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[ROCm][CI] Fine-tuning queues and test names (#39238)

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Signed-off-by: Andreas Karatzas <akaratza@amd.com>
This commit is contained in:
Andreas Karatzas
2026-06-25 13:24:09 -07:00
committed by GitHub
parent c5e3c40877
commit 2a6f8f0c05
6 changed files with 43 additions and 56 deletions
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.buildkite/test-amd.yaml
+8 -22
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@@ -771,7 +771,7 @@ steps:
#----------------------------------------------------------- mi300 · cuda ------------------------------------------------------------#
- label: Platform Tests (CUDA) # TBD
- label: Platform Tests # TBD
timeout_in_minutes: 180
mirror_hardwares: [amdexperimental, amdproduction, amdgfx942nightly, amdmi300]
agent_pool: mi300_1
@@ -831,7 +831,7 @@ steps:
- pytest -v -s distributed/test_eplb_execute.py
- pytest -v -s distributed/test_eplb_spec_decode.py
- label: Distributed Tests (2xH100-2xMI250) # TBD
- label: Distributed Tests (2xH100-2xMI300) # TBD
timeout_in_minutes: 180
mirror_hardwares: [amdexperimental, amdproduction, amdgfx942nightly, amdmi300]
agent_pool: mi300_2
@@ -843,13 +843,19 @@ steps:
- vllm/model_executor/layers/fused_moe/
- vllm/v1/attention/backends/
- vllm/v1/attention/selector.py
- tests/v1/distributed/test_dbo.py
- tests/distributed/test_context_parallel.py
- examples/features/data_parallel/data_parallel_offline.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
commands:
- pytest -v -s tests/distributed/test_context_parallel.py
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 examples/rl/rlhf_async_new_apis.py
- VLLM_LOGGING_LEVEL=DEBUG python3 examples/features/data_parallel/data_parallel_offline.py --model=Qwen/Qwen1.5-MoE-A2.7B -tp=1 -dp=2 --max-model-len=2048 --all2all-backend=deepep_high_throughput
- VLLM_LOGGING_LEVEL=DEBUG python3 examples/features/data_parallel/data_parallel_offline.py --model=Qwen/Qwen1.5-MoE-A2.7B -tp=1 -dp=2 --max-model-len=2048 --all2all-backend=allgather_reducescatter --disable-nccl-for-dp-synchronization
- pytest -v -s tests/v1/distributed/test_dbo.py
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 pytest -v -s tests/distributed/test_weight_transfer.py
- pytest -v -s tests/distributed/test_packed_tensor.py
- label: Distributed Tests (4xA100-4xMI300) # TBD
timeout_in_minutes: 180
@@ -2195,26 +2201,6 @@ steps:
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_external_lb_dp.py
- DP_SIZE=2 pytest -v -s entrypoints/openai/test_multi_api_servers.py
- label: Distributed Tests (2xH100-2xMI300) # TBD
timeout_in_minutes: 180
mirror_hardwares: [amdexperimental, amdproduction, amdgfx942nightly, amdmi300]
agent_pool: mi300_2
num_gpus: 2
working_dir: "/vllm-workspace/"
source_file_dependencies:
- vllm/distributed/
- vllm/v1/distributed/
- vllm/model_executor/layers/fused_moe/
- tests/v1/distributed/test_dbo.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
commands:
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 examples/rl/rlhf_async_new_apis.py
- VLLM_LOGGING_LEVEL=DEBUG python3 examples/features/data_parallel/data_parallel_offline.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
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 pytest -v -s tests/distributed/test_weight_transfer.py
- pytest -v -s tests/distributed/test_packed_tensor.py
- label: Metrics, Tracing (2 GPUs) # TBD
timeout_in_minutes: 20
mirror_hardwares: [amdexperimental, amdproduction, amdgfx942nightly, amdmi300]
.buildkite/test_areas/cuda.yaml
+2 -2
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@@ -2,8 +2,8 @@ group: CUDA
depends_on:
- image-build
steps:
- label: Platform Tests (CUDA)
key: platform-tests-cuda
- label: Platform Tests
key: platform-tests
timeout_in_minutes: 15
device: h200_18gb
source_file_dependencies:
.buildkite/test_areas/distributed.yaml
+7 -7
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@@ -174,8 +174,8 @@ steps:
# test multi-node TP with multiproc executor (simulated on single node)
- pytest -v -s distributed/test_multiproc_executor.py::test_multiproc_executor_multi_node
- label: Distributed Tests (8 GPUs)(H100)
key: distributed-tests-8-gpus-h100
- label: Distributed Tests (8xH100)
key: distributed-tests-8xh100
timeout_in_minutes: 10
device: h100
num_devices: 8
@@ -195,8 +195,8 @@ steps:
# test with torchrun tp=2 and dp=4 with ep
- torchrun --nproc-per-node=8 ../examples/features/torchrun/torchrun_dp_example_offline.py --tp-size=2 --pp-size=1 --dp-size=4 --enable-ep
- label: Distributed Tests (4 GPUs)(A100)
key: distributed-tests-4-gpus-a100
- label: Distributed Tests (4xA100)
key: distributed-tests-4xa100
device: a100
optional: true
num_devices: 4
@@ -211,7 +211,7 @@ steps:
- pytest -v -s -x lora/test_mixtral.py
- label: Distributed Tests (2xH100-2xMI300)
key: distributed-tests-2-gpus-h100
key: distributed-tests-2xh100-2xmi300
timeout_in_minutes: 15
device: h100
optional: true
@@ -237,8 +237,8 @@ steps:
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 pytest -v -s tests/distributed/test_weight_transfer.py
- pytest -v -s tests/distributed/test_packed_tensor.py
- label: Distributed Tests (2 GPUs)(B200)
key: distributed-tests-2-gpus-b200
- label: Distributed Tests (2xB200)
key: distributed-tests-2xb200
device: b200-k8s
optional: true
working_dir: "/vllm-workspace/"
.buildkite/test_areas/e2e_integration.yaml
+6 -6
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@@ -2,8 +2,8 @@ group: E2E Integration
depends_on:
- image-build
steps:
- label: DeepSeek V2-Lite Sync EPLB Accuracy
key: deepseek-v2-lite-sync-eplb-accuracy
- label: DeepSeek V2-Lite Sync EPLB Accuracy (4xH100)
key: deepseek-v2-lite-sync-eplb-accuracy-4xh100
timeout_in_minutes: 60
device: h100
optional: true
@@ -12,8 +12,8 @@ steps:
commands:
- bash .buildkite/scripts/scheduled_integration_test/deepseek_v2_lite_ep_eplb.sh 0.25 200 8010
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (4xH100)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-4xh100
timeout_in_minutes: 60
device: h100
optional: true
@@ -22,8 +22,8 @@ steps:
commands:
- bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (B200)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-b200
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (2xB200)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-2xb200
timeout_in_minutes: 60
device: b200-k8s
optional: true
.buildkite/test_areas/kernels.yaml
+4 -4
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@@ -274,8 +274,8 @@ steps:
- pytest -v -s kernels/helion/
- label: Kernels FP8 MoE Test (1 H100)
key: kernels-fp8-moe-test-1-h100
- label: Kernels FP8 MoE Test (1xH100)
key: kernels-fp8-moe-test-1xh100
timeout_in_minutes: 90
device: h100
num_devices: 1
@@ -291,8 +291,8 @@ steps:
- 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)
key: kernels-fp8-moe-test-2-h100s
- label: Kernels FP8 MoE Test (2xH100)
key: kernels-fp8-moe-test-2xh100
timeout_in_minutes: 90
device: h100
num_devices: 2
.buildkite/test_areas/lm_eval.yaml
+16 -15
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@@ -28,7 +28,8 @@ steps:
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
# - label: LM Eval Large Models (4 GPUs)(A100)
# - label: LM Eval Large Models (4xA100)
# key: lm-eval-large-models-4xa100
# device: a100
# optional: true
# num_devices: 4
@@ -40,8 +41,8 @@ steps:
# - 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)
key: lm-eval-large-models-4-gpus-h100
- label: LM Eval Large Models (4xH100)
key: lm-eval-large-models-4xh100
device: h100
optional: true
num_devices: 4
@@ -53,8 +54,8 @@ steps:
- 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)
key: lm-eval-small-models-b200
- label: LM Eval Small Models (2xB200)
key: lm-eval-small-models-2xb200
timeout_in_minutes: 120
device: b200-k8s
optional: true
@@ -64,8 +65,8 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell.txt
- label: LM Eval Large Models (B200, EP)
key: lm-eval-large-models-b200-ep
- label: LM Eval Large Models EP (2xB200)
key: lm-eval-large-models-ep-2xb200
timeout_in_minutes: 120
device: b200-k8s
optional: true
@@ -76,8 +77,8 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell-ep.txt
- label: LM Eval Qwen3.5 Models (B200)
key: lm-eval-qwen3-5-models-b200
- label: LM Eval Qwen3.5 Models (2xB200)
key: lm-eval-qwen3-5-models-2xb200
timeout_in_minutes: 120
device: b200-k8s
optional: true
@@ -93,8 +94,8 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-qwen35-blackwell.txt
- label: LM Eval Large Models (H200)
key: lm-eval-large-models-h200
- label: LM Eval Large Models (8xH200)
key: lm-eval-large-models-8xh200
timeout_in_minutes: 60
device: h200
optional: true
@@ -192,8 +193,8 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/models-turboquant.txt
- label: GPQA Eval (GPT-OSS) (H100)
key: gpqa-eval-gpt-oss-h100
- label: GPQA Eval (GPT-OSS) (2xH100)
key: gpqa-eval-gpt-oss-2xh100
timeout_in_minutes: 120
device: h100
optional: true
@@ -206,8 +207,8 @@ steps:
- 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)
key: gpqa-eval-gpt-oss-b200
- label: GPQA Eval (GPT-OSS) (2xB200)
key: gpqa-eval-gpt-oss-2xb200
timeout_in_minutes: 120
device: b200-k8s
optional: true