Struct MLflowClient 

pub struct MLflowClient { /* private fields */ }

MLflow client for experiment tracking

Implementations

impl MLflowClient

pub fn new(config: MLflowConfig) -> Self

Create a new MLflow client

Arguments

• config - MLflow configuration

Example

use trustformers_debug::{MLflowClient, MLflowConfig};

let config = MLflowConfig::default();
let client = MLflowClient::new(config);

pub fn set_tracking_uri(&mut self, uri: impl Into<String>)

Set the tracking URI

Arguments

• uri - MLflow tracking server URI

pub fn start_experiment(&mut self, name: impl Into<String>) -> Result<String>

Start a new experiment

Arguments

• name - Experiment name

Returns

Experiment ID

pub fn start_run(&mut self, run_name: Option<&str>) -> Result<String>

Start a new run within the current experiment

Arguments

• run_name - Optional run name

Returns

Run ID

pub fn end_run(&mut self, status: RunStatus) -> Result<()>

End the current run

Arguments

• status - Final run status

pub fn log_param( &mut self, key: impl Into<String>, value: impl ToString, ) -> Result<()>

Log a parameter

Arguments

• key - Parameter name
• value - Parameter value

pub fn log_params(&mut self, params: HashMap<String, String>) -> Result<()>

Log multiple parameters at once

Arguments

• params - Map of parameter names to values

pub fn log_metric( &mut self, key: impl Into<String>, value: f64, step: i64, ) -> Result<()>

Log a metric at a specific step

Arguments

• key - Metric name
• value - Metric value
• step - Step number

pub fn log_metrics( &mut self, metrics: HashMap<String, f64>, step: i64, ) -> Result<()>

Log multiple metrics at once

Arguments

• metrics - Map of metric names to values
• step - Step number

pub fn log_tensor_stats( &mut self, prefix: &str, tensor: &Tensor, step: i64, ) -> Result<()>

Log tensor statistics as metrics

Arguments

• prefix - Metric name prefix
• tensor - Tensor to analyze
• step - Step number

pub fn log_array_stats( &mut self, prefix: &str, array: &Array1<f64>, step: i64, ) -> Result<()>

Log array statistics as metrics

Arguments

• prefix - Metric name prefix
• array - Array to analyze
• step - Step number

pub fn log_artifact( &self, local_path: impl AsRef<Path>, artifact_path: Option<&str>, artifact_type: ArtifactType, ) -> Result<()>

Log an artifact (file)

Arguments

• local_path - Path to local file
• artifact_path - Optional path within artifact storage
• artifact_type - Type of artifact

pub fn log_model( &self, model_path: impl AsRef<Path>, model_name: Option<&str>, ) -> Result<()>

Log a model artifact

Arguments

• model_path - Path to model file
• model_name - Optional model name

pub fn log_plot( &self, plot_path: impl AsRef<Path>, plot_name: Option<&str>, ) -> Result<()>

Log a plot/visualization

Arguments

• plot_path - Path to plot file
• plot_name - Optional plot name

pub fn log_report(&self, content: &str, filename: &str) -> Result<()>

Log a text report

Arguments

• content - Report content
• filename - Report filename

pub fn get_run_info(&self) -> Option<RunInfo>

Get current run information

pub fn get_params(&self) -> HashMap<String, String>

Get all logged parameters

pub fn get_metrics(&self) -> HashMap<String, Vec<MetricPoint>>

Get all logged metrics

Trait Implementations

impl Debug for MLflowClient

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.