GETTING STARTED
API REFERENCE
TROUBLESHOOTING
Sweep API
read_sweep
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vessl.read_sweep(
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sweep_name: str, **kwargs
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)
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Read sweep in the default organization/project. If you want to override the default organization/project, then pass
organization_name or project_name as **kwargs.Args
sweep_name(str) : Sweep name.
Example
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vessl.read_sweep(
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sweep_name="pitch-lord",
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)
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list_sweeps
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vessl.list_sweeps(
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**kwargs
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)
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List sweeps in the default organization/project. If you want to override the default organization/project, then pass
organization_name or project_name as **kwargs.Example
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vessl.list_sweeps()
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create_sweep
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vessl.create_sweep(
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objective: OrmSweepObjective, max_experiment_count: int,
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parallel_experiment_count: int, max_failed_experiment_count: int,
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algorithm: str, parameters: List[OrmParameter], cluster_name: str,
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start_command: str, kernel_resource_spec_name: str = None,
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processor_type: str = None, cpu_limit: float = None, memory_limit: float = None,
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gpu_type: str = None, gpu_limit: int = None, kernel_image_url: str = None, *,
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early_stopping_name: str = None, early_stopping_settings: List[Tuple[str,
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str]] = None, message: str = None, hyperparameters: List[Tuple[str, str]] = None,
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dataset_mounts: List[str] = None, git_ref_mounts: List[str] = None,
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git_diff_mount: str = None, archive_file_mount: str = None,
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root_volume_size: str = None, working_dir: str = None,
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output_dir: str = MOUNT_PATH_OUTPUT, **kwargs
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)
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Create sweep in the default organization/project. If you want to override the default organization/project, then pass
organization_name or project_name as **kwargs. Pass use_git_diff=True if you want to run experiment with uncommitted changes and pass use_git_diff_untracked=True if you want to run untracked changes(only valid if use_git_diff is set).Args
objective(OrmSweepObjective) : A sweep objective including goal, metric, and type.max_experiment_count(int) : The maximum number of experiments to run.parallel_experiment_count(int) : The number of experiments to run in parallel.max_failed_experiment_count(int) : The maximum number of experiments to allow to fail.algorithm(str) : Parameter suggestion algorithm.grid,random, orbayesian.parameters(List[OrmParameter]) : A list of parameters to search.cluster_name(str) : Cluster name(must be specified before other options).start_command(str) : Start command to execute in experiment container.kernel_resource_spec_name(str) : Resource type to run an experiment (for managed cluster only). Defaults to None.cpu_limit(float) : Number of vCPUs (for custom cluster only). Defaults to None.memory_limit(str) : Memory limit in GiB (for custom cluster only). Defaults to None.gpu_type(str) : GPU type (for custom cluster only). Defaults to None.gpu_limit(int) : Number of GPU cores (for custom cluster only). Defaults to None.kernel_image_url(str) : Kernel docker image URL. Defaults to None.early_stopping_name(str) : Early stopping algorithm name. Defaults to None.early_stopping_settings(List[Tuple[str, str]]) : Early stopping algorithm settings. Defaults to None.message(str) : Message. Defaults to None.hyperparameters(List[str]) : A list of hyperparameters. Defaults to None.dataset_mounts(List[str]) : A list of dataset mounts. Defaults to None.git_ref_mounts(List[str]) : A list of git repository mounts. Defaults to None.git_diff_mount(str) : Git diff mounts. Defaults to None.archive_file_mount(str) : Local archive file mounts. Defaults to None.root_volume_size(str) : Root volume size. Defaults to None.working_dir(str) : Working directory path. Defaults to None.output_dir(str) : Output directory path. Defaults to "/output/". processor_type(str) cpu or gpu (for custom cluster only). Defaults to None.
Example
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sweep_objective = vessl.SweepObjective(
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type="maximize",
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goal="0.99",
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metric="val_accuracy",
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)
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parameters = [
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vessl.SweepParameter(
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name="optimizer",
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type="categorical",
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range=vessl.SweepParameterRange(
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list=["adam", "sgd", "adadelta"]
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)
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),
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vessl.SweepParameter(
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name="batch_size",
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type="int",
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range=vessl.SweepParameterRange(
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max="256",
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min="64",
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step="8",
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)
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)
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]
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vessl.create_sweep(
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objective=sweep_objective,
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max_experiment_count=4,
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parallel_experiment_count=2,
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max_failed_experiment_count=2,
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algorithm="random",
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parameters=parameters,
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dataset_mounts=[/input:mnist],
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cluster_name="aws-apne2-prod1",
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kernel_resource_spec_name="v1.cpu-4.mem-13",
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kernel_image_url="public.ecr.aws/vessl/kernels:py36.full-cpu",
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start_command="pip install requirements.txt && python main.py",
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)
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terminate_sweep
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vessl.terminate_sweep(
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sweep_name: str, **kwargs
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)
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Terminate sweep in the default organization/project. If you want to override the default organization/project, then pass
organization_name or project_name as **kwargs.Args
sweep_name(str) : Sweep name.
Example
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vessl.terminate_sweep(
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sweep_name="pitch-lord",
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)
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list_sweep_logs
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vessl.list_sweep_logs(
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sweep_name: str, tail: int = 200, **kwargs
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)
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List sweep logs in the default organization/project. If you want to override the default organization/project, then pass
organization_name or project_name as **kwargs.Args
sweep_name(str) : Sweep name.tail(int) : The number of lines to display from the end. Display all if -1. Defaults to 200.
Example
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vessl.list_sweep_logs(
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sweep_name="pitch-lord",
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)
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get_best_sweep_experiment
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vessl.get_best_sweep_experiment(
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sweep_name: str, **kwargs
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)
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Read sweep and return the best experiment info in the default organization/project. If you want to override the default organization/project, then pass
organization_name or project_name as **kwargs.Args
sweep_name(str) : Sweep name.
Example
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vessl.get_best_sweep_experiment(
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sweep_name="pitch-lord",
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)
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Last modified 2mo ago