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[Build] Temporarily Disable Kernels and LoRA tests (#6961)

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Simon Mo 2024-07-30 14:59:48 -07:00 committed by GitHub
parent 6ca8031e71
commit 40c27a7cbb
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1 changed files with 19 additions and 19 deletions
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38
.buildkite/test-pipeline.yaml
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@ -155,12 +155,12 @@ steps:
- pytest -v -s test_inputs.py
- pytest -v -s multimodal
- label: Kernels Test %N
#mirror_hardwares: [amd]
commands:
- pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.0.8/flashinfer-0.0.8+cu121torch2.3-cp310-cp310-linux_x86_64.whl
- pytest -v -s kernels --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 4
# - label: Kernels Test %N
# #mirror_hardwares: [amd]
# commands:
# - pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.0.8/flashinfer-0.0.8+cu121torch2.3-cp310-cp310-linux_x86_64.whl
# - pytest -v -s kernels --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
# parallelism: 4
- label: Models Test
#mirror_hardwares: [amd]
@ -202,20 +202,20 @@ steps:
- export VLLM_ATTENTION_BACKEND=XFORMERS
- pytest -v -s spec_decode
- label: LoRA Test %N
#mirror_hardwares: [amd]
command: pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_long_context.py
parallelism: 4
# - label: LoRA Test %N
# #mirror_hardwares: [amd]
# command: pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_long_context.py
# parallelism: 4
- label: LoRA Long Context (Distributed)
#mirror_hardwares: [amd]
num_gpus: 4
# This test runs llama 13B, so it is required to run on 4 GPUs.
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
- pytest -v -s -x lora/test_long_context.py
# - label: LoRA Long Context (Distributed)
# #mirror_hardwares: [amd]
# num_gpus: 4
# # This test runs llama 13B, so it is required to run on 4 GPUs.
# 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
# - pytest -v -s -x lora/test_long_context.py
- label: Tensorizer Test
#mirror_hardwares: [amd]