Sweep API
vessl.read_sweep(
sweep_name: str, **kwargs
)
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
vessl.read_sweep(
sweep_name="pitch-lord",
)
vessl.list_sweeps(
**kwargs
)
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
vessl.list_sweeps()
vessl.create_sweep(
name: str, objective: OrmSweepObjective, max_experiment_count: int,
parallel_experiment_count: int, max_failed_experiment_count: int,
algorithm: str, parameters: List[OrmParameter], cluster_name: str,
start_command: str, kernel_resource_spec_name: str = None,
processor_type: str = None, cpu_limit: float = None, memory_limit: float = None,
gpu_type: str = None, gpu_limit: int = None, kernel_image_url: str = None, *,
early_stopping_name: str = None, early_stopping_settings: List[Tuple[str,
str]] = None, message: str = None, hyperparameters: List[Tuple[str, str]] = None,
dataset_mounts: List[str] = None, git_ref_mounts: List[str] = None,
git_diff_mount: str = None, archive_file_mount: str = None,
root_volume_size: str = None, working_dir: str = None,
output_dir: str = MOUNT_PATH_OUTPUT, **kwargs
)
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
name
(str) : Nameobjective
(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
sweep_objective = vessl.SweepObjective(
type="maximize",
goal="0.99",
metric="val_accuracy",
)
parameters = [
vessl.SweepParameter(
name="optimizer",
type="categorical",
range=vessl.SweepParameterRange(
list=["adam", "sgd", "adadelta"]
)
),
vessl.SweepParameter(
name="batch_size",
type="int",
range=vessl.SweepParameterRange(
max="256",
min="64",
step="8",
)
)
]
vessl.create_sweep(
name="example-sweep-name",
objective=sweep_objective,
max_experiment_count=4,
parallel_experiment_count=2,
max_failed_experiment_count=2,
algorithm="random",
parameters=parameters,
dataset_mounts=[/input:mnist],
cluster_name="aws-apne2-prod1",
kernel_resource_spec_name="v1.cpu-4.mem-13",
kernel_image_url="public.ecr.aws/vessl/kernels:py36.full-cpu",
start_command="pip install requirements.txt && python main.py",
)
vessl.terminate_sweep(
sweep_name: str, **kwargs
)
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
vessl.terminate_sweep(
sweep_name="pitch-lord",
)
vessl.list_sweep_logs(
sweep_name: str, tail: int = 200, **kwargs
)
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
vessl.list_sweep_logs(
sweep_name="pitch-lord",
)
vessl.get_best_sweep_experiment(
sweep_name: str, **kwargs
)
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
vessl.get_best_sweep_experiment(
sweep_name="pitch-lord",
)
Last modified 2mo ago