quant.py -k "llama-3"
- label: Fusion E2E Config Sweep (B200)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: b200
num_devices: 1
optional: true
commands:
- nvidia-smi
# Run all models but only FLASHINFER, Inductor partition and native custom ops
# Qwen requires +quant_fp8 as -quant_fp8 rms+quant fusion is not supported
# Run just llama3 (fp8 & fp4) for all config combinations (only inductor partition)
- pytest -v -s tests/compile/fusions_e2e/test_tp1_quant.py -k "inductor_partition and (FLASHINFER and not +rms_norm and (not +quant_fp8 or +quant_fp8 and qwen3) or llama-3)"
- label: Fusion E2E TP2 Quick (H100)
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: h100
num_devices: 2
source_file_dependencies:
- csrc/quantization/
- vllm/model_executor/
- vllm/v1/attention/
- vllm/compilation/
- tests/compile/fusions_e2e/
commands:
- nvidia-smi
# Run all models and attn backends but only Inductor partition and native custom ops
- pytest -v -s tests/compile/fusions_e2e/test_tp2_ar_rms.py -k "inductor_partition and not +rms_norm and not +quant_fp8"
- pytest -v -s tests/compile/fusions_e2e/test_tp2_async_tp.py -k "inductor_partition and not +rms_norm and not +quant_fp8"
- label: Fusion E2E TP2 AR-RMS Config Sweep (H100)
timeout_in_minutes: 40
working_dir: "/vllm-workspace/"
device: h100
num_devices: 2
source_file_dependencies:
- csrc/quantization/
- vllm/compilation/
# can affect pattern matching
- vllm/model_executor/layers/layernorm.py
- vllm/model_executor/layers/activation.py
- vllm/model_executor/layers/attention/attention.py
- vllm/model_executor/layers/quantization/input_quant_fp8.py
- tests/compile/fusions_e2e/
commands:
- nvidia-smi
# Run just llama3 (fp8 & bf16) for all config combinations
- pytest -v -s tests/compile/fusions_e2e/test_tp2_ar_rms.py -k "llama-3"
- label: Fusion E2E TP2 AsyncTP Config Sweep (H100)
timeout_in_minutes: 40
working_dir: "/vllm-workspace/"
device: h100
num_devices: 2
source_file_dependencies:
- csrc/quantization/
- vllm/compilation/
# can affect pattern matching
- vllm/model_executor/layers/layernorm.py
- vllm/model_executor/layers/activation.py
- vllm/model_executor/layers/attention/attention.py
- vllm/model_executor/layers/quantization/input_quant_fp8.py
- tests/compile/fusions_e2e/
commands:
- nvidia-smi
# Run just llama3 (fp8 & bf16) for all config combinations
- pytest -v -s tests/compile/fusions_e2e/test_tp2_async_tp.py -k "llama-3"
- label: Fusion E2E TP2 (B200)
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: b200
num_devices: 2
source_file_dependencies:
- csrc/quantization/
- vllm/model_executor/
- vllm/v1/attention/
- vllm/compilation/
- tests/compile/fusions_e2e/
commands:
- nvidia-smi
# Run all models but only FLASHINFER, Inductor partition and native custom ops
# include qwen with +quant_fp8 as -quant_fp8 rms+quant fusion is not supported
# for ar-rms-quant-fp4, also sweep llama3
- pytest -v -s tests/compile/fusions_e2e/test_tp2_ar_rms.py -k "(FLASHINFER and inductor_partition and not +rms_norm and (not +quant_fp8 or +quant_fp8 and qwen3)) or Llama-3.1-8B-Instruct-FP4"
- pytest -v -s tests/compile/fusions_e2e/test_tp2_async_tp.py -k "FLASHINFER and inductor_partition and not +rms_norm and (not +quant_fp8 or +quant_fp8 and qwen3)"
group: CUDA
depends_on:
- image-build
steps:
- label: Platform Tests (CUDA)
timeout_in_minutes: 15
source_file_dependencies:
- vllm/
- tests/cuda
commands:
- pytest -v -s cuda/test_cuda_context.py
- pytest -v -s cuda/test_platform_no_cuda_init.py
- label: Cudagraph
timeout_in_minutes: 20
source_file_dependencies:
- tests/v1/cudagraph
- vllm/v1/cudagraph_dispatcher.py
- vllm/config/compilation.py
- vllm/compilation
commands:
- pytest -v -s v1/cudagraph/test_cudagraph_dispatch.py
- pytest -v -s v1/cudagraph/test_cudagraph_mode.py
\ No newline at end of file
group: Distributed
depends_on:
- image-build
steps:
- label: Distributed Comm Ops
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/distributed
- tests/distributed
commands:
- pytest -v -s distributed/test_comm_ops.py
- pytest -v -s distributed/test_shm_broadcast.py
- pytest -v -s distributed/test_shm_buffer.py
- pytest -v -s distributed/test_shm_storage.py
- label: Distributed (2 GPUs)
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/compilation/
- vllm/distributed/
- vllm/engine/
- vllm/executor/
- vllm/worker/worker_base.py
- vllm/v1/engine/
- vllm/v1/worker/
- tests/compile/fullgraph/test_basic_correctness.py
- tests/compile/test_wrapper.py
- tests/distributed/
- tests/entrypoints/llm/test_collective_rpc.py
- tests/v1/distributed
- tests/v1/entrypoints/openai/test_multi_api_servers.py
- tests/v1/shutdown
- tests/v1/worker/test_worker_memory_snapshot.py
commands:
# https://github.com/NVIDIA/nccl/issues/1838
- export NCCL_CUMEM_HOST_ENABLE=0
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_async_llm_dp.py
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_eagle_dp.py
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_external_lb_dp.py
- DP_SIZE=2 pytest -v -s v1/entrypoints/openai/test_multi_api_servers.py
- pytest -v -s entrypoints/llm/test_collective_rpc.py
- pytest -v -s ./compile/fullgraph/test_basic_correctness.py
- pytest -v -s ./compile/test_wrapper.py
- VLLM_TEST_SAME_HOST=1 torchrun --nproc-per-node=4 distributed/test_same_node.py | grep 'Same node test passed'
- VLLM_TEST_SAME_HOST=1 VLLM_TEST_WITH_DEFAULT_DEVICE_SET=1 torchrun --nproc-per-node=4 distributed/test_same_node.py | grep 'Same node test passed'
- CUDA_VISIBLE_DEVICES=0,1 pytest -v -s v1/shutdown
- pytest -v -s v1/worker/test_worker_memory_snapshot.py
- label: Distributed Tests (4 GPUs)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/
- tests/distributed/test_utils
- tests/distributed/test_pynccl
- tests/distributed/test_events
- tests/compile/fullgraph/test_basic_correctness.py
- examples/offline_inference/rlhf.py
- examples/offline_inference/rlhf_colocate.py
- examples/offline_inference/new_weight_syncing/
- tests/examples/offline_inference/data_parallel.py
- tests/v1/distributed
- tests/v1/engine/test_engine_core_client.py
- tests/distributed/test_symm_mem_allreduce.py
commands:
# https://github.com/NVIDIA/nccl/issues/1838
- export NCCL_CUMEM_HOST_ENABLE=0
# test with torchrun tp=2 and external_dp=2
- torchrun --nproc-per-node=4 distributed/test_torchrun_example.py
# test with torchrun tp=2 and pp=2
- PP_SIZE=2 torchrun --nproc-per-node=4 distributed/test_torchrun_example.py
# test with torchrun tp=4 and dp=1
- TP_SIZE=4 torchrun --nproc-per-node=4 distributed/test_torchrun_example_moe.py
# test with torchrun tp=2, pp=2 and dp=1
- PP_SIZE=2 TP_SIZE=2 torchrun --nproc-per-node=4 distributed/test_torchrun_example_moe.py
# test with torchrun tp=1 and dp=4 with ep
- DP_SIZE=4 ENABLE_EP=1 torchrun --nproc-per-node=4 distributed/test_torchrun_example_moe.py
# test with torchrun tp=2 and dp=2 with ep
- TP_SIZE=2 DP_SIZE=2 ENABLE_EP=1 torchrun --nproc-per-node=4 distributed/test_torchrun_example_moe.py
# test with internal dp
- python3 ../examples/offline_inference/data_parallel.py --enforce-eager
- TP_SIZE=2 DP_SIZE=2 pytest -v -s v1/distributed/test_async_llm_dp.py
- TP_SIZE=2 DP_SIZE=2 pytest -v -s v1/distributed/test_eagle_dp.py
- TP_SIZE=2 DP_SIZE=2 pytest -v -s v1/distributed/test_external_lb_dp.py
- TP_SIZE=1 DP_SIZE=4 pytest -v -s v1/distributed/test_internal_lb_dp.py
- TP_SIZE=1 DP_SIZE=4 pytest -v -s v1/distributed/test_hybrid_lb_dp.py
- pytest -v -s v1/engine/test_engine_core_client.py::test_kv_cache_events_dp
- pytest -v -s distributed/test_utils.py
- pytest -v -s compile/fullgraph/test_basic_correctness.py
- pytest -v -s distributed/test_pynccl.py
- pytest -v -s distributed/test_events.py
- pytest -v -s distributed/test_symm_mem_allreduce.py
# TODO: create a dedicated test section for multi-GPU example tests
# when we have multiple distributed example tests
# OLD rlhf examples
- cd ../examples/offline_inference
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 rlhf.py
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 RAY_DEDUP_LOGS=0 python3 rlhf_colocate.py
# NEW rlhf examples
- cd new_weight_syncing
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 rlhf_nccl.py
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 rlhf_ipc.py
- label: Distributed Tests (8 GPUs)(H100)
timeout_in_minutes: 10
device: h100
num_devices: 8
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- examples/offline_inference/torchrun_dp_example.py
- vllm/config/parallel.py
- vllm/distributed/
- vllm/v1/engine/llm_engine.py
- vllm/v1/executor/uniproc_executor.py
- vllm/v1/worker/gpu_worker.py
commands:
# https://github.com/NVIDIA/nccl/issues/1838
- export NCCL_CUMEM_HOST_ENABLE=0
# test with torchrun tp=2 and dp=4 with ep
- torchrun --nproc-per-node=8 ../examples/offline_inference/torchrun_dp_example.py --tp-size=2 --pp-size=1 --dp-size=4 --enable-ep
- label: Distributed Tests (4 GPUs)(A100)
device: a100
optional: true
num_devices: 4
source_file_dependencies:
- vllm/
commands:
# NOTE: don't test llama model here, it seems hf implementation is buggy
# see https://github.com/vllm-project/vllm/pull/5689 for details
- pytest -v -s distributed/test_custom_all_reduce.py
- torchrun --nproc_per_node=2 distributed/test_ca_buffer_sharing.py
- TARGET_TEST_SUITE=A100 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
- pytest -v -s -x lora/test_mixtral.py
- label: Distributed Tests (2 GPUs)(H100)
timeout_in_minutes: 15
device: h100
optional: true
working_dir: "/vllm-workspace/"
num_devices: 2
commands:
- pytest -v -s tests/distributed/test_context_parallel.py
# - VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 examples/offline_inference/new_weight_syncing/rlhf_async_new_apis.py --- failing, need to re-enable
- VLLM_USE_DEEP_GEMM=1 VLLM_LOGGING_LEVEL=DEBUG python3 examples/offline_inference/data_parallel.py --model=Qwen/Qwen1.5-MoE-A2.7B -tp=1 -dp=2 --max-model-len=2048 --all2all-backend=deepep_high_throughput
- pytest -v -s tests/v1/distributed/test_dbo.py
- label: Distributed Tests (2 GPUs)(B200)
device: b200
optional: true
working_dir: "/vllm-workspace/"
num_devices: 2
commands:
- pytest -v -s tests/distributed/test_context_parallel.py
- pytest -v -s tests/distributed/test_nccl_symm_mem_allreduce.py
- pytest -v -s tests/v1/distributed/test_dbo.py
- label: 2 Node Test (4 GPUs)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
num_nodes: 2
no_plugin: true
optional: true # TODO: revert once infra issue solved
source_file_dependencies:
- vllm/distributed/
- vllm/engine/
- vllm/executor/
- vllm/model_executor/models/
- tests/distributed/
- tests/examples/offline_inference/data_parallel.py
commands:
- ./.buildkite/scripts/run-multi-node-test.sh /vllm-workspace/tests 2 2 $IMAGE_TAG "VLLM_TEST_SAME_HOST=0 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_same_node.py | grep 'Same node test passed' && NUM_NODES=2 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_node_count.py | grep 'Node count test passed' && python3 ../examples/offline_inference/data_parallel.py -dp=2 -tp=1 --dp-num-nodes=2 --dp-node-rank=0 --dp-master-addr=192.168.10.10 --dp-master-port=12345 --enforce-eager --trust-remote-code && VLLM_MULTI_NODE=1 pytest -v -s distributed/test_multi_node_assignment.py && VLLM_MULTI_NODE=1 pytest -v -s distributed/test_pipeline_parallel.py" "VLLM_TEST_SAME_HOST=0 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_same_node.py | grep 'Same node test passed' && NUM_NODES=2 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_node_count.py | grep 'Node count test passed' && python3 ../examples/offline_inference/data_parallel.py -dp=2 -tp=1 --dp-num-nodes=2 --dp-node-rank=1 --dp-master-addr=192.168.10.10 --dp-master-port=12345 --enforce-eager --trust-remote-code"
- label: Distributed NixlConnector PD accuracy (4 GPUs)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: DP EP Distributed NixlConnector PD accuracy tests (4 GPUs)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- DP_EP=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: CrossLayer KV layout Distributed NixlConnector PD accuracy tests (4 GPUs)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- CROSS_LAYERS_BLOCKS=True bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Pipeline + Context Parallelism (4 GPUs)
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/
- vllm/engine/
- vllm/executor/
- vllm/model_executor/models/
- tests/distributed/
commands:
- pytest -v -s distributed/test_pp_cudagraph.py
- pytest -v -s distributed/test_pipeline_parallel.py
group: E2E Integration
depends_on:
- image-build
steps:
- label: DeepSeek V2-Lite Accuracy
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 4
working_dir: "/vllm-workspace"
commands:
- bash .buildkite/scripts/scheduled_integration_test/deepseek_v2_lite_ep_eplb.sh 0.25 200 8010
- label: Qwen3-30B-A3B-FP8-block Accuracy
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 4
working_dir: "/vllm-workspace"
commands:
- bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020
- label: Qwen3-30B-A3B-FP8-block Accuracy (B200)
timeout_in_minutes: 60
device: b200
optional: true
num_devices: 2
working_dir: "/vllm-workspace"
commands:
- bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020 2 1
- label: DeepSeek V2-Lite Prefetch Offload Accuracy (H100)
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 1
working_dir: "/vllm-workspace"
commands:
- bash .buildkite/scripts/scheduled_integration_test/deepseek_v2_lite_prefetch_offload.sh 0.25 200 8030
group: Engine
depends_on:
- image-build
steps:
- label: Engine
timeout_in_minutes: 15
source_file_dependencies:
- vllm/
- tests/engine
- tests/test_sequence
- tests/test_config
- tests/test_logger
- tests/test_vllm_port
commands:
- pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py
- label: V1 e2e + engine (1 GPU)
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
- tests/v1
commands:
# TODO: accuracy does not match, whether setting
# VLLM_USE_FLASHINFER_SAMPLER or not on H100.
- pytest -v -s v1/e2e
# Run this test standalone for now;
# need to untangle use (implicit) use of spawn/fork across the tests.
- pytest -v -s v1/engine/test_preprocess_error_handling.py
# Run the rest of v1/engine tests
- pytest -v -s v1/engine --ignore v1/engine/test_preprocess_error_handling.py
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
commands:
- pytest -v -s v1/e2e
- pytest -v -s v1/engine
- label: V1 e2e (2 GPUs)
timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
optional: true
num_devices: 2
source_file_dependencies:
- vllm/
- tests/v1/e2e
commands:
# Only run tests that need exactly 2 GPUs
- pytest -v -s v1/e2e/test_spec_decode.py -k "tensor_parallelism"
mirror:
amd:
device: mi325_2
depends_on:
- image-build-amd
- label: V1 e2e (4 GPUs)
timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
optional: true
num_devices: 4
source_file_dependencies:
- vllm/
- tests/v1/e2e
commands:
# Only run tests that need 4 GPUs
- pytest -v -s v1/e2e/test_spec_decode.py -k "eagle_correctness_heavy"
mirror:
amd:
device: mi325_4
depends_on:
- image-build-amd
group: Entrypoints
depends_on:
- image-build
steps:
- label: Entrypoints Unit Tests
timeout_in_minutes: 10
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/entrypoints
- tests/entrypoints/
commands:
- pytest -v -s entrypoints/openai/tool_parsers
- pytest -v -s entrypoints/ --ignore=entrypoints/llm --ignore=entrypoints/rpc --ignore=entrypoints/sleep --ignore=entrypoints/instrumentator --ignore=entrypoints/openai --ignore=entrypoints/offline_mode --ignore=entrypoints/test_chat_utils.py --ignore=entrypoints/pooling
- label: Entrypoints Integration (LLM)
timeout_in_minutes: 40
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/llm
- tests/entrypoints/offline_mode
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/llm --ignore=entrypoints/llm/test_generate.py --ignore=entrypoints/llm/test_collective_rpc.py
- 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
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server 1)
timeout_in_minutes: 130
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/openai
- tests/entrypoints/test_chat_utils
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/openai --ignore=entrypoints/openai/test_chat_with_tool_reasoning.py --ignore=entrypoints/openai/test_oot_registration.py --ignore=entrypoints/openai/test_tensorizer_entrypoint.py --ignore=entrypoints/openai/correctness/ --ignore=entrypoints/openai/tool_parsers/ --ignore=entrypoints/openai/responses
- pytest -v -s entrypoints/test_chat_utils.py
- label: Entrypoints Integration (API Server 2)
timeout_in_minutes: 130
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/rpc
- tests/entrypoints/instrumentator
- tests/tool_use
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/instrumentator
- PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/rpc
- pytest -v -s tool_use
- label: Entrypoints Integration (Pooling)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/pooling
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/pooling
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: Entrypoints Integration (Responses API)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/openai/responses
commands:
- pytest -v -s entrypoints/openai/responses
- label: Entrypoints V1
timeout_in_minutes: 50
source_file_dependencies:
- vllm/
- tests/v1
commands:
- pytest -v -s v1/entrypoints
- label: OpenAI API Correctness
timeout_in_minutes: 30
source_file_dependencies:
- csrc/
- vllm/entrypoints/openai/
- vllm/model_executor/models/whisper.py
commands: # LMEval+Transcription WER check
- pytest -s entrypoints/openai/correctness/
group: Expert Parallelism
depends_on:
- image-build
steps:
- label: EPLB Algorithm
timeout_in_minutes: 15
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/distributed/eplb
- tests/distributed/test_eplb_algo.py
commands:
- pytest -v -s distributed/test_eplb_algo.py
- label: EPLB Execution
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/eplb
- tests/distributed/test_eplb_execute.py
commands:
- pytest -v -s distributed/test_eplb_execute.py
- pytest -v -s distributed/test_eplb_spec_decode.py
- label: Elastic EP Scaling Test
timeout_in_minutes: 20
device: b200
optional: true
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/
- vllm/engine/
- vllm/executor/
- vllm/compilation/
- tests/distributed/
commands:
- pytest -v -s distributed/test_elastic_ep.py
group: Kernels
depends_on:
- image-build
steps:
- label: Kernels Core Operation Test
timeout_in_minutes: 75
source_file_dependencies:
- csrc/
- tests/kernels/core
- tests/kernels/test_top_k_per_row.py
commands:
- pytest -v -s kernels/core kernels/test_top_k_per_row.py
- label: Kernels Attention Test %N
timeout_in_minutes: 35
source_file_dependencies:
- csrc/attention/
- vllm/v1/attention
# TODO: remove this dependency (https://github.com/vllm-project/vllm/issues/32267)
- vllm/model_executor/layers/attention
- tests/kernels/attention
commands:
- pytest -v -s kernels/attention --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
- label: Kernels Quantization Test %N
timeout_in_minutes: 90
source_file_dependencies:
- csrc/quantization/
- vllm/model_executor/layers/quantization
- tests/kernels/quantization
commands:
- pytest -v -s kernels/quantization --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
- label: Kernels MoE Test %N
timeout_in_minutes: 60
source_file_dependencies:
- csrc/quantization/cutlass_w8a8/moe/
- csrc/moe/
- tests/kernels/moe
- vllm/model_executor/layers/fused_moe/
- vllm/distributed/device_communicators/
- vllm/envs.py
- vllm/config
commands:
- pytest -v -s kernels/moe --ignore=kernels/moe/test_modular_oai_triton_moe.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
- pytest -v -s kernels/moe/test_modular_oai_triton_moe.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
- label: Kernels Mamba Test
timeout_in_minutes: 45
source_file_dependencies:
- csrc/mamba/
- tests/kernels/mamba
- vllm/model_executor/layers/mamba/ops
commands:
- pytest -v -s kernels/mamba
- label: Kernels DeepGEMM Test (H100)
timeout_in_minutes: 45
device: h100
num_devices: 1
source_file_dependencies:
- tools/install_deepgemm.sh
- vllm/utils/deep_gemm.py
- vllm/model_executor/layers/fused_moe
- vllm/model_executor/layers/quantization
- tests/kernels/quantization/test_block_fp8.py
- tests/kernels/moe/test_deepgemm.py
- tests/kernels/moe/test_batched_deepgemm.py
- tests/kernels/attention/test_deepgemm_attention.py
commands:
- pytest -v -s kernels/quantization/test_block_fp8.py
- pytest -v -s kernels/moe/test_deepgemm.py
- pytest -v -s kernels/moe/test_batched_deepgemm.py
- pytest -v -s kernels/attention/test_deepgemm_attention.py
- label: Kernels (B200)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: b200
# optional: true
source_file_dependencies:
- csrc/quantization/fp4/
- csrc/attention/mla/
- csrc/quantization/cutlass_w8a8/moe/
- vllm/model_executor/layers/fused_moe/cutlass_moe.py
- vllm/model_executor/layers/fused_moe/flashinfer_cutlass_moe.py
- vllm/model_executor/layers/fused_moe/flashinfer_a2a_prepare_finalize.py
- vllm/model_executor/layers/quantization/utils/flashinfer_utils.py
- vllm/v1/attention/backends/flashinfer.py
- vllm/v1/attention/backends/mla/cutlass_mla.py
- vllm/v1/attention/backends/mla/flashinfer_mla.py
- vllm/v1/attention/selector.py
- vllm/platforms/cuda.py
commands:
- nvidia-smi
- python3 examples/offline_inference/basic/chat.py
# Attention
# num_heads2 broken by https://github.com/flashinfer-ai/flashinfer/issues/1353
- pytest -v -s tests/kernels/attention/test_attention_selector.py
- pytest -v -s tests/kernels/attention/test_flashinfer.py -k 'not num_heads2'
- pytest -v -s tests/kernels/attention/test_flashinfer_trtllm_attention.py
- pytest -v -s tests/kernels/attention/test_cutlass_mla_decode.py
- pytest -v -s tests/kernels/attention/test_flashinfer_mla_decode.py
# Quantization
- pytest -v -s tests/kernels/quantization/test_cutlass_scaled_mm.py -k 'fp8'
- pytest -v -s tests/kernels/quantization/test_nvfp4_quant.py
- pytest -v -s tests/kernels/quantization/test_silu_mul_nvfp4_quant.py
- pytest -v -s tests/kernels/quantization/test_nvfp4_scaled_mm.py
- pytest -v -s tests/kernels/quantization/test_flashinfer_scaled_mm.py
- pytest -v -s tests/kernels/quantization/test_flashinfer_nvfp4_scaled_mm.py
- pytest -v -s tests/kernels/quantization/test_nvfp4_qutlass.py
- pytest -v -s tests/kernels/quantization/test_mxfp4_qutlass.py
- pytest -v -s tests/kernels/moe/test_nvfp4_moe.py
- pytest -v -s tests/kernels/moe/test_ocp_mx_moe.py
- pytest -v -s tests/kernels/moe/test_flashinfer.py
- pytest -v -s tests/kernels/moe/test_flashinfer_moe.py
- pytest -v -s tests/kernels/moe/test_cutedsl_moe.py
# e2e
- pytest -v -s tests/models/quantization/test_nvfp4.py
- label: Kernels Helion Test
timeout_in_minutes: 30
device: h100
source_file_dependencies:
- vllm/utils/import_utils.py
- tests/kernels/helion/
commands:
- pip install helion
- pytest -v -s kernels/helion/
- label: Kernels FP8 MoE Test (1 H100)
timeout_in_minutes: 90
device: h100
num_devices: 1
optional: true
commands:
- pytest -v -s kernels/moe/test_cutlass_moe.py
- pytest -v -s kernels/moe/test_flashinfer.py
- pytest -v -s kernels/moe/test_gpt_oss_triton_kernels.py
- pytest -v -s kernels/moe/test_modular_oai_triton_moe.py
- pytest -v -s kernels/moe/test_moe.py
# - pytest -v -s kernels/moe/test_block_fp8.py - failing on main
- pytest -v -s kernels/moe/test_block_int8.py
- pytest -v -s kernels/moe/test_triton_moe_no_act_mul.py
- pytest -v -s kernels/moe/test_triton_moe_ptpc_fp8.py
- label: Kernels FP8 MoE Test (2 H100s)
timeout_in_minutes: 90
device: h100
num_devices: 2
optional: true
commands:
- pytest -v -s kernels/moe/test_deepep_deepgemm_moe.py
- pytest -v -s kernels/moe/test_deepep_moe.py
- label: Kernels Fp4 MoE Test (B200)
timeout_in_minutes: 60
device: b200
num_devices: 1
optional: true
commands:
- pytest -v -s kernels/moe/test_cutedsl_moe.py
- pytest -v -s kernels/moe/test_flashinfer_moe.py
- pytest -v -s kernels/moe/test_nvfp4_moe.py
- pytest -v -s kernels/moe/test_ocp_mx_moe.py
group: LM Eval
depends_on:
- image-build
steps:
- label: LM Eval Small Models
timeout_in_minutes: 75
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
autorun_on_main: true
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-small.txt
# - label: LM Eval Large Models (4 GPUs)(A100)
# device: a100
# optional: true
# num_devices: 4
# working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
# source_file_dependencies:
# - csrc/
# - vllm/model_executor/layers/quantization
# commands:
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large.txt --tp-size=4
- label: LM Eval Large Models (4 GPUs)(H100)
device: h100
optional: true
num_devices: 4
working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
commands:
- export VLLM_USE_DEEP_GEMM=0 # We found Triton is faster than DeepGEMM for H100
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large-hopper.txt --tp-size=4
- label: LM Eval Small Models (B200)
timeout_in_minutes: 120
device: b200
optional: true
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell.txt
- label: LM Eval Large Models (H200)
timeout_in_minutes: 60
device: h200
optional: true
num_devices: 8
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-h200.txt
- label: MoE Refactor Integration Test (H100 - TEMPORARY)
device: h100
optional: true
num_devices: 2
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor/config-h100.txt
- label: MoE Refactor Integration Test (B200 - TEMPORARY)
device: b200
optional: true
num_devices: 2
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor/config-b200.txt
- label: MoE Refactor Integration Test (B200 DP - TEMPORARY)
device: b200
optional: true
num_devices: 2
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor-dp-ep/config-b200.txt
- label: GPQA Eval (GPT-OSS) (H100)
timeout_in_minutes: 120
device: h100
optional: true
num_devices: 2
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
- tests/evals/gpt_oss/
commands:
- uv pip install --system 'gpt-oss[eval]==0.0.5'
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-h100.txt
- label: GPQA Eval (GPT-OSS) (B200)
timeout_in_minutes: 120
device: b200
optional: true
num_devices: 2
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
- tests/evals/gpt_oss/
commands:
- uv pip install --system 'gpt-oss[eval]==0.0.5'
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-b200.txt
group: LoRA
depends_on:
- image-build
steps:
- label: LoRA %N
timeout_in_minutes: 30
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_chatglm3_tp.py --ignore=lora/test_llama_tp.py --ignore=lora/test_llm_with_multi_loras.py --ignore=lora/test_olmoe_tp.py --ignore=lora/test_deepseekv2_tp.py --ignore=lora/test_gptoss_tp.py --ignore=lora/test_qwen3moe_tp.py
parallelism: 4
- label: LoRA TP (Distributed)
timeout_in_minutes: 30
num_devices: 4
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
# FIXIT: find out which code initialize cuda before running the test
# before the fix, we need to use spawn to test it
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
# Alot of these tests are on the edge of OOMing
- export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
# There is some Tensor Parallelism related processing logic in LoRA that
# requires multi-GPU testing for validation.
- pytest -v -s -x lora/test_chatglm3_tp.py
- pytest -v -s -x lora/test_llama_tp.py
- pytest -v -s -x lora/test_llm_with_multi_loras.py
- pytest -v -s -x lora/test_olmoe_tp.py
- pytest -v -s -x lora/test_gptoss_tp.py
\ No newline at end of file
group: Miscellaneous
depends_on:
- image-build
steps:
- label: V1 Others
timeout_in_minutes: 60
source_file_dependencies:
- vllm/
- tests/v1
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
# split the test to avoid interference
- pytest -v -s -m 'not cpu_test' v1/core
- pytest -v -s v1/executor
- pytest -v -s v1/kv_offload
- pytest -v -s v1/sample
- pytest -v -s v1/logits_processors
- pytest -v -s v1/worker
# TODO: create another `optional` test group for slow tests
- pytest -v -s -m 'not slow_test' v1/spec_decode
- pytest -v -s -m 'not cpu_test' v1/kv_connector/unit
- pytest -v -s -m 'not cpu_test' v1/metrics
- pytest -v -s v1/test_oracle.py
- pytest -v -s v1/test_request.py
- pytest -v -s v1/test_outputs.py
# Integration test for streaming correctness (requires special branch).
- pip install -U git+https://github.com/robertgshaw2-redhat/lm-evaluation-harness.git@streaming-api
- pytest -v -s entrypoints/openai/correctness/test_lmeval.py::test_lm_eval_accuracy_v1_engine
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: V1 Others (CPU)
depends_on:
- image-build-cpu
source_file_dependencies:
- vllm/
- tests/v1
device: cpu
commands:
# split the test to avoid interference
- pytest -v -s -m 'cpu_test' v1/core
- pytest -v -s v1/structured_output
- pytest -v -s v1/test_serial_utils.py
- pytest -v -s -m 'cpu_test' v1/kv_connector/unit
- pytest -v -s -m 'cpu_test' v1/metrics
- label: Regression
timeout_in_minutes: 20
source_file_dependencies:
- vllm/
- tests/test_regression
commands:
- pip install modelscope
- pytest -v -s test_regression.py
working_dir: "/vllm-workspace/tests" # optional
- label: Examples
timeout_in_minutes: 45
working_dir: "/vllm-workspace/examples"
source_file_dependencies:
- vllm/entrypoints
- vllm/multimodal
- examples/
commands:
- pip install tensorizer # for tensorizer test
- python3 offline_inference/basic/chat.py # for basic
- python3 offline_inference/basic/generate.py --model facebook/opt-125m
- python3 offline_inference/basic/generate.py --model meta-llama/Llama-2-13b-chat-hf --cpu-offload-gb 10
- python3 offline_inference/basic/classify.py
- python3 offline_inference/basic/embed.py
- python3 offline_inference/basic/score.py
# for multi-modal models
- python3 offline_inference/audio_language.py --seed 0
- python3 offline_inference/vision_language.py --seed 0
- python3 offline_inference/vision_language_multi_image.py --seed 0
- python3 offline_inference/encoder_decoder_multimodal.py --model-type whisper --seed 0
# for pooling models
- python3 pooling/embed/vision_embedding_offline.py --seed 0
# for features demo
- python3 offline_inference/prefix_caching.py
- python3 offline_inference/llm_engine_example.py
- python3 others/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 others/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
- python3 offline_inference/spec_decode.py --test --method eagle --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 2048
# https://github.com/vllm-project/vllm/pull/26682 uses slightly more memory in PyTorch 2.9+ causing this test to OOM in 1xL4 GPU
- python3 offline_inference/spec_decode.py --test --method eagle3 --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 1536
- label: Metrics, Tracing (2 GPUs)
timeout_in_minutes: 20
num_devices: 2
source_file_dependencies:
- vllm/
- tests/v1/tracing
commands:
- "pip install \
'opentelemetry-sdk>=1.26.0' \
'opentelemetry-api>=1.26.0' \
'opentelemetry-exporter-otlp>=1.26.0' \
'opentelemetry-semantic-conventions-ai>=0.4.1'"
- pytest -v -s v1/tracing
- label: Python-only Installation
depends_on: ~
timeout_in_minutes: 20
source_file_dependencies:
- tests/standalone_tests/python_only_compile.sh
- setup.py
commands:
- bash standalone_tests/python_only_compile.sh
- label: Async Engine, Inputs, Utils, Worker
timeout_in_minutes: 50
source_file_dependencies:
- vllm/
- tests/detokenizer
- tests/multimodal
- tests/utils_
commands:
- pytest -v -s detokenizer
- pytest -v -s -m 'not cpu_test' multimodal
- pytest -v -s utils_
- label: Async Engine, Inputs, Utils, Worker, Config (CPU)
depends_on:
- image-build-cpu
timeout_in_minutes: 30
source_file_dependencies:
- vllm/
- tests/test_inputs.py
- tests/test_outputs.py
- tests/test_pooling_params.py
- tests/test_ray_env.py
- tests/multimodal
- tests/renderers
- tests/standalone_tests/lazy_imports.py
- tests/tokenizers_
- tests/tool_parsers
- tests/transformers_utils
- tests/config
device: cpu
commands:
- python3 standalone_tests/lazy_imports.py
- pytest -v -s test_inputs.py
- pytest -v -s test_outputs.py
- pytest -v -s test_pooling_params.py
- pytest -v -s test_ray_env.py
- pytest -v -s -m 'cpu_test' multimodal
- pytest -v -s renderers
- pytest -v -s tokenizers_
- pytest -v -s tool_parsers
- pytest -v -s transformers_utils
- pytest -v -s config
- label: Batch Invariance (H100)
timeout_in_minutes: 25
device: h100
source_file_dependencies:
- vllm/v1/attention
- vllm/model_executor/layers
- tests/v1/determinism/
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pip install pytest-timeout pytest-forked
- pytest -v -s v1/determinism/test_batch_invariance.py
- pytest -v -s v1/determinism/test_rms_norm_batch_invariant.py
- label: Acceptance Length Test (Large Models) # optional
timeout_in_minutes: 25
gpu: h100
optional: true
num_gpus: 1
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/model_executor/models/mlp_speculator.py
- tests/v1/spec_decode/test_acceptance_length.py
commands:
- export VLLM_ALLOW_INSECURE_SERIALIZATION=1
- pytest -v -s v1/spec_decode/test_acceptance_length.py -m slow_test
group: Model Executor
depends_on:
- image-build
steps:
- label: Model Executor
timeout_in_minutes: 35
source_file_dependencies:
- vllm/engine/arg_utils.py
- vllm/config/model.py
- vllm/model_executor
- tests/model_executor
- tests/entrypoints/openai/test_tensorizer_entrypoint.py
commands:
- apt-get update && apt-get install -y curl libsodium23
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s model_executor
- pytest -v -s entrypoints/openai/test_tensorizer_entrypoint.py
group: Models - Basic
depends_on:
- image-build
steps:
- label: Basic Models Tests (Initialization)
timeout_in_minutes: 45
torch_nightly: true
source_file_dependencies:
- vllm/
- tests/models/test_initialization.py
- tests/models/registry.py
commands:
# Run a subset of model initialization tests
- pytest -v -s models/test_initialization.py::test_can_initialize_small_subset
- label: Basic Models Tests (Extra Initialization) %N
timeout_in_minutes: 45
torch_nightly: true
source_file_dependencies:
- vllm/model_executor/models/
- tests/models/test_initialization.py
- tests/models/registry.py
commands:
# Only when vLLM model source is modified - test initialization of a large
# subset of supported models (the complement of the small subset in the above
# test.) Also run if model initialization test file is modified
- pytest -v -s models/test_initialization.py -k 'not test_can_initialize_small_subset' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
parallelism: 2
- label: Basic Models Tests (Other)
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
- tests/models/test_terratorch.py
- tests/models/test_transformers.py
- tests/models/test_registry.py
commands:
- pytest -v -s models/test_terratorch.py models/test_transformers.py models/test_registry.py
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: Basic Models Test (Other CPU) # 5min
depends_on:
- image-build-cpu
timeout_in_minutes: 10
source_file_dependencies:
- vllm/
- tests/models/test_utils.py
- tests/models/test_vision.py
device: cpu
commands:
- pytest -v -s models/test_utils.py models/test_vision.py
- label: Transformers Nightly Models
working_dir: "/vllm-workspace/"
optional: true
soft_fail: true
commands:
- pip install --upgrade git+https://github.com/huggingface/transformers
- pytest -v -s tests/models/test_initialization.py
- pytest -v -s tests/models/test_transformers.py
- pytest -v -s tests/models/multimodal/processing/
- pytest -v -s tests/models/multimodal/test_mapping.py
- python3 examples/offline_inference/basic/chat.py
- python3 examples/offline_inference/vision_language.py --model-type qwen2_5_vl
# Whisper needs spawn method to avoid deadlock
- VLLM_WORKER_MULTIPROC_METHOD=spawn python3 examples/offline_inference/audio_language.py --model-type whisper
group: Models - Distributed
depends_on:
- image-build
steps:
- label: Distributed Model Tests (2 GPUs)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/model_executor/model_loader/sharded_state_loader.py
- vllm/model_executor/models/
- tests/basic_correctness/
- tests/model_executor/model_loader/test_sharded_state_loader.py
- tests/models/
commands:
- TARGET_TEST_SUITE=L4 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
- CUDA_VISIBLE_DEVICES=0,1 pytest -v -s model_executor/model_loader/test_sharded_state_loader.py
# Avoid importing model tests that cause CUDA reinitialization error
- pytest models/test_transformers.py -v -s -m 'distributed(num_gpus=2)'
- pytest models/language -v -s -m 'distributed(num_gpus=2)'
- pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py
- VLLM_WORKER_MULTIPROC_METHOD=spawn pytest models/multimodal/generation/test_whisper.py -v -s -m 'distributed(num_gpus=2)'
group: Models - Language
depends_on:
- image-build
steps:
- label: Language Models Tests (Standard)
timeout_in_minutes: 25
torch_nightly: true
source_file_dependencies:
- vllm/
- tests/models/language
commands:
# Test standard language models, excluding a subset of slow tests
- pip freeze | grep -E 'torch'
- pytest -v -s models/language -m 'core_model and (not slow_test)'
- label: Language Models Tests (Extra Standard) %N
timeout_in_minutes: 45
torch_nightly: true
source_file_dependencies:
- vllm/model_executor/models/
- tests/models/language/pooling/test_embedding.py
- tests/models/language/generation/test_common.py
- tests/models/language/pooling/test_classification.py
commands:
# Shard slow subset of standard language models tests. Only run when model
# source is modified, or when specified test files are modified
- pip freeze | grep -E 'torch'
- pytest -v -s models/language -m 'core_model and slow_test' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
parallelism: 2
- label: Language Models Tests (Hybrid) %N
timeout_in_minutes: 75
torch_nightly: true
source_file_dependencies:
- vllm/
- tests/models/language/generation
commands:
# Install fast path packages for testing against transformers
# Note: also needed to run plamo2 model in vLLM
- uv pip install --system --no-build-isolation 'git+https://github.com/state-spaces/mamba@v2.3.0'
- uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.5.2'
# Shard hybrid language model tests
- pytest -v -s models/language/generation -m hybrid_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
parallelism: 2
- label: Language Models Test (Extended Generation) # 80min
timeout_in_minutes: 110
optional: true
source_file_dependencies:
- vllm/
- tests/models/language/generation
commands:
# Install fast path packages for testing against transformers
# Note: also needed to run plamo2 model in vLLM
- uv pip install --system --no-build-isolation 'git+https://github.com/state-spaces/mamba@v2.3.0'
- uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.5.2'
- pytest -v -s models/language/generation -m '(not core_model) and (not hybrid_model)'
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
commands:
- uv pip install --system --no-build-isolation 'git+https://github.com/AndreasKaratzas/mamba@fix-rocm-7.0-warp-size-constexpr'
- uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.5.2'
- pytest -v -s models/language/generation -m '(not core_model) and (not hybrid_model)'
- label: Language Models Test (PPL)
timeout_in_minutes: 110
optional: true
source_file_dependencies:
- vllm/
- tests/models/language/generation_ppl_test
commands:
- pytest -v -s models/language/generation_ppl_test
- label: Language Models Test (Extended Pooling) # 36min
timeout_in_minutes: 50
optional: true
source_file_dependencies:
- vllm/
- tests/models/language/pooling
commands:
- pytest -v -s models/language/pooling -m 'not core_model'
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: Language Models Test (MTEB)
timeout_in_minutes: 110
optional: true
source_file_dependencies:
- vllm/
- tests/models/language/pooling_mteb_test
commands:
- pytest -v -s models/language/pooling_mteb_test
group: Models - Multimodal
depends_on:
- image-build
steps:
- label: Multi-Modal Models (Standard) # 60min
timeout_in_minutes: 80
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pip freeze | grep -E 'torch'
- pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/processing
- cd .. && VLLM_WORKER_MULTIPROC_METHOD=spawn pytest -v -s tests/models/multimodal/generation/test_whisper.py -m core_model # Otherwise, mp_method="spawn" doesn't work
- label: Multi-Modal Processor Test (CPU)
depends_on:
- image-build-cpu
timeout_in_minutes: 60
source_file_dependencies:
- vllm/
- tests/models/multimodal
- tests/models/registry.py
device: cpu
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/processing --ignore models/multimodal/processing/test_tensor_schema.py
- label: Multi-Modal Processor # 44min
timeout_in_minutes: 60
source_file_dependencies:
- vllm/
- tests/models/multimodal
- tests/models/registry.py
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/processing/test_tensor_schema.py
- label: Multi-Modal Accuracy Eval (Small Models) # 50min
timeout_in_minutes: 70
working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
source_file_dependencies:
- vllm/multimodal/
- vllm/inputs/
- vllm/v1/core/
commands:
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-mm-small.txt --tp-size=1
- label: Multi-Modal Models (Extended) 1
optional: true
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal -m 'not core_model' --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/processing
- label: Multi-Modal Models (Extended) 2
optional: true
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=0) and not core_model'
- label: Multi-Modal Models (Extended) 3
optional: true
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=1) and not core_model'
group: Plugins
depends_on:
- image-build
steps:
- label: Plugin Tests (2 GPUs)
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/plugins/
- tests/plugins/
commands:
# begin platform plugin and general plugin tests, all the code in-between runs on dummy platform
- pip install -e ./plugins/vllm_add_dummy_platform
- pytest -v -s plugins_tests/test_platform_plugins.py
- pip uninstall vllm_add_dummy_platform -y
# end platform plugin tests
# begin io_processor plugins test, all the code in between uses the prithvi_io_processor plugin
- pip install -e ./plugins/prithvi_io_processor_plugin
- pytest -v -s plugins_tests/test_io_processor_plugins.py
- pip uninstall prithvi_io_processor_plugin -y
# test bge_m3_sparse io_processor plugin
- pip install -e ./plugins/bge_m3_sparse_plugin
- pytest -v -s plugins_tests/test_bge_m3_sparse_io_processor_plugins.py
- pip uninstall bge_m3_sparse_plugin -y
# end io_processor plugins test
# begin stat_logger plugins test
- pip install -e ./plugins/vllm_add_dummy_stat_logger
- pytest -v -s plugins_tests/test_stats_logger_plugins.py
- pip uninstall dummy_stat_logger -y
# end stat_logger plugins test
# other tests continue here:
- pytest -v -s plugins_tests/test_scheduler_plugins.py
- pip install -e ./plugins/vllm_add_dummy_model
- pytest -v -s distributed/test_distributed_oot.py
- 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
- pytest -v -s plugins/lora_resolvers # unit tests for in-tree lora resolver plugins
group: PyTorch
depends_on:
- image-build
steps:
- label: PyTorch Compilation Unit Tests
timeout_in_minutes: 10
source_file_dependencies:
- vllm/
- tests/compile
commands:
# Run unit tests defined directly under compile/,
# not including subdirectories, which are usually heavier
# tests covered elsewhere.
# Use `find` to launch multiple instances of pytest so that
# they do not suffer from https://github.com/vllm-project/vllm/issues/28965
# However, find does not normally propagate error codes, so we combine it with xargs
# (using -0 for proper path handling)
- "find compile/ -maxdepth 1 -name 'test_*.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
- label: PyTorch Compilation Passes Unit Tests
timeout_in_minutes: 20
source_file_dependencies:
- vllm/
- tests/compile/passes
commands:
- pytest -s -v compile/passes --ignore compile/passes/distributed
- label: PyTorch Fullgraph Smoke Test
timeout_in_minutes: 35
source_file_dependencies:
- vllm/
- tests/compile
commands:
# Run smoke tests under fullgraph directory, except test_full_graph.py
# as it is a heavy test that is covered in other steps.
# Use `find` to launch multiple instances of pytest so that
# they do not suffer from https://github.com/vllm-project/vllm/issues/28965
- "find compile/fullgraph/ -name 'test_*.py' -not -name 'test_full_graph.py' -exec pytest -s -v {} \\;"
- label: PyTorch Fullgraph
timeout_in_minutes: 30
source_file_dependencies:
- vllm/
- tests/compile
commands:
# fp8 kv scales not supported on sm89, tested on Blackwell instead
- pytest -v -s compile/fullgraph/test_full_graph.py -k 'not test_fp8_kv_scale_compile'
- label: Pytorch Nightly Dependency Override Check # 2min
# 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
soft_fail: true
source_file_dependencies:
- requirements/nightly_torch_test.txt
commands:
- bash standalone_tests/pytorch_nightly_dependency.sh
\ No newline at end of file
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