mlflow (version 1.9.0)

mlflow_log_batch: Log Batch

Description

Log a batch of metrics, params, and/or tags for a run. The server will respond with an error (non-200 status code) if any data failed to be persisted. In case of error (due to internal server error or an invalid request), partial data may be written.

Usage

mlflow_log_batch(
  metrics = NULL,
  params = NULL,
  tags = NULL,
  run_id = NULL,
  client = NULL
)

Arguments

metrics

A dataframe of metrics to log, containing the following columns: "key", "value", "step", "timestamp". This dataframe cannot contain any missing ('NA') entries.

params

A dataframe of params to log, containing the following columns: "key", "value". This dataframe cannot contain any missing ('NA') entries.

tags

A dataframe of tags to log, containing the following columns: "key", "value". This dataframe cannot contain any missing ('NA') entries.

run_id

Run ID.

client

(Optional) An MLflow client object returned from mlflow_client. If specified, MLflow will use the tracking server associated with the passed-in client. If unspecified (the common case), MLflow will use the tracking server associated with the current tracking URI.