[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:
@@ -215,6 +215,7 @@ steps:
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- label: ":nvidia: (H200 MIG 35GB) Entrypoints Integration (Multimodal)"
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device: h200_35gb
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key: entrypoints-integration-multimodal
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automatic_shard: true
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timeout_in_minutes: 45
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working_dir: "/vllm-workspace/tests"
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source_file_dependencies:
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@@ -30,9 +30,10 @@ steps:
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- vllm/_aiter_ops.py
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- vllm/platforms/rocm.py
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- label: ":nvidia: (H200 MIG 35GB) Core Operation Kernels Shard %N"
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- label: ":nvidia: (H200 MIG 35GB) Core Operation Kernels"
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device: h200_35gb
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key: kernels-core-operation-test
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automatic_shard: true
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timeout_in_minutes: 120
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source_file_dependencies:
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- csrc/
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@@ -40,10 +41,10 @@ steps:
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- tests/kernels/test_concat_mla_q.py
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- tests/kernels/test_fused_qk_norm_rope_gate.py
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commands:
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- 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
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parallelism: 3
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- 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
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mirror:
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amd:
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parallelism: 3
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label: ":amd: (MI300) Core Operation Kernels Shard %N"
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dind: false
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device: mi300_1
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@@ -236,6 +236,7 @@ steps:
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- label: ":nvidia: (B200) LM Eval PCP"
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key: lm-eval-pcp-4xb200
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automatic_shard: true
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timeout_in_minutes: 360
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device: b200-k8s
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num_devices: 4
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@@ -199,20 +199,23 @@ steps:
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- vllm/platforms/rocm.py
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- tests/models/language/generation_ppl_test
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- label: ":nvidia: (H200 MIG 35GB) Language Models (Extended Pooling) Shard %N"
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- label: ":nvidia: (H200 MIG 35GB) Language Models (Extended Pooling)"
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device: h200_35gb
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key: language-models-test-extended-pooling
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automatic_shard: true
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timeout_in_minutes: 120
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parallelism: 4
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optional: true
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source_file_dependencies:
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- vllm/
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- "!vllm/distributed/kv_transfer/"
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- tests/models/language/pooling
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commands:
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- pytest -v -s models/language/pooling -m 'not core_model' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
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- pytest -v -s models/language/pooling -m 'not core_model'
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mirror:
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amd:
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parallelism: 4
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commands:
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- "pytest -v -s models/language/pooling -m 'not core_model' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB"
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label: ":amd: (MI300) Language Models (Extended Pooling) Shard %N"
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dind: false
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device: mi300_1
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@@ -2,11 +2,11 @@ group: Quantization
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depends_on:
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- image-build
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steps:
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- label: ":nvidia: (H200 MIG 35GB) Quantization Shard %N"
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- label: ":nvidia: (H200 MIG 35GB) Quantization"
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device: h200_35gb
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key: quantization
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automatic_shard: true
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timeout_in_minutes: 40
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parallelism: 4
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source_file_dependencies:
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- csrc/
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- vllm/model_executor/layers/quantization
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@@ -18,9 +18,10 @@ steps:
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- uv pip install --system conch-triton-kernels
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# The SM90-only checkpoint currently contains a removed weight_chan_scale
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# parameter. It was not exercised by the previous L4 job.
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- 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
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- 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'
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mirror:
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amd:
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parallelism: 4
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label: ":amd: (MI300) Quantization Shard %N"
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dind: false
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device: mi300_1
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