group: Engine
depends_on: 
  - image-build
steps:
- label: Engine
  timeout_in_minutes: 15
  source_file_dependencies:
  - vllm/
  - tests/engine
  - tests/test_sequence
  - tests/test_config
  - tests/test_logger
  - tests/test_vllm_port
  commands:
  - pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py

- label: V1 e2e + engine (1 GPU)
  timeout_in_minutes: 45
  source_file_dependencies:
    - vllm/
    - tests/v1
  commands:
    # TODO: accuracy does not match, whether setting
    # VLLM_USE_FLASHINFER_SAMPLER or not on H100.
    - pytest -v -s v1/e2e
    # Run this test standalone for now;
    # need to untangle use (implicit) use of spawn/fork across the tests.
    - pytest -v -s v1/engine/test_preprocess_error_handling.py
    # Run the rest of v1/engine tests
    - pytest -v -s v1/engine --ignore v1/engine/test_preprocess_error_handling.py
  mirror:
    amd:
      device: mi325_1
      depends_on:
      - image-build-amd
      commands:
      - pytest -v -s v1/e2e
      - pytest -v -s v1/engine

- label: V1 e2e (2 GPUs)
  timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
  optional: true
  num_devices: 2
  source_file_dependencies:
    - vllm/
    - tests/v1/e2e
  commands:
    # Only run tests that need exactly 2 GPUs
    - pytest -v -s v1/e2e/test_spec_decode.py -k "tensor_parallelism"
  mirror:
    amd:
      device: mi325_2
      depends_on:
      - image-build-amd

- label: V1 e2e (4 GPUs)
  timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
  optional: true
  num_devices: 4
  source_file_dependencies:
    - vllm/
    - tests/v1/e2e
  commands:
    # Only run tests that need 4 GPUs
    - pytest -v -s v1/e2e/test_spec_decode.py -k "eagle_correctness_heavy"
  mirror:
    amd:
      device: mi325_4
      depends_on:
      - image-build-amd