Chakra Replay#
Chakra Replay workload (test_template_name is ChakraReplay) replays execution traces from the Chakra execution trace format for performance analysis and debugging.
Usage Examples#
Test TOML example:
name = "my_chakra_test"
description = "Example Chakra replay test"
test_template_name = "ChakraReplay"
[cmd_args]
trace_path = "/path/to/trace.et"
Test Scenario example:
name = "chakra-replay-test"
[[Tests]]
id = "chakra.1"
num_nodes = 1
time_limit = "00:10:00"
test_name = "my_chakra_test"
Test-in-Scenario example:
name = "chakra-replay-test"
[[Tests]]
id = "chakra.1"
num_nodes = 1
time_limit = "00:10:00"
name = "my_chakra_test"
description = "Example Chakra replay test"
test_template_name = "ChakraReplay"
[Tests.cmd_args]
trace_path = "/path/to/trace.et"
API Documentation#
Command Arguments#
Test Definition#
- class cloudai.workloads.chakra_replay.chakra_replay.ChakraReplayTestDefinition(*, name: str, description: str, test_template_name: str, cmd_args: ~cloudai.workloads.chakra_replay.chakra_replay.ChakraReplayCmdArgs, dse_excluded_args: list[str] = <factory>, extra_env_vars: dict[str, str | ~typing.List[str]] = {}, extra_cmd_args: dict[str, str] = {}, extra_container_mounts: list[str] = [], git_repos: list[~cloudai._core.installables.git_repo.GitRepo] = [], nsys: ~cloudai.models.workload.NsysConfiguration | None = None, predictor: ~cloudai.models.workload.PredictorConfig | None = None, agent: str = 'grid_search', agent_steps: int = 1, agent_metrics: list[str] = ['default'], agent_reward_function: str = 'inverse', agent_config: dict[str, ~typing.Any] | None = None)[source]#
Bases:
TestDefinitionTest object for ChakraReplay.
- is_dse_excluded_arg(path: str) bool#
Return whether a dot-separated cmd_args path should be ignored by DSE.