Run operations
MLFlowClient.createrun — Functioncreaterun(instance::MLFlow, experiment_id::String;
run_name::Union{String, Missing}=missing,
start_time::Union{Int64, Missing}=missing,
tags::Union{Dict{<:Any}, Array{<:Any}}=[])Create a new Run within an Experiment. A Run is usually a single execution of a machine learning or data ETL pipeline.
Arguments
instance:MLFlowconfiguration.experiment_id: ID of the associatedExperiment.run_name: Name of theRun.start_time: Unix timestamp in milliseconds of when theRunstarted.tags: Additional metadata forRun.
Returns
An instance of type Run.
MLFlowClient.deleterun — Functiondeleterun(instance::MLFlow, run_id::String)
deleterun(instance::MLFlow, run::Run)Mark a Run for deletion.
Arguments
Returns
true if successful. Otherwise, raises exception.
MLFlowClient.restorerun — Functionrestorerun(instance::MLFlow, run_id::String)
restorerun(instance::MLFlow, run::Run)Restore a deleted Run.
Arguments
Returns
true if successful. Otherwise, raises exception.
MLFlowClient.getrun — Functiongetrun(instance::MLFlow, run_id::String)Get metadata, metrics, params, and tags for a Run. In the case where multiple metrics with the same key are logged for a Run, return only the value with the latest timestamp. If there are multiple values with the latest timestamp, return the maximum of these values.
Arguments
Returns
An instance of type Run.
MLFlowClient.setruntag — Functionsetruntag(instance::MLFlow, run_id::String, key::String, value::String)
setruntag(instance::MLFlow, run::Run, key::String, value::String)
setruntag(instance::MLFlow, run::Run, tag::Tag)Arguments
instance:MLFlowconfiguration.run_id: ID of theRununder which to log theTag.key: Name of theTag.value: String value of theTagbeing logged.
Returns
true if successful. Otherwise, raises exception.
MLFlowClient.deleteruntag — Functiondeleteruntag(instance::MLFlow, run_id::String, key::String)
deleteruntag(instance::MLFlow, run::Run, key::String)
deleteruntag(instance::MLFlow, run::Run, tag::Tag)Arguments
instance:MLFlowconfiguration.run_id: ID of theRunthat theTagwas logged under.key: Name of theTag.
Returns
true if successful. Otherwise, raises exception.
MLFlowClient.searchruns — Functionsearchruns(instance::MLFlow; experiment_ids::Array{String}=String[], filter::String="",
run_view_type::ViewType=ACTIVE_ONLY, max_results::Int=1000,
order_by::Array{String}=String[], page_token::String="")Search for runs that satisfy expressions. Search expressions can use Metric and Param keys.
Arguments
instance:MLFlowconfiguration.experiment_ids: List ofExperimentIDs to search over.filter: A filter expression over params, metrics, and tags, that allows returning a subset of runs. See MLFlow documentation.run_view_type: Whether to display only active, only deleted, or all runs. Defaults to only active runs.max_results: Maximum number of runs desired.order_by: List of columns to be ordered by, including attributes, params, metrics, and tags with an optional “DESC” or “ASC” annotation, where “ASC” is the default.page_token: Token indicating the page of runs to fetch.
Returns
- Vector of
Runthat were found in the specified experiments. - The next page token if there are more results.
MLFlowClient.updaterun — Functionupdaterun(instance::MLFlow, run_id::String; status::Union{RunStatus, Missing}=missing,
end_time::Union{Int64, Missing}=missing, run_name::Union{String, Missing}=missing)
updaterun(instance::MLFlow, run::Run; status::Union{RunStatus, Missing}=missing,
end_time::Union{Int64, Missing}=missing, run_name::Union{String, Missing}=missing)Update Run metadata.
Arguments
instance:MLFlowconfiguration.run_id: ID of theRunto update.status: Updated status of theRun.end_time: Unix timestamp in milliseconds of when theRunended.run_name: Updated name of theRun.
Returns
- An instance of type
RunInfowith the updated metadata.