[CI][torch.compile] Reduce e2e fusion test time (#33293)

Signed-off-by: Luka Govedič <lgovedic@redhat.com>
Signed-off-by: ProExpertProg <luka.govedic@gmail.com>
Signed-off-by: Luka Govedič <ProExpertProg@users.noreply.github.com>
This commit is contained in:
Luka Govedič
2026-02-04 19:09:03 -05:00
committed by GitHub
parent 439afa4eea
commit 4d9513537d
17 changed files with 1068 additions and 821 deletions

View File

@@ -16,7 +16,7 @@ steps:
- pytest -v -s distributed/test_shm_storage.py
- label: Distributed (2 GPUs)
timeout_in_minutes: 90
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -47,7 +47,6 @@ steps:
- 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'
- pytest -v -s distributed/test_sequence_parallel.py
- CUDA_VISIBLE_DEVICES=0,1 pytest -v -s v1/shutdown
- pytest -v -s v1/worker/test_worker_memory_snapshot.py
@@ -133,25 +132,13 @@ steps:
- TARGET_TEST_SUITE=A100 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
- pytest -v -s -x lora/test_mixtral.py
- label: Sequence Parallel Tests (H100)
timeout_in_minutes: 60
working_dir: "/vllm-workspace/"
device: h100
optional: true
num_devices: 2
commands:
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
# Run sequence parallel tests
- pytest -v -s tests/distributed/test_sequence_parallel.py
- pytest -v -s tests/compile/distributed/test_sequence_parallelism.py
- label: Distributed Tests (2 GPUs)(H100)
timeout_in_minutes: 15
device: h100
optional: true
working_dir: "/vllm-workspace/"
num_devices: 2
commands:
- VLLM_TEST_CLEAN_GPU_MEMORY=1 pytest -v -s tests/compile/distributed/test_async_tp.py
- pytest -v -s tests/distributed/test_context_parallel.py
- 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
@@ -217,45 +204,3 @@ steps:
commands:
- pytest -v -s distributed/test_pp_cudagraph.py
- pytest -v -s distributed/test_pipeline_parallel.py
- label: Hopper Fusion E2E Tests (H100)
timeout_in_minutes: 70
working_dir: "/vllm-workspace/"
device: h100
optional: true
source_file_dependencies:
- csrc/quantization/fp4/
- vllm/model_executor/layers/quantization/utils/flashinfer_utils.py
- vllm/v1/attention/backends/flashinfer.py
- vllm/compilation/
# can affect pattern matching
- vllm/model_executor/layers/layernorm.py
- vllm/model_executor/layers/activation.py
- vllm/model_executor/layers/quantization/input_quant_fp8.py
- tests/compile/test_fusion_attn.py
commands:
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
# skip Llama-4 since it does not fit on this device
- pytest -v -s tests/compile/test_fusion_attn.py -k 'not Llama-4'
- label: Hopper Fusion Distributed E2E Tests (2xH100)
timeout_in_minutes: 70
working_dir: "/vllm-workspace/"
device: h100
optional: true
num_devices: 2
source_file_dependencies:
- csrc/quantization/fp4/
- vllm/model_executor/layers/quantization/utils/flashinfer_utils.py
- vllm/v1/attention/backends/flashinfer.py
- vllm/compilation/
# can affect pattern matching
- vllm/model_executor/layers/layernorm.py
- vllm/model_executor/layers/activation.py
- vllm/model_executor/layers/quantization/input_quant_fp8.py
- tests/compile/distributed/test_fusions_e2e.py
commands:
- export VLLM_TEST_CLEAN_GPU_MEMORY=1
# Run all e2e fusion tests
- pytest -v -s tests/compile/distributed/test_fusions_e2e.py -k 'not Llama-4'
- pytest -v -s tests/compile/distributed/test_fusion_all_reduce.py