Documentation
¶
Index ¶
- type Client
- func (c *Client) CreateExperiment(ctx context.Context, req *CreateExperimentRequest, opts ...call.Option) (*CreateExperimentResponse, error)
- func (c *Client) CreateLoggedModel(ctx context.Context, req *CreateLoggedModelRequest, opts ...call.Option) (*CreateLoggedModelResponse, error)
- func (c *Client) CreateRun(ctx context.Context, req *CreateRunRequest, opts ...call.Option) (*CreateRunResponse, error)
- func (c *Client) DeleteExperiment(ctx context.Context, req *DeleteExperimentRequest, opts ...call.Option) (*DeleteExperimentResponse, error)
- func (c *Client) DeleteLoggedModel(ctx context.Context, req *DeleteLoggedModelRequest, opts ...call.Option) (*DeleteLoggedModelResponse, error)
- func (c *Client) DeleteLoggedModelTag(ctx context.Context, req *DeleteLoggedModelTagRequest, opts ...call.Option) (*DeleteLoggedModelTagResponse, error)
- func (c *Client) DeleteRun(ctx context.Context, req *DeleteRunRequest, opts ...call.Option) (*DeleteRunResponse, error)
- func (c *Client) DeleteRuns(ctx context.Context, req *DeleteRunsRequest, opts ...call.Option) (*DeleteRunsResponse, error)
- func (c *Client) DeleteTag(ctx context.Context, req *DeleteTagRequest, opts ...call.Option) (*DeleteTagResponse, error)
- func (c *Client) FinalizeLoggedModel(ctx context.Context, req *FinalizeLoggedModelRequest, opts ...call.Option) (*FinalizeLoggedModelResponse, error)
- func (c *Client) GetExperiment(ctx context.Context, req *GetExperimentRequest, opts ...call.Option) (*GetExperimentResponse, error)
- func (c *Client) GetExperimentByName(ctx context.Context, req *GetExperimentByNameRequest, opts ...call.Option) (*GetExperimentByNameResponse, error)
- func (c *Client) GetLoggedModel(ctx context.Context, req *GetLoggedModelRequest, opts ...call.Option) (*GetLoggedModelResponse, error)
- func (c *Client) GetRun(ctx context.Context, req *GetRunRequest, opts ...call.Option) (*GetRunResponse, error)
- func (c *Client) ListArtifacts(ctx context.Context, req *ListArtifactsRequest, opts ...call.Option) (*ListArtifactsResponse, error)
- func (c *Client) ListArtifactsIter(ctx context.Context, req *ListArtifactsRequest, opts ...call.Option) iter.Seq2[*FileInfo, error]
- func (c *Client) ListExperiments(ctx context.Context, req *ListExperimentsRequest, opts ...call.Option) (*ListExperimentsResponse, error)
- func (c *Client) ListExperimentsIter(ctx context.Context, req *ListExperimentsRequest, opts ...call.Option) iter.Seq2[*Experiment, error]
- func (c *Client) ListMetricHistory(ctx context.Context, req *ListMetricHistoryRequest, opts ...call.Option) (*GetMetricHistoryResponse, error)
- func (c *Client) ListMetricHistoryIter(ctx context.Context, req *ListMetricHistoryRequest, opts ...call.Option) iter.Seq2[*Metric, error]
- func (c *Client) LogBatch(ctx context.Context, req *LogBatchRequest, opts ...call.Option) (*LogBatchResponse, error)
- func (c *Client) LogInputs(ctx context.Context, req *LogInputsRequest, opts ...call.Option) (*LogInputsResponse, error)
- func (c *Client) LogLoggedModelParams(ctx context.Context, req *LogLoggedModelParamsRequest, opts ...call.Option) (*LogLoggedModelParamsResponse, error)
- func (c *Client) LogMetric(ctx context.Context, req *LogMetricRequest, opts ...call.Option) (*LogMetricResponse, error)
- func (c *Client) LogModel(ctx context.Context, req *LogModelRequest, opts ...call.Option) (*LogModelResponse, error)
- func (c *Client) LogOutputs(ctx context.Context, req *LogOutputsRequest, opts ...call.Option) (*LogOutputsResponse, error)
- func (c *Client) LogParam(ctx context.Context, req *LogParamRequest, opts ...call.Option) (*LogParamResponse, error)
- func (c *Client) RestoreExperiment(ctx context.Context, req *RestoreExperimentRequest, opts ...call.Option) (*RestoreExperimentResponse, error)
- func (c *Client) RestoreRun(ctx context.Context, req *RestoreRunRequest, opts ...call.Option) (*RestoreRunResponse, error)
- func (c *Client) RestoreRuns(ctx context.Context, req *RestoreRunsRequest, opts ...call.Option) (*RestoreRunsResponse, error)
- func (c *Client) SearchExperiments(ctx context.Context, req *SearchExperimentsRequest, opts ...call.Option) (*SearchExperimentsResponse, error)
- func (c *Client) SearchExperimentsIter(ctx context.Context, req *SearchExperimentsRequest, opts ...call.Option) iter.Seq2[*Experiment, error]
- func (c *Client) SearchLoggedModels(ctx context.Context, req *SearchLoggedModelsRequest, opts ...call.Option) (*SearchLoggedModelsResponse, error)
- func (c *Client) SearchRuns(ctx context.Context, req *SearchRunsRequest, opts ...call.Option) (*SearchRunsResponse, error)
- func (c *Client) SearchRunsIter(ctx context.Context, req *SearchRunsRequest, opts ...call.Option) iter.Seq2[*Run, error]
- func (c *Client) SetExperimentTag(ctx context.Context, req *SetExperimentTagRequest, opts ...call.Option) (*SetExperimentTagResponse, error)
- func (c *Client) SetLoggedModelTags(ctx context.Context, req *SetLoggedModelTagsRequest, opts ...call.Option) (*SetLoggedModelTagsResponse, error)
- func (c *Client) SetTag(ctx context.Context, req *SetTagRequest, opts ...call.Option) (*SetTagResponse, error)
- func (c *Client) UpdateExperiment(ctx context.Context, req *UpdateExperimentRequest, opts ...call.Option) (*UpdateExperimentResponse, error)
- func (c *Client) UpdateRun(ctx context.Context, req *UpdateRunRequest, opts ...call.Option) (*UpdateRunResponse, error)
- type CreateExperimentRequest
- type CreateExperimentResponse
- type CreateLoggedModelRequest
- type CreateLoggedModelResponse
- type CreateRunRequest
- type CreateRunResponse
- type Dataset
- type DatasetInput
- type DeleteExperimentRequest
- type DeleteExperimentResponse
- type DeleteLoggedModelRequest
- type DeleteLoggedModelResponse
- type DeleteLoggedModelTagRequest
- type DeleteLoggedModelTagResponse
- type DeleteRunRequest
- type DeleteRunResponse
- type DeleteRunsRequest
- type DeleteRunsResponse
- type DeleteTagRequest
- type DeleteTagResponse
- type Experiment
- type ExperimentTag
- type ExperimentTraceLocation
- type ExperimentTraceLocation_Location_UcTraceLocation
- type FileInfo
- type FinalizeLoggedModelRequest
- type FinalizeLoggedModelResponse
- type GetExperimentByNameRequest
- type GetExperimentByNameResponse
- type GetExperimentRequest
- type GetExperimentResponse
- type GetLoggedModelRequest
- type GetLoggedModelResponse
- type GetMetricHistoryResponse
- type GetRunRequest
- type GetRunResponse
- type InputTag
- type ListArtifactsRequest
- type ListArtifactsResponse
- type ListExperimentsRequest
- type ListExperimentsResponse
- type ListMetricHistoryRequest
- type LogBatchRequest
- type LogBatchResponse
- type LogInputsRequest
- type LogInputsResponse
- type LogLoggedModelParamsRequest
- type LogLoggedModelParamsResponse
- type LogMetricRequest
- type LogMetricResponse
- type LogModelRequest
- type LogModelResponse
- type LogOutputsRequest
- type LogOutputsResponse
- type LogParamRequest
- type LogParamResponse
- type LoggedModel
- type LoggedModelData
- type LoggedModelInfo
- type LoggedModelParameter
- type LoggedModelStatus
- type LoggedModelTag
- type Metric
- type ModelInput
- type ModelOutput
- type Param
- type RestoreExperimentRequest
- type RestoreExperimentResponse
- type RestoreRunRequest
- type RestoreRunResponse
- type RestoreRunsRequest
- type RestoreRunsResponse
- type Run
- type RunData
- type RunInfo
- type RunInputs
- type RunStatus
- type RunTag
- type SearchExperimentsRequest
- type SearchExperimentsResponse
- type SearchLoggedModelsRequest
- type SearchLoggedModelsRequest_Dataset
- type SearchLoggedModelsRequest_OrderBy
- type SearchLoggedModelsResponse
- type SearchRunsRequest
- type SearchRunsResponse
- type SetExperimentTagRequest
- type SetExperimentTagResponse
- type SetLoggedModelTagsRequest
- type SetLoggedModelTagsResponse
- type SetTagRequest
- type SetTagResponse
- type UcTraceLocation
- type UpdateExperimentRequest
- type UpdateExperimentResponse
- type UpdateRunRequest
- type UpdateRunResponse
- type ViewType
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
This section is empty.
Types ¶
type Client ¶
type Client struct {
// contains filtered or unexported fields
}
func (*Client) CreateExperiment ¶
func (c *Client) CreateExperiment(ctx context.Context, req *CreateExperimentRequest, opts ...call.Option) (*CreateExperimentResponse, error)
Creates an experiment with a name. Returns the ID of the newly created experiment. Validates that another experiment with the same name does not already exist and fails if another experiment with the same name already exists.
Throws `RESOURCE_ALREADY_EXISTS` if an experiment with the given name exists. Note: In some contexts, this error may be remapped to `ALREADY_EXISTS`. To be safe, clients should check for both error codes.
func (*Client) CreateLoggedModel ¶
func (c *Client) CreateLoggedModel(ctx context.Context, req *CreateLoggedModelRequest, opts ...call.Option) (*CreateLoggedModelResponse, error)
Create a logged model.
func (*Client) CreateRun ¶
func (c *Client) CreateRun(ctx context.Context, req *CreateRunRequest, opts ...call.Option) (*CreateRunResponse, error)
Creates a new run within an experiment. A run is usually a single execution of a machine learning or data ETL pipeline. MLflow uses runs to track the `mlflowParam`, `mlflowMetric`, and `mlflowRunTag` associated with a single execution.
func (*Client) DeleteExperiment ¶
func (c *Client) DeleteExperiment(ctx context.Context, req *DeleteExperimentRequest, opts ...call.Option) (*DeleteExperimentResponse, error)
Marks an experiment and associated metadata, runs, metrics, params, and tags for deletion. If the experiment uses FileStore, artifacts associated with the experiment are also deleted.
func (*Client) DeleteLoggedModel ¶
func (c *Client) DeleteLoggedModel(ctx context.Context, req *DeleteLoggedModelRequest, opts ...call.Option) (*DeleteLoggedModelResponse, error)
Delete a logged model.
func (*Client) DeleteLoggedModelTag ¶
func (c *Client) DeleteLoggedModelTag(ctx context.Context, req *DeleteLoggedModelTagRequest, opts ...call.Option) (*DeleteLoggedModelTagResponse, error)
Delete a tag on a logged model.
func (*Client) DeleteRun ¶
func (c *Client) DeleteRun(ctx context.Context, req *DeleteRunRequest, opts ...call.Option) (*DeleteRunResponse, error)
Marks a run for deletion.
func (*Client) DeleteRuns ¶
func (c *Client) DeleteRuns(ctx context.Context, req *DeleteRunsRequest, opts ...call.Option) (*DeleteRunsResponse, error)
Bulk delete runs in an experiment that were created prior to or at the specified timestamp. Deletes at most max_runs per request. To call this API from a Databricks Notebook in Python, you can use the client code snippet on
func (*Client) DeleteTag ¶
func (c *Client) DeleteTag(ctx context.Context, req *DeleteTagRequest, opts ...call.Option) (*DeleteTagResponse, error)
Deletes a tag on a run. Tags are run metadata that can be updated during a run and after a run completes.
func (*Client) FinalizeLoggedModel ¶
func (c *Client) FinalizeLoggedModel(ctx context.Context, req *FinalizeLoggedModelRequest, opts ...call.Option) (*FinalizeLoggedModelResponse, error)
Finalize a logged model.
func (*Client) GetExperiment ¶
func (c *Client) GetExperiment(ctx context.Context, req *GetExperimentRequest, opts ...call.Option) (*GetExperimentResponse, error)
Gets metadata for an experiment. This method works on deleted experiments.
func (*Client) GetExperimentByName ¶
func (c *Client) GetExperimentByName(ctx context.Context, req *GetExperimentByNameRequest, opts ...call.Option) (*GetExperimentByNameResponse, error)
Gets metadata for an experiment.
This endpoint will return deleted experiments, but prefers the active experiment if an active and deleted experiment share the same name. If multiple deleted experiments share the same name, the API will return one of them.
Throws `RESOURCE_DOES_NOT_EXIST` if no experiment with the specified name exists.
func (*Client) GetLoggedModel ¶
func (c *Client) GetLoggedModel(ctx context.Context, req *GetLoggedModelRequest, opts ...call.Option) (*GetLoggedModelResponse, error)
Get a logged model.
func (*Client) GetRun ¶
func (c *Client) GetRun(ctx context.Context, req *GetRunRequest, opts ...call.Option) (*GetRunResponse, error)
Gets the 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.
func (*Client) ListArtifacts ¶
func (c *Client) ListArtifacts(ctx context.Context, req *ListArtifactsRequest, opts ...call.Option) (*ListArtifactsResponse, error)
List artifacts for a run. Takes an optional `artifact_path` prefix which if specified, the response contains only artifacts with the specified prefix. A maximum of 1000 artifacts will be retrieved for UC Volumes. Please call `/api/2.0/fs/directories{directory_path}` for listing artifacts in UC Volumes, which supports pagination. See [List directory contents | Files API](/api/workspace/files/listdirectorycontents).
func (*Client) ListArtifactsIter ¶
func (c *Client) ListArtifactsIter(ctx context.Context, req *ListArtifactsRequest, opts ...call.Option) iter.Seq2[*FileInfo, error]
ListArtifactsIter returns an iterator that iterates over the results of ListArtifacts.
For example:
for item, err := range c.ListArtifactsIter(ctx, &ListArtifactsRequest{}) {
if err != nil {
return err
}
fmt.Println(item)
}
Options opts are passed to each ListArtifacts call made by the iterator under the hood.
Callers who need custom pagination logic should use ListArtifacts directly.
func (*Client) ListExperiments ¶
func (c *Client) ListExperiments(ctx context.Context, req *ListExperimentsRequest, opts ...call.Option) (*ListExperimentsResponse, error)
Gets a list of all experiments.
func (*Client) ListExperimentsIter ¶
func (c *Client) ListExperimentsIter(ctx context.Context, req *ListExperimentsRequest, opts ...call.Option) iter.Seq2[*Experiment, error]
ListExperimentsIter returns an iterator that iterates over the results of ListExperiments.
For example:
for item, err := range c.ListExperimentsIter(ctx, &ListExperimentsRequest{}) {
if err != nil {
return err
}
fmt.Println(item)
}
Options opts are passed to each ListExperiments call made by the iterator under the hood.
Callers who need custom pagination logic should use ListExperiments directly.
func (*Client) ListMetricHistory ¶
func (c *Client) ListMetricHistory(ctx context.Context, req *ListMetricHistoryRequest, opts ...call.Option) (*GetMetricHistoryResponse, error)
Gets a list of all values for the specified metric for a given run.
func (*Client) ListMetricHistoryIter ¶
func (c *Client) ListMetricHistoryIter(ctx context.Context, req *ListMetricHistoryRequest, opts ...call.Option) iter.Seq2[*Metric, error]
ListMetricHistoryIter returns an iterator that iterates over the results of ListMetricHistory.
For example:
for item, err := range c.ListMetricHistoryIter(ctx, &ListMetricHistoryRequest{}) {
if err != nil {
return err
}
fmt.Println(item)
}
Options opts are passed to each ListMetricHistory call made by the iterator under the hood.
Callers who need custom pagination logic should use ListMetricHistory directly.
func (*Client) LogBatch ¶
func (c *Client) LogBatch(ctx context.Context, req *LogBatchRequest, opts ...call.Option) (*LogBatchResponse, error)
Logs a batch of metrics, params, and tags for a run. If any data failed to be persisted, the server will respond with an error (non-200 status code).
In case of error (due to internal server error or an invalid request), partial data may be written.
You can write metrics, params, and tags in interleaving fashion, but within a given entity type are guaranteed to follow the order specified in the request body.
The overwrite behavior for metrics, params, and tags is as follows:
* Metrics: metric values are never overwritten. Logging a metric (key, value, timestamp) appends to the set of values for the metric with the provided key.
* Tags: tag values can be overwritten by successive writes to the same tag key. That is, if multiple tag values with the same key are provided in the same API request, the last-provided tag value is written. Logging the same tag (key, value) is permitted. Specifically, logging a tag is idempotent.
* Parameters: once written, param values cannot be changed (attempting to overwrite a param value will result in an error). However, logging the same param (key, value) is permitted. Specifically, logging a param is idempotent.
Request Limits ------------------------------- A single JSON-serialized API request may be up to 1 MB in size and contain:
* No more than 1000 metrics, params, and tags in total
* Up to 1000 metrics
* Up to 100 params
* Up to 100 tags
For example, a valid request might contain 900 metrics, 50 params, and 50 tags, but logging 900 metrics, 50 params, and 51 tags is invalid.
The following limits also apply to metric, param, and tag keys and values:
* Metric keys, param keys, and tag keys can be up to 250 characters in length
* Parameter and tag values can be up to 250 characters in length
func (*Client) LogInputs ¶
func (c *Client) LogInputs(ctx context.Context, req *LogInputsRequest, opts ...call.Option) (*LogInputsResponse, error)
Logs inputs, such as datasets and models, to an MLflow Run.
func (*Client) LogLoggedModelParams ¶
func (c *Client) LogLoggedModelParams(ctx context.Context, req *LogLoggedModelParamsRequest, opts ...call.Option) (*LogLoggedModelParamsResponse, error)
Logs params for a logged model. A param is a key-value pair (string key, string value). Examples include hyperparameters used for ML model training. A param can be logged only once for a logged model, and attempting to overwrite an existing param with a different value will result in an error
func (*Client) LogMetric ¶
func (c *Client) LogMetric(ctx context.Context, req *LogMetricRequest, opts ...call.Option) (*LogMetricResponse, error)
Log a metric for a run. A metric is a key-value pair (string key, float value) with an associated timestamp. Examples include the various metrics that represent ML model accuracy. A metric can be logged multiple times.
func (*Client) LogModel ¶
func (c *Client) LogModel(ctx context.Context, req *LogModelRequest, opts ...call.Option) (*LogModelResponse, error)
**Note:** the [Create a logged model](/api/workspace/experiments/createloggedmodel) API replaces this endpoint.
Log a model to an MLflow Run.
func (*Client) LogOutputs ¶
func (c *Client) LogOutputs(ctx context.Context, req *LogOutputsRequest, opts ...call.Option) (*LogOutputsResponse, error)
Logs outputs, such as models, from an MLflow Run.
func (*Client) LogParam ¶
func (c *Client) LogParam(ctx context.Context, req *LogParamRequest, opts ...call.Option) (*LogParamResponse, error)
Logs a param used for a run. A param is a key-value pair (string key, string value). Examples include hyperparameters used for ML model training and constant dates and values used in an ETL pipeline. A param can be logged only once for a run.
func (*Client) RestoreExperiment ¶
func (c *Client) RestoreExperiment(ctx context.Context, req *RestoreExperimentRequest, opts ...call.Option) (*RestoreExperimentResponse, error)
Restore an experiment marked for deletion. This also restores associated metadata, runs, metrics, params, and tags. If experiment uses FileStore, underlying artifacts associated with experiment are also restored.
Throws `RESOURCE_DOES_NOT_EXIST` if experiment was never created or was permanently deleted.
func (*Client) RestoreRun ¶
func (c *Client) RestoreRun(ctx context.Context, req *RestoreRunRequest, opts ...call.Option) (*RestoreRunResponse, error)
Restores a deleted run. This also restores associated metadata, runs, metrics, params, and tags.
Throws `RESOURCE_DOES_NOT_EXIST` if the run was never created or was permanently deleted.
func (*Client) RestoreRuns ¶
func (c *Client) RestoreRuns(ctx context.Context, req *RestoreRunsRequest, opts ...call.Option) (*RestoreRunsResponse, error)
Bulk restore runs in an experiment that were deleted no earlier than the specified timestamp. Restores at most max_runs per request. To call this API from a Databricks Notebook in Python, you can use the client code snippet on
func (*Client) SearchExperiments ¶
func (c *Client) SearchExperiments(ctx context.Context, req *SearchExperimentsRequest, opts ...call.Option) (*SearchExperimentsResponse, error)
Searches for experiments that satisfy specified search criteria.
func (*Client) SearchExperimentsIter ¶
func (c *Client) SearchExperimentsIter(ctx context.Context, req *SearchExperimentsRequest, opts ...call.Option) iter.Seq2[*Experiment, error]
SearchExperimentsIter returns an iterator that iterates over the results of SearchExperiments.
For example:
for item, err := range c.SearchExperimentsIter(ctx, &SearchExperimentsRequest{}) {
if err != nil {
return err
}
fmt.Println(item)
}
Options opts are passed to each SearchExperiments call made by the iterator under the hood.
Callers who need custom pagination logic should use SearchExperiments directly.
func (*Client) SearchLoggedModels ¶
func (c *Client) SearchLoggedModels(ctx context.Context, req *SearchLoggedModelsRequest, opts ...call.Option) (*SearchLoggedModelsResponse, error)
Search for Logged Models that satisfy specified search criteria.
func (*Client) SearchRuns ¶
func (c *Client) SearchRuns(ctx context.Context, req *SearchRunsRequest, opts ...call.Option) (*SearchRunsResponse, error)
Searches for runs that satisfy expressions.
Search expressions can use `mlflowMetric` and `mlflowParam` keys.
func (*Client) SearchRunsIter ¶
func (c *Client) SearchRunsIter(ctx context.Context, req *SearchRunsRequest, opts ...call.Option) iter.Seq2[*Run, error]
SearchRunsIter returns an iterator that iterates over the results of SearchRuns.
For example:
for item, err := range c.SearchRunsIter(ctx, &SearchRunsRequest{}) {
if err != nil {
return err
}
fmt.Println(item)
}
Options opts are passed to each SearchRuns call made by the iterator under the hood.
Callers who need custom pagination logic should use SearchRuns directly.
func (*Client) SetExperimentTag ¶
func (c *Client) SetExperimentTag(ctx context.Context, req *SetExperimentTagRequest, opts ...call.Option) (*SetExperimentTagResponse, error)
Sets a tag on an experiment. Experiment tags are metadata that can be updated.
func (*Client) SetLoggedModelTags ¶
func (c *Client) SetLoggedModelTags(ctx context.Context, req *SetLoggedModelTagsRequest, opts ...call.Option) (*SetLoggedModelTagsResponse, error)
Set tags for a logged model.
func (*Client) SetTag ¶
func (c *Client) SetTag(ctx context.Context, req *SetTagRequest, opts ...call.Option) (*SetTagResponse, error)
Sets a tag on a run. Tags are run metadata that can be updated during a run and after a run completes.
func (*Client) UpdateExperiment ¶
func (c *Client) UpdateExperiment(ctx context.Context, req *UpdateExperimentRequest, opts ...call.Option) (*UpdateExperimentResponse, error)
Updates experiment metadata.
func (*Client) UpdateRun ¶
func (c *Client) UpdateRun(ctx context.Context, req *UpdateRunRequest, opts ...call.Option) (*UpdateRunResponse, error)
Updates run metadata.
type CreateExperimentRequest ¶
type CreateExperimentRequest struct {
// Experiment name.
Name *string
// Location where all artifacts for the experiment are stored. If not provided,
// the remote server will select an appropriate default.
ArtifactLocation *string
// A collection of tags to set on the experiment. Maximum tag size and number of
// tags per request depends on the storage backend. All storage backends are
// guaranteed to support tag keys up to 250 bytes in size and tag values up to
// 5000 bytes in size. All storage backends are also guaranteed to support up to
// 20 tags per request.
Tags []ExperimentTag
// The location where the experiment's traces are stored. When set, the
// underlying storage is provisioned and the experiment's traces are routed to
// it. When unset, traces are stored in the default MLflow backend. This field
// cannot be updated after the experiment is created.
TraceLocation *ExperimentTraceLocation
}
type CreateExperimentResponse ¶
type CreateExperimentResponse struct {
// Unique identifier for the experiment.
ExperimentId *string
}
type CreateLoggedModelRequest ¶
type CreateLoggedModelRequest struct {
// The ID of the experiment that owns the model.
ExperimentId *string
// The name of the model (optional). If not specified one will be generated.
Name *string
// The type of the model, such as “"Agent"“, “"Classifier"“, “"LLM"“.
ModelType *string
// The ID of the run that created the model.
SourceRunId *string
// Parameters attached to the model.
Params []LoggedModelParameter
// Tags attached to the model.
Tags []LoggedModelTag
}
type CreateLoggedModelResponse ¶
type CreateLoggedModelResponse struct {
// The newly created logged model.
Model *LoggedModel
}
type CreateRunRequest ¶
type CreateRunRequest struct {
// ID of the associated experiment.
ExperimentId *string
// ID of the user executing the run. This field is deprecated as of MLflow 1.0,
// and will be removed in a future MLflow release. Use 'mlflow.user' tag
// instead.
UserId *string
// The name of the run.
RunName *string
// Unix timestamp in milliseconds of when the run started.
StartTime *int64
// Additional metadata for run.
Tags []RunTag
}
type CreateRunResponse ¶
type CreateRunResponse struct {
// The newly created run.
Run *Run
}
type Dataset ¶
type Dataset struct {
// The name of the dataset. E.g. “my.uc.table@2” “nyc-taxi-dataset”,
// “fantastic-elk-3”
Name *string
// Dataset digest, e.g. an md5 hash of the dataset that uniquely identifies it
// within datasets of the same name.
Digest *string
// The type of the dataset source, e.g. ‘databricks-uc-table’, ‘DBFS’,
// ‘S3’, ...
SourceType *string
// Source information for the dataset. Note that the source may not exactly
// reproduce the dataset if it was transformed / modified before use with
// MLflow.
Source *string
// The schema of the dataset. E.g., MLflow ColSpec JSON for a dataframe, MLflow
// TensorSpec JSON for an ndarray, or another schema format.
Schema *string
// The profile of the dataset. Summary statistics for the dataset, such as the
// number of rows in a table, the mean / std / mode of each column in a table,
// or the number of elements in an array.
Profile *string
}
Dataset. Represents a reference to data used for training, testing, or evaluation during the model development process..
type DatasetInput ¶
type DatasetInput struct {
// A list of tags for the dataset input, e.g. a “context” tag with value
// “training”
Tags []InputTag
// The dataset being used as a Run input.
Dataset *Dataset
}
DatasetInput. Represents a dataset and input tags..
type DeleteExperimentRequest ¶
type DeleteExperimentRequest struct {
// ID of the associated experiment.
ExperimentId *string
}
type DeleteExperimentResponse ¶
type DeleteExperimentResponse struct {
}
type DeleteLoggedModelRequest ¶
type DeleteLoggedModelRequest struct {
// The ID of the logged model to delete.
ModelId *string
}
type DeleteLoggedModelResponse ¶
type DeleteLoggedModelResponse struct {
}
type DeleteLoggedModelTagResponse ¶
type DeleteLoggedModelTagResponse struct {
}
type DeleteRunRequest ¶
type DeleteRunRequest struct {
// ID of the run to delete.
RunId *string
}
type DeleteRunResponse ¶
type DeleteRunResponse struct {
}
type DeleteRunsRequest ¶
type DeleteRunsRequest struct {
// The ID of the experiment containing the runs to delete.
ExperimentId *string
// The maximum creation timestamp in milliseconds since the UNIX epoch for
// deleting runs. Only runs created prior to or at this timestamp are deleted.
MaxTimestampMillis *int64
// An optional positive integer indicating the maximum number of runs to delete.
// The maximum allowed value for max_runs is 10000.
MaxRuns *int
}
type DeleteRunsResponse ¶
type DeleteRunsResponse struct {
// The number of runs deleted.
RunsDeleted *int
}
type DeleteTagRequest ¶
type DeleteTagResponse ¶
type DeleteTagResponse struct {
}
type Experiment ¶
type Experiment struct {
// Unique identifier for the experiment.
ExperimentId *string
// Human readable name that identifies the experiment.
Name *string
// Location where artifacts for the experiment are stored.
ArtifactLocation *string
// Current life cycle stage of the experiment: "active" or "deleted". Deleted
// experiments are not returned by APIs.
LifecycleStage *string
// Last update time
LastUpdateTime *int64
// Creation time
CreationTime *int64
// Tags: Additional metadata key-value pairs.
Tags []ExperimentTag
// The location where the experiment's traces are stored. Unset when traces are
// stored in the default MLflow backend. This field cannot be updated after the
// experiment is created.
TraceLocation *ExperimentTraceLocation
}
An experiment and its metadata..
type ExperimentTag ¶
A tag for an experiment..
type ExperimentTraceLocation ¶
type ExperimentTraceLocation struct {
Location isExperimentTraceLocation_Location
}
The storage location for an experiment's traces..
type ExperimentTraceLocation_Location_UcTraceLocation ¶
type ExperimentTraceLocation_Location_UcTraceLocation struct {
UcTraceLocation UcTraceLocation
}
ExperimentTraceLocation_Location_UcTraceLocation selects UcTraceLocation for ExperimentTraceLocation.Location. A Unity Catalog schema where the experiment's traces are stored as Delta tables.
type FileInfo ¶
type FileInfo struct {
// The path relative to the root artifact directory run.
Path *string
// Whether the path is a directory.
IsDir *bool
// The size in bytes of the file. Unset for directories.
FileSize *int64
}
Metadata of a single artifact file or directory..
type FinalizeLoggedModelRequest ¶
type FinalizeLoggedModelRequest struct {
// The ID of the logged model to finalize.
ModelId *string
// Whether or not the model is ready for use. “"LOGGED_MODEL_UPLOAD_FAILED"“
// indicates that something went wrong when logging the model weights / agent
// code.
Status LoggedModelStatus
}
type FinalizeLoggedModelResponse ¶
type FinalizeLoggedModelResponse struct {
// The updated logged model.
Model *LoggedModel
}
type GetExperimentByNameRequest ¶
type GetExperimentByNameRequest struct {
// Name of the associated experiment.
ExperimentName *string
}
type GetExperimentByNameResponse ¶
type GetExperimentByNameResponse struct {
// Experiment details.
Experiment *Experiment
}
type GetExperimentRequest ¶
type GetExperimentRequest struct {
// ID of the associated experiment.
ExperimentId *string
}
type GetExperimentResponse ¶
type GetExperimentResponse struct {
// Experiment details.
Experiment *Experiment
// A collection of active runs in the experiment. Note: this may not contain all
// of the experiment's active runs.
//
// This field is deprecated. Please use the "Search Runs" API to fetch runs
// within an experiment.
Runs []RunInfo
}
type GetLoggedModelRequest ¶
type GetLoggedModelRequest struct {
// The ID of the logged model to retrieve.
ModelId *string
}
type GetLoggedModelResponse ¶
type GetLoggedModelResponse struct {
// The retrieved logged model.
Model *LoggedModel
}
type GetMetricHistoryResponse ¶
type GetMetricHistoryResponse struct {
// All logged values for this metric if `max_results` is not specified in the
// request or if the total count of metrics returned is less than the service
// level pagination threshold. Otherwise, this is one page of results.
Metrics []Metric
// A token that can be used to issue a query for the next page of metric history
// values. A missing token indicates that no additional metrics are available to
// fetch.
NextPageToken *string
}
type GetRunRequest ¶
type GetRunResponse ¶
type GetRunResponse struct {
// Run metadata (name, start time, etc) and data (metrics, params, and tags).
Run *Run
}
type ListArtifactsRequest ¶
type ListArtifactsRequest struct {
// ID of the run whose artifacts to list. Must be provided.
RunId *string
// [Deprecated, use `run_id` instead] ID of the run whose artifacts to list.
// This field will be removed in a future MLflow version.
RunUuid *string
// Filter artifacts matching this path (a relative path from the root artifact
// directory).
Path *string
// The token indicating the page of artifact results to fetch. `page_token` is
// not supported when listing artifacts in UC Volumes. A maximum of 1000
// artifacts will be retrieved for UC Volumes. Please call
// `/api/2.0/fs/directories{directory_path}` for listing artifacts in UC
// Volumes, which supports pagination. See [List directory contents | Files
// API](/api/workspace/files/listdirectorycontents).
PageToken *string
}
type ListArtifactsResponse ¶
type ListExperimentsRequest ¶
type ListExperimentsRequest struct {
// Qualifier for type of experiments to be returned. If unspecified, return only
// active experiments.
ViewType ViewType
// Maximum number of experiments desired. If `max_results` is unspecified,
// return all experiments. If `max_results` is too large, it'll be automatically
// capped at 1000. Callers of this endpoint are encouraged to pass max_results
// explicitly and leverage page_token to iterate through experiments.
MaxResults *int64
// Token indicating the page of experiments to fetch
PageToken *string
}
type ListExperimentsResponse ¶
type ListExperimentsResponse struct {
// Paginated Experiments beginning with the first item on the requested page.
Experiments []Experiment
// Token that can be used to retrieve the next page of experiments. Empty token
// means no more experiment is available for retrieval.
NextPageToken *string
}
type ListMetricHistoryRequest ¶
type ListMetricHistoryRequest struct {
// ID of the run from which to fetch metric values. Must be provided.
RunId *string
// [Deprecated, use `run_id` instead] ID of the run from which to fetch metric
// values. This field will be removed in a future MLflow version.
RunUuid *string
// Name of the metric.
MetricKey *string
// Token indicating the page of metric histories to fetch.
PageToken *string
// Maximum number of Metric records to return per paginated request. Default is
// set to 25,000. If set higher than 25,000, a request Exception will be raised.
MaxResults *int
}
type LogBatchRequest ¶
type LogBatchRequest struct {
// ID of the run to log under
RunId *string
// Metrics to log. A single request can contain up to 1000 metrics, and up to
// 1000 metrics, params, and tags in total.
Metrics []Metric
// Params to log. A single request can contain up to 100 params, and up to 1000
// metrics, params, and tags in total.
Params []Param
// Tags to log. A single request can contain up to 100 tags, and up to 1000
// metrics, params, and tags in total.
Tags []RunTag
}
type LogBatchResponse ¶
type LogBatchResponse struct {
}
type LogInputsRequest ¶
type LogInputsRequest struct {
// ID of the run to log under
RunId *string
// Dataset inputs
Datasets []DatasetInput
// Model inputs
Models []ModelInput
}
type LogInputsResponse ¶
type LogInputsResponse struct {
}
type LogLoggedModelParamsRequest ¶
type LogLoggedModelParamsRequest struct {
// The ID of the logged model to log params for.
ModelId *string
// Parameters to attach to the model.
Params []LoggedModelParameter
}
type LogLoggedModelParamsResponse ¶
type LogLoggedModelParamsResponse struct {
}
type LogMetricRequest ¶
type LogMetricRequest struct {
// ID of the run under which to log the metric. Must be provided.
RunId *string
// [Deprecated, use `run_id` instead] ID of the run under which to log the
// metric. This field will be removed in a future MLflow version.
RunUuid *string
// Name of the metric.
Key *string
// Double value of the metric being logged.
Value *float64
// Unix timestamp in milliseconds at the time metric was logged.
Timestamp *int64
// Step at which to log the metric
Step *int64
// ID of the logged model associated with the metric, if applicable
ModelId *string
// The name of the dataset associated with the metric. E.g. “my.uc.table@2”
// “nyc-taxi-dataset”, “fantastic-elk-3”
DatasetName *string
// Dataset digest of the dataset associated with the metric, e.g. an md5 hash of
// the dataset that uniquely identifies it within datasets of the same name.
DatasetDigest *string
}
type LogMetricResponse ¶
type LogMetricResponse struct {
}
type LogModelRequest ¶
type LogModelResponse ¶
type LogModelResponse struct {
}
type LogOutputsRequest ¶
type LogOutputsRequest struct {
// The ID of the Run from which to log outputs.
RunId *string
// The model outputs from the Run.
Models []ModelOutput
}
type LogOutputsResponse ¶
type LogOutputsResponse struct {
}
type LogParamRequest ¶
type LogParamRequest struct {
// ID of the run under which to log the param. Must be provided.
RunId *string
// [Deprecated, use `run_id` instead] ID of the run under which to log the
// param. This field will be removed in a future MLflow version.
RunUuid *string
// Name of the param. Maximum size is 255 bytes.
Key *string
// String value of the param being logged. Maximum size is 500 bytes.
Value *string
}
type LogParamResponse ¶
type LogParamResponse struct {
}
type LoggedModel ¶
type LoggedModel struct {
// The logged model attributes such as model ID, status, tags, etc.
Info *LoggedModelInfo
// The params and metrics attached to the logged model.
Data *LoggedModelData
}
A logged model message includes logged model attributes, tags, registration info, params, and linked run metrics..
type LoggedModelData ¶
type LoggedModelData struct {
// Immutable string key-value pairs of the model.
Params []LoggedModelParameter
// Performance metrics linked to the model.
Metrics []Metric
}
A LoggedModelData message includes logged model params and linked metrics..
type LoggedModelInfo ¶
type LoggedModelInfo struct {
// The unique identifier for the logged model.
ModelId *string
// The ID of the experiment that owns the model.
ExperimentId *string
// The name of the model.
Name *string
// The timestamp when the model was created in milliseconds since the UNIX
// epoch.
CreationTimestampMs *int64
// The timestamp when the model was last updated in milliseconds since the UNIX
// epoch.
LastUpdatedTimestampMs *int64
// The URI of the directory where model artifacts are stored.
ArtifactUri *string
// The status of whether or not the model is ready for use.
Status LoggedModelStatus
// The ID of the user or principal that created the model.
CreatorId *int64
// The type of model, such as “"Agent"“, “"Classifier"“, “"LLM"“.
ModelType *string
// The ID of the run that created the model.
SourceRunId *string
// Details on the current model status.
StatusMessage *string
// Mutable string key-value pairs set on the model.
Tags []LoggedModelTag
}
A LoggedModelInfo includes logged model attributes, tags, and registration info..
type LoggedModelParameter ¶
type LoggedModelParameter struct {
// The key identifying this param.
Key *string
// The value of this param.
Value *string
}
Parameter associated with a LoggedModel..
type LoggedModelStatus ¶
type LoggedModelStatus string
A LoggedModelStatus enum value represents the status of a logged model.
const ( LoggedModelStatus_Unspecified LoggedModelStatus = "" // The LoggedModel has been created, but the LoggedModel files are not // completely uploaded. LoggedModelStatus_LoggedModelPending LoggedModelStatus = "LOGGED_MODEL_PENDING" // The LoggedModel is created, and the LoggedModel files are completely // uploaded. LoggedModelStatus_LoggedModelReady LoggedModelStatus = "LOGGED_MODEL_READY" // The LoggedModel is created, but an error occurred when uploading the // LoggedModel files such as model weights / agent code. LoggedModelStatus_LoggedModelUploadFailed LoggedModelStatus = "LOGGED_MODEL_UPLOAD_FAILED" )
type LoggedModelTag ¶
Tag for a LoggedModel..
type Metric ¶
type Metric struct {
// The key identifying the metric.
Key *string
// The value of the metric.
Value *float64
// The timestamp at which the metric was recorded.
Timestamp *int64
// The step at which the metric was logged.
Step *int64
// The name of the dataset associated with the metric. E.g. “my.uc.table@2”
// “nyc-taxi-dataset”, “fantastic-elk-3”
DatasetName *string
// The dataset digest of the dataset associated with the metric, e.g. an md5
// hash of the dataset that uniquely identifies it within datasets of the same
// name.
DatasetDigest *string
// The ID of the logged model or registered model version associated with the
// metric, if applicable.
ModelId *string
// The ID of the run containing the metric.
RunId *string
}
Metric associated with a run, represented as a key-value pair..
type ModelInput ¶
type ModelInput struct {
// The unique identifier of the model.
ModelId *string
}
Represents a LoggedModel or Registered Model Version input to a Run..
type ModelOutput ¶
type ModelOutput struct {
// The unique identifier of the model.
ModelId *string
// The step at which the model was produced.
Step *int64
}
Represents a LoggedModel output of a Run..
type Param ¶
type Param struct {
// Key identifying this param.
Key *string
// Value associated with this param.
Value *string
}
Param associated with a run..
type RestoreExperimentRequest ¶
type RestoreExperimentRequest struct {
// ID of the associated experiment.
ExperimentId *string
}
type RestoreExperimentResponse ¶
type RestoreExperimentResponse struct {
}
type RestoreRunRequest ¶
type RestoreRunRequest struct {
// ID of the run to restore.
RunId *string
}
type RestoreRunResponse ¶
type RestoreRunResponse struct {
}
type RestoreRunsRequest ¶
type RestoreRunsRequest struct {
// The ID of the experiment containing the runs to restore.
ExperimentId *string
// The minimum deletion timestamp in milliseconds since the UNIX epoch for
// restoring runs. Only runs deleted no earlier than this timestamp are
// restored.
MinTimestampMillis *int64
// An optional positive integer indicating the maximum number of runs to
// restore. The maximum allowed value for max_runs is 10000.
MaxRuns *int
}
type RestoreRunsResponse ¶
type RestoreRunsResponse struct {
// The number of runs restored.
RunsRestored *int
}
type Run ¶
type Run struct {
// Run metadata.
Info *RunInfo
// Run data.
Data *RunData
// Run inputs.
Inputs *RunInputs
}
A single run..
type RunData ¶
type RunData struct {
// Run metrics.
Metrics []Metric
// Run parameters.
Params []Param
// Additional metadata key-value pairs.
Tags []RunTag
}
Run data (metrics, params, and tags)..
type RunInfo ¶
type RunInfo struct {
// Unique identifier for the run.
RunId *string
// [Deprecated, use run_id instead] Unique identifier for the run. This field
// will be removed in a future MLflow version.
RunUuid *string
// The experiment ID.
ExperimentId *string
// The name of the run.
RunName *string
// User who initiated the run. This field is deprecated as of MLflow 1.0, and
// will be removed in a future MLflow release. Use 'mlflow.user' tag instead.
UserId *string
// Current status of the run.
Status RunStatus
// Unix timestamp of when the run started in milliseconds.
StartTime *int64
// Unix timestamp of when the run ended in milliseconds.
EndTime *int64
// URI of the directory where artifacts should be uploaded. This can be a local
// path (starting with "/"), or a distributed file system (DFS) path, like
// “s3://bucket/directory“ or “dbfs:/my/directory“. If not set, the local
// “./mlruns“ directory is chosen.
ArtifactUri *string
// Current life cycle stage of the experiment : OneOf("active", "deleted")
LifecycleStage *string
}
Metadata of a single run..
type RunInputs ¶
type RunInputs struct {
// Run metrics.
DatasetInputs []DatasetInput
// Model inputs to the Run.
ModelInputs []ModelInput
}
Run inputs..
type RunStatus ¶
type RunStatus string
Status of a run.
const ( RunStatus_Unspecified RunStatus = "" // Run has been initiated. RunStatus_Running RunStatus = "RUNNING" // Run is scheduled to run at a later time. RunStatus_Scheduled RunStatus = "SCHEDULED" // Run has completed. RunStatus_Finished RunStatus = "FINISHED" // Run execution failed. RunStatus_Failed RunStatus = "FAILED" // Run killed by user. RunStatus_Killed RunStatus = "KILLED" )
type SearchExperimentsRequest ¶
type SearchExperimentsRequest struct {
// Maximum number of experiments desired. Max threshold is 3000.
MaxResults *int64
// Token indicating the page of experiments to fetch
PageToken *string
// String representing a SQL filter condition (e.g. "name ILIKE
// 'my-experiment%'")
Filter *string
// List of columns for ordering search results, which can include experiment
// name and last updated timestamp with an optional "DESC" or "ASC" annotation,
// where "ASC" is the default. Tiebreaks are done by experiment id DESC.
OrderBy []string
// Qualifier for type of experiments to be returned. If unspecified, return only
// active experiments.
ViewType ViewType
}
type SearchExperimentsResponse ¶
type SearchExperimentsResponse struct {
// Experiments that match the search criteria
Experiments []Experiment
// Token that can be used to retrieve the next page of experiments. An empty
// token means that no more experiments are available for retrieval.
NextPageToken *string
}
type SearchLoggedModelsRequest ¶
type SearchLoggedModelsRequest struct {
// The IDs of the experiments in which to search for logged models.
ExperimentIds []string
// A filter expression over logged model info and data that allows returning a
// subset of logged models. The syntax is a subset of SQL that supports AND'ing
// together binary operations.
//
// Example: “params.alpha < 0.3 AND metrics.accuracy > 0.9“.
Filter *string
// List of datasets on which to apply the metrics filter clauses. For example, a
// filter with `metrics.accuracy > 0.9` and dataset info with name
// "test_dataset" means we will return all logged models with accuracy > 0.9 on
// the test_dataset. Metric values from ANY dataset matching the criteria are
// considered. If no datasets are specified, then metrics across all datasets
// are considered in the filter.
Datasets []SearchLoggedModelsRequest_Dataset
// The maximum number of Logged Models to return. The maximum limit is 50.
MaxResults *int
// The list of columns for ordering the results, with additional fields for
// sorting criteria.
OrderBy []SearchLoggedModelsRequest_OrderBy
// The token indicating the page of logged models to fetch.
PageToken *string
}
type SearchLoggedModelsRequest_OrderBy ¶
type SearchLoggedModelsRequest_OrderBy struct {
// The name of the field to order by, e.g. "metrics.accuracy".
FieldName *string
// Whether the search results order is ascending or not.
Ascending *bool
// If “field_name“ refers to a metric, this field specifies the name of the
// dataset associated with the metric. Only metrics associated with the
// specified dataset name will be considered for ordering. This field may only
// be set if “field_name“ refers to a metric.
DatasetName *string
// If “field_name“ refers to a metric, this field specifies the digest of the
// dataset associated with the metric. Only metrics associated with the
// specified dataset name and digest will be considered for ordering. This field
// may only be set if “dataset_name“ is also set.
DatasetDigest *string
}
type SearchLoggedModelsResponse ¶
type SearchLoggedModelsResponse struct {
// Logged models that match the search criteria.
Models []LoggedModel
// The token that can be used to retrieve the next page of logged models.
NextPageToken *string
}
type SearchRunsRequest ¶
type SearchRunsRequest struct {
// List of experiment IDs to search over.
ExperimentIds []string
// A filter expression over params, metrics, and tags, that allows returning a
// subset of runs. The syntax is a subset of SQL that supports ANDing together
// binary operations between a param, metric, or tag and a constant.
//
// Example: `metrics.rmse < 1 and params.model_class = 'LogisticRegression'`
//
// You can select columns with special characters (hyphen, space, period, etc.)
// by using double quotes: `metrics."model class" = 'LinearRegression' and
// tags."user-name" = 'Tomas'`
//
// Supported operators are `=`, `!=`, `>`, `>=`, `<`, and `<=`.
Filter *string
// Whether to display only active, only deleted, or all runs. Defaults to only
// active runs.
RunViewType ViewType
// Maximum number of runs desired. Max threshold is 50000
MaxResults *int
// 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. Example: `["params.input DESC", "metrics.alpha ASC",
// "metrics.rmse"]`. Tiebreaks are done by start_time `DESC` followed by
// `run_id` for runs with the same start time (and this is the default ordering
// criterion if order_by is not provided).
OrderBy []string
// Token for the current page of runs.
PageToken *string
}
type SearchRunsResponse ¶
type SetExperimentTagRequest ¶
type SetExperimentTagRequest struct {
// ID of the experiment under which to log the tag. Must be provided.
ExperimentId *string
// Name of the tag. Keys up to 250 bytes in size are supported.
Key *string
// String value of the tag being logged. Values up to 64KB in size are
// supported.
Value *string
}
type SetExperimentTagResponse ¶
type SetExperimentTagResponse struct {
}
type SetLoggedModelTagsRequest ¶
type SetLoggedModelTagsRequest struct {
// The ID of the logged model to set the tags on.
ModelId *string
// The tags to set on the logged model.
Tags []LoggedModelTag
}
type SetLoggedModelTagsResponse ¶
type SetLoggedModelTagsResponse struct {
}
type SetTagRequest ¶
type SetTagRequest struct {
// ID of the run under which to log the tag. Must be provided.
RunId *string
// [Deprecated, use `run_id` instead] ID of the run under which to log the tag.
// This field will be removed in a future MLflow version.
RunUuid *string
// Name of the tag. Keys up to 250 bytes in size are supported.
Key *string
// String value of the tag being logged. Values up to 64KB in size are
// supported.
Value *string
}
type SetTagResponse ¶
type SetTagResponse struct {
}
type UcTraceLocation ¶
type UcTraceLocation struct {
// The name of the Unity Catalog catalog.
Catalog *string
// The name of the Unity Catalog schema within `catalog`.
Schema *string
// The prefix for the trace tables, which are named
// `{catalog}.{schema}.{table_prefix}_otel_*`. May only contain letters, digits,
// and underscores, and may be at most 238 characters. When unset, a
// server-generated prefix derived from the experiment ID is used and this field
// stays empty on read; the resolved value is always available in
// `effective_table_prefix`.
TablePrefix *string
// The trace-table prefix actually in effect: `table_prefix` if it was set on
// creation, otherwise the server-generated default.
EffectiveTablePrefix *string
}
A Unity Catalog trace storage location. Traces are stored as Delta tables in the specified catalog and schema..
type UpdateExperimentRequest ¶
type UpdateExperimentResponse ¶
type UpdateExperimentResponse struct {
}
type UpdateRunRequest ¶
type UpdateRunRequest struct {
// ID of the run to update. Must be provided.
RunId *string
// [Deprecated, use `run_id` instead] ID of the run to update. This field will
// be removed in a future MLflow version.
RunUuid *string
// Updated status of the run.
Status RunStatus
// Unix timestamp in milliseconds of when the run ended.
EndTime *int64
// Updated name of the run.
RunName *string
}
type UpdateRunResponse ¶
type UpdateRunResponse struct {
// Updated metadata of the run.
RunInfo *RunInfo
}