mlflow_log_batch: Log Batch

In mlflow: Interface to 'MLflow'

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.

mlflow documentation built on Nov. 1, 2024, 1:07 a.m.