[CI] Shard quantization, pooling, multimodal APIs, core kernels and PCP eval automatically (#61477)

Signed-off-by: Kevin Luu <51931015+khluu@users.noreply.github.com>
Co-authored-by: Codex <noreply@openai.com>
This commit is contained in:
Kevin H. Luu
2026-10-13 16:15:30 -07:00
committed by GitHub
co-authored by Codex
parent 0da66a6e46
commit 6a03954b45
6 changed files with 20 additions and 9 deletions
+1
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@@ -215,6 +215,7 @@ steps:
- label: ":nvidia: (H200 MIG 35GB) Entrypoints Integration (Multimodal)"
device: h200_35gb
key: entrypoints-integration-multimodal
automatic_shard: true
timeout_in_minutes: 45
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
+4 -3
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@@ -30,9 +30,10 @@ steps:
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
- label: ":nvidia: (H200 MIG 35GB) Core Operation Kernels Shard %N"
- label: ":nvidia: (H200 MIG 35GB) Core Operation Kernels"
device: h200_35gb
key: kernels-core-operation-test
automatic_shard: true
timeout_in_minutes: 120
source_file_dependencies:
- csrc/
@@ -40,10 +41,10 @@ steps:
- tests/kernels/test_concat_mla_q.py
- tests/kernels/test_fused_qk_norm_rope_gate.py
commands:
- pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py kernels/test_concat_mla_q.py kernels/test_fused_qk_norm_rope_gate.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 3
- pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py kernels/test_concat_mla_q.py kernels/test_fused_qk_norm_rope_gate.py
mirror:
amd:
parallelism: 3
label: ":amd: (MI300) Core Operation Kernels Shard %N"
dind: false
device: mi300_1
+1
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@@ -236,6 +236,7 @@ steps:
- label: ":nvidia: (B200) LM Eval PCP"
key: lm-eval-pcp-4xb200
automatic_shard: true
timeout_in_minutes: 360
device: b200-k8s
num_devices: 4
+6 -3
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@@ -199,20 +199,23 @@ steps:
- vllm/platforms/rocm.py
- tests/models/language/generation_ppl_test
- label: ":nvidia: (H200 MIG 35GB) Language Models (Extended Pooling) Shard %N"
- label: ":nvidia: (H200 MIG 35GB) Language Models (Extended Pooling)"
device: h200_35gb
key: language-models-test-extended-pooling
automatic_shard: true
timeout_in_minutes: 120
parallelism: 4
optional: true
source_file_dependencies:
- vllm/
- "!vllm/distributed/kv_transfer/"
- tests/models/language/pooling
commands:
- pytest -v -s models/language/pooling -m 'not core_model' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
- pytest -v -s models/language/pooling -m 'not core_model'
mirror:
amd:
parallelism: 4
commands:
- "pytest -v -s models/language/pooling -m 'not core_model' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB"
label: ":amd: (MI300) Language Models (Extended Pooling) Shard %N"
dind: false
device: mi300_1
+4 -3
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@@ -2,11 +2,11 @@ group: Quantization
depends_on:
- image-build
steps:
- label: ":nvidia: (H200 MIG 35GB) Quantization Shard %N"
- label: ":nvidia: (H200 MIG 35GB) Quantization"
device: h200_35gb
key: quantization
automatic_shard: true
timeout_in_minutes: 40
parallelism: 4
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
@@ -18,9 +18,10 @@ steps:
- uv pip install --system conch-triton-kernels
# The SM90-only checkpoint currently contains a removed weight_chan_scale
# parameter. It was not exercised by the previous L4 job.
- VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py --ignore quantization/test_rocm_moe.py -k 'not test_compressed_tensors_w4a8_fp8' --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
- VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py --ignore quantization/test_rocm_moe.py -k 'not test_compressed_tensors_w4a8_fp8'
mirror:
amd:
parallelism: 4
label: ":amd: (MI300) Quantization Shard %N"
dind: false
device: mi300_1