Run#
Run information representation |
|
Run view type |
- class mlflow_rest_client.run.Run(**data)#
Run representation
Examples
run_info = RunInfo(id="some_id") run_data = RunData(params=..., metrics=..., tags=...) run = Run(run_info, run_data)
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- class mlflow_rest_client.run.RunStage(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)#
Run stage
- ACTIVE = 'active'#
Run is active
- DELETED = 'deleted'#
Run was deleted
- class mlflow_rest_client.run.RunStatus(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)#
Run status
- FAILED = 'FAILED'#
Run is failed
- FINISHED = 'FINISHED'#
Run was finished successfully
- KILLED = 'KILLED'#
Run was killed
- SCHEDULED = 'SCHEDULED'#
Run is scheduled for run
- STARTED = 'RUNNING'#
Run is running or created
- class mlflow_rest_client.run.RunInfo(**data)#
Run information representation
- Parameters:
- idstr
Run ID
- experiment_idint, optional
Experiment ID
- status
str
orRunStatus
, optional Run status
- stage
str
orRunStage
, optional Run stage
- start_time
int
(UNIX timestamp) ordatetime.datetime
, optional Run start time
- end_time
int
(UNIX timestamp) ordatetime.datetime
, optional Run end time
- artifact_uristr, optional
Artifact URL
Examples
run_info = RunInfo("some_id")
- Attributes:
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- class mlflow_rest_client.run.RunViewType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)#
Run view type
- ACTIVE = 'ACTIVE_ONLY'#
Show only active runs
- ALL = 'ALL'#
Show all runs
- DELETED = 'DELETED_ONLY'#
Show only deleted runs
- class mlflow_rest_client.run.RunData(**data)#
Run data representation
- Parameters:
- params
dict
orlist
ofdict
, optional Params list
- metrics
dict
orlist
ofdict
, optional Metrics list
- tags
dict
orlist
ofdict
, optional Run tags list
- params
Examples
param = Param(key="some.param", value="some_value") metric = Metric(name="some.metric", value=1.23) tag = RunTag(key="some.tag", value="some.val") run_data = RunData(params=[param], metrics=[metric], tags=[tag])
- Attributes:
- params
ParamList
Params list
- metrics
MetricList
Metrics list
- tags
RunTagList
Run tags list
- params
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- class mlflow_rest_client.run.Param(**data)#
Bases:
Tag
Run parameter
- Parameters:
- keystr
Param name
- valuestr
Param value
- Attributes:
- keystr
Param name
- valuestr
Param value
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- class mlflow_rest_client.run.Metric(**data)#
Run metric representation
- Parameters:
- namestr
Metric name
- valuefloat, optional
Metric value
- stepint, optional
Metric step
- timestamp
int
(UNIX timestamp) ordatetime.datetime
, optional Metric timestamp
Examples
metric = Metric(name="some.metric") metric = Metric(name="some.metric", value=1.23) metric = Metric(name="some.metric", value=1.23, step=2) metric = Metric( name="some.metric", value=1.23, step=2, timestamp=datetime.datetime.now() )
- Attributes:
- namestr
Metric name
- valuefloat
Metric value
- stepint
Metric step
- timestamp
datetime.datetime
Metric timestamp
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- class mlflow_rest_client.run.RunTag(**data)#
Bases:
Tag
Run tag
- Parameters:
- keystr
Tag name
- valuestr
Tag value
Examples
tag = RunTag(key="some.tag", value="some.val")
- Attributes:
- keystr
Tag name
- valuestr
Tag value
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.