trustformers_training/
framework_integration.rs

1//! Framework Integration for TrustformeRS Training
2//!
3//! This module provides integrations with popular ML experiment tracking and monitoring
4//! frameworks including WandB, MLflow, TensorBoard, Neptune.ai, and ClearML.
5
6use anyhow::{anyhow, Result};
7use serde::{Deserialize, Serialize};
8use std::collections::HashMap;
9use std::path::PathBuf;
10use std::sync::{Arc, Mutex};
11use std::time::SystemTime;
12
13/// Main framework integration manager
14pub struct FrameworkIntegrationManager {
15    /// Active integrations
16    integrations: Arc<Mutex<HashMap<String, Box<dyn ExperimentTracker>>>>,
17    /// Configuration
18    #[allow(dead_code)]
19    config: IntegrationConfig,
20    /// Experiment metadata
21    experiment_metadata: Arc<Mutex<ExperimentMetadata>>,
22}
23
24#[derive(Debug, Clone, Serialize, Deserialize)]
25pub struct IntegrationConfig {
26    /// Enabled integrations
27    pub enabled_integrations: Vec<IntegrationType>,
28    /// Default integration for logging
29    pub default_integration: Option<IntegrationType>,
30    /// Synchronization settings
31    pub sync_config: SyncConfig,
32    /// Data export settings
33    pub export_config: ExportConfig,
34}
35
36#[derive(Debug, Clone, Serialize, Deserialize)]
37pub enum IntegrationType {
38    /// Weights & Biases
39    WandB { config: WandBConfig },
40    /// MLflow
41    MLflow { config: MLflowConfig },
42    /// TensorBoard
43    TensorBoard { config: TensorBoardConfig },
44    /// Neptune.ai
45    Neptune { config: NeptuneConfig },
46    /// ClearML
47    ClearML { config: ClearMLConfig },
48    /// Custom integration
49    Custom {
50        name: String,
51        config: HashMap<String, String>,
52    },
53}
54
55#[derive(Debug, Clone, Serialize, Deserialize)]
56pub struct SyncConfig {
57    /// Synchronize metrics across all integrations
58    pub sync_metrics: bool,
59    /// Synchronize artifacts
60    pub sync_artifacts: bool,
61    /// Synchronization frequency
62    pub sync_frequency: SyncFrequency,
63    /// Conflict resolution strategy
64    pub conflict_resolution: ConflictResolution,
65}
66
67#[derive(Debug, Clone, Serialize, Deserialize)]
68pub enum SyncFrequency {
69    /// Real-time synchronization
70    RealTime,
71    /// Batch synchronization
72    Batch { interval_seconds: u64 },
73    /// Manual synchronization
74    Manual,
75}
76
77#[derive(Debug, Clone, Serialize, Deserialize)]
78pub enum ConflictResolution {
79    /// Use first integration's value
80    FirstWins,
81    /// Use last integration's value
82    LastWins,
83    /// Merge values if possible
84    Merge,
85    /// Skip conflicting values
86    Skip,
87}
88
89#[derive(Debug, Clone, Serialize, Deserialize)]
90pub struct ExportConfig {
91    /// Export formats
92    pub formats: Vec<ExportFormat>,
93    /// Export frequency
94    pub frequency: ExportFrequency,
95    /// Output directory
96    pub output_dir: PathBuf,
97}
98
99#[derive(Debug, Clone, Serialize, Deserialize)]
100pub enum ExportFormat {
101    JSON,
102    CSV,
103    Parquet,
104    HDF5,
105    SQLite,
106}
107
108#[derive(Debug, Clone, Serialize, Deserialize)]
109pub enum ExportFrequency {
110    /// Export at end of training
111    EndOfTraining,
112    /// Export at end of each epoch
113    EndOfEpoch,
114    /// Export at regular intervals
115    Interval { seconds: u64 },
116}
117
118/// WandB integration configuration
119#[derive(Debug, Clone, Serialize, Deserialize)]
120pub struct WandBConfig {
121    /// Project name
122    pub project: String,
123    /// Entity (team) name
124    pub entity: Option<String>,
125    /// Run name
126    pub run_name: Option<String>,
127    /// Run group
128    pub group: Option<String>,
129    /// Job type
130    pub job_type: Option<String>,
131    /// Tags
132    pub tags: Vec<String>,
133    /// API key
134    pub api_key: Option<String>,
135    /// Offline mode
136    pub offline: bool,
137    /// Resume configuration
138    pub resume: ResumeConfig,
139    /// Artifact configuration
140    pub artifacts: ArtifactConfig,
141    /// Advanced settings
142    pub advanced: WandBAdvancedConfig,
143}
144
145#[derive(Debug, Clone, Serialize, Deserialize)]
146pub enum ResumeConfig {
147    /// Never resume
148    Never,
149    /// Always resume if possible
150    Always,
151    /// Resume with specific run ID
152    RunId { run_id: String },
153    /// Auto resume
154    Auto,
155}
156
157#[derive(Debug, Clone, Serialize, Deserialize)]
158pub struct ArtifactConfig {
159    /// Track model artifacts
160    pub track_models: bool,
161    /// Track dataset artifacts
162    pub track_datasets: bool,
163    /// Track code artifacts
164    pub track_code: bool,
165    /// Custom artifacts
166    pub custom_artifacts: Vec<CustomArtifact>,
167}
168
169#[derive(Debug, Clone, Serialize, Deserialize)]
170pub struct CustomArtifact {
171    /// Artifact name
172    pub name: String,
173    /// Artifact type
174    pub artifact_type: String,
175    /// Source path
176    pub source_path: PathBuf,
177    /// Metadata
178    pub metadata: HashMap<String, String>,
179}
180
181#[derive(Debug, Clone, Serialize, Deserialize)]
182pub struct WandBAdvancedConfig {
183    /// Log system metrics
184    pub log_system_metrics: bool,
185    /// Log code changes
186    pub log_code: bool,
187    /// Save code
188    pub save_code: bool,
189    /// Watch model
190    pub watch_model: WatchModelConfig,
191    /// Custom metrics
192    pub custom_metrics: Vec<CustomMetric>,
193}
194
195#[derive(Debug, Clone, Serialize, Deserialize)]
196pub struct WatchModelConfig {
197    /// Enable model watching
198    pub enabled: bool,
199    /// Log frequency
200    pub log_freq: usize,
201    /// Log gradients
202    pub log_gradients: bool,
203    /// Log parameters
204    pub log_parameters: bool,
205    /// Log graph
206    pub log_graph: bool,
207}
208
209#[derive(Debug, Clone, Serialize, Deserialize)]
210pub struct CustomMetric {
211    /// Metric name
212    pub name: String,
213    /// Metric type
214    pub metric_type: MetricType,
215    /// Aggregation function
216    pub aggregation: AggregationFunction,
217}
218
219#[derive(Debug, Clone, Serialize, Deserialize)]
220pub enum MetricType {
221    Scalar,
222    Histogram,
223    Image,
224    Audio,
225    Video,
226    Table,
227    Html,
228}
229
230#[derive(Debug, Clone, Serialize, Deserialize)]
231pub enum AggregationFunction {
232    Mean,
233    Sum,
234    Max,
235    Min,
236    Count,
237    StdDev,
238}
239
240/// MLflow integration configuration
241#[derive(Debug, Clone, Serialize, Deserialize)]
242pub struct MLflowConfig {
243    /// Tracking URI
244    pub tracking_uri: String,
245    /// Experiment name
246    pub experiment_name: String,
247    /// Run name
248    pub run_name: Option<String>,
249    /// Registry URI
250    pub registry_uri: Option<String>,
251    /// Artifact location
252    pub artifact_location: Option<PathBuf>,
253    /// Authentication
254    pub auth: MLflowAuth,
255    /// Model registration
256    pub model_registration: ModelRegistrationConfig,
257    /// Advanced settings
258    pub advanced: MLflowAdvancedConfig,
259}
260
261#[derive(Debug, Clone, Serialize, Deserialize)]
262pub struct MLflowAuth {
263    /// Authentication type
264    pub auth_type: MLflowAuthType,
265    /// Authentication credentials
266    pub credentials: HashMap<String, String>,
267}
268
269#[derive(Debug, Clone, Serialize, Deserialize)]
270pub enum MLflowAuthType {
271    None,
272    BasicAuth,
273    Token,
274    OAuth,
275}
276
277#[derive(Debug, Clone, Serialize, Deserialize)]
278pub struct ModelRegistrationConfig {
279    /// Auto-register models
280    pub auto_register: bool,
281    /// Model name
282    pub model_name: String,
283    /// Model stage
284    pub stage: ModelStage,
285    /// Model description
286    pub description: Option<String>,
287    /// Model tags
288    pub tags: HashMap<String, String>,
289}
290
291#[derive(Debug, Clone, Serialize, Deserialize)]
292pub enum ModelStage {
293    Staging,
294    Production,
295    Archived,
296    None,
297}
298
299#[derive(Debug, Clone, Serialize, Deserialize)]
300pub struct MLflowAdvancedConfig {
301    /// Log system metrics
302    pub log_system_metrics: bool,
303    /// Auto-log parameters
304    pub autolog_parameters: bool,
305    /// Auto-log metrics
306    pub autolog_metrics: bool,
307    /// Auto-log artifacts
308    pub autolog_artifacts: bool,
309    /// Nested runs
310    pub nested_runs: bool,
311}
312
313/// TensorBoard integration configuration
314#[derive(Debug, Clone, Serialize, Deserialize)]
315pub struct TensorBoardConfig {
316    /// Log directory
317    pub log_dir: PathBuf,
318    /// Experiment name
319    pub experiment_name: String,
320    /// Update frequency
321    pub update_freq: UpdateFrequency,
322    /// Histogram configuration
323    pub histograms: HistogramConfig,
324    /// Image logging
325    pub images: ImageLoggingConfig,
326    /// Audio logging
327    pub audio: AudioLoggingConfig,
328    /// Graph logging
329    pub graph: GraphLoggingConfig,
330    /// Advanced features
331    pub advanced: TensorBoardAdvancedConfig,
332}
333
334#[derive(Debug, Clone, Serialize, Deserialize)]
335pub enum UpdateFrequency {
336    /// Update every N steps
337    Steps(usize),
338    /// Update every N epochs
339    Epochs(usize),
340    /// Update every N seconds
341    Seconds(u64),
342}
343
344#[derive(Debug, Clone, Serialize, Deserialize)]
345pub struct HistogramConfig {
346    /// Enable histogram logging
347    pub enabled: bool,
348    /// Log weights
349    pub log_weights: bool,
350    /// Log gradients
351    pub log_gradients: bool,
352    /// Log activations
353    pub log_activations: bool,
354    /// Bucket count
355    pub bucket_count: usize,
356}
357
358#[derive(Debug, Clone, Serialize, Deserialize)]
359pub struct ImageLoggingConfig {
360    /// Enable image logging
361    pub enabled: bool,
362    /// Maximum images per step
363    pub max_images: usize,
364    /// Image size
365    pub image_size: (usize, usize),
366    /// Color format
367    pub color_format: ColorFormat,
368}
369
370#[derive(Debug, Clone, Serialize, Deserialize)]
371pub enum ColorFormat {
372    RGB,
373    BGR,
374    Grayscale,
375}
376
377#[derive(Debug, Clone, Serialize, Deserialize)]
378pub struct AudioLoggingConfig {
379    /// Enable audio logging
380    pub enabled: bool,
381    /// Sample rate
382    pub sample_rate: usize,
383    /// Maximum duration (seconds)
384    pub max_duration: f64,
385}
386
387#[derive(Debug, Clone, Serialize, Deserialize)]
388pub struct GraphLoggingConfig {
389    /// Enable graph logging
390    pub enabled: bool,
391    /// Profile execution
392    pub profile_execution: bool,
393    /// Log device placement
394    pub log_device_placement: bool,
395}
396
397#[derive(Debug, Clone, Serialize, Deserialize)]
398pub struct TensorBoardAdvancedConfig {
399    /// Enable profiling
400    pub profiling: ProfilingConfig,
401    /// Custom scalars
402    pub custom_scalars: Vec<CustomScalar>,
403    /// Mesh visualization
404    pub mesh_visualization: bool,
405}
406
407#[derive(Debug, Clone, Serialize, Deserialize)]
408pub struct ProfilingConfig {
409    /// Enable profiling
410    pub enabled: bool,
411    /// Profile steps
412    pub profile_steps: Vec<usize>,
413    /// Profile memory
414    pub profile_memory: bool,
415    /// Profile operators
416    pub profile_operators: bool,
417}
418
419#[derive(Debug, Clone, Serialize, Deserialize)]
420pub struct CustomScalar {
421    /// Scalar name
422    pub name: String,
423    /// Layout configuration
424    pub layout: ScalarLayout,
425}
426
427#[derive(Debug, Clone, Serialize, Deserialize)]
428pub struct ScalarLayout {
429    /// Chart title
430    pub title: String,
431    /// Series names
432    pub series: Vec<String>,
433    /// Chart type
434    pub chart_type: ChartType,
435}
436
437#[derive(Debug, Clone, Serialize, Deserialize)]
438pub enum ChartType {
439    Line,
440    Scatter,
441    Bar,
442    Histogram,
443}
444
445/// Neptune.ai integration configuration
446#[derive(Debug, Clone, Serialize, Deserialize)]
447pub struct NeptuneConfig {
448    /// Project name
449    pub project: String,
450    /// API token
451    pub api_token: String,
452    /// Run name
453    pub run_name: Option<String>,
454    /// Tags
455    pub tags: Vec<String>,
456    /// Source files
457    pub source_files: Vec<PathBuf>,
458    /// Monitoring
459    pub monitoring: NeptuneMonitoringConfig,
460    /// Experiment tracking
461    pub experiment_tracking: NeptuneExperimentConfig,
462}
463
464#[derive(Debug, Clone, Serialize, Deserialize)]
465pub struct NeptuneMonitoringConfig {
466    /// Monitor system metrics
467    pub system_metrics: bool,
468    /// Monitor GPU metrics
469    pub gpu_metrics: bool,
470    /// Custom monitoring
471    pub custom_monitoring: Vec<CustomMonitoring>,
472}
473
474#[derive(Debug, Clone, Serialize, Deserialize)]
475pub struct CustomMonitoring {
476    /// Metric name
477    pub name: String,
478    /// Monitoring function
479    pub function: String,
480    /// Update frequency
481    pub frequency: u64,
482}
483
484#[derive(Debug, Clone, Serialize, Deserialize)]
485pub struct NeptuneExperimentConfig {
486    /// Log hyperparameters
487    pub log_hyperparameters: bool,
488    /// Log model summary
489    pub log_model_summary: bool,
490    /// Log datasets
491    pub log_datasets: bool,
492    /// Log artifacts
493    pub log_artifacts: bool,
494}
495
496/// ClearML integration configuration
497#[derive(Debug, Clone, Serialize, Deserialize)]
498pub struct ClearMLConfig {
499    /// Project name
500    pub project_name: String,
501    /// Task name
502    pub task_name: String,
503    /// Task type
504    pub task_type: ClearMLTaskType,
505    /// Auto-connect frameworks
506    pub auto_connect: AutoConnectConfig,
507    /// Output URI
508    pub output_uri: Option<String>,
509    /// Artifacts
510    pub artifacts: ClearMLArtifactConfig,
511}
512
513#[derive(Debug, Clone, Serialize, Deserialize)]
514pub enum ClearMLTaskType {
515    Training,
516    Testing,
517    Inference,
518    DataProcessing,
519    Application,
520    Monitor,
521    Controller,
522    Optimizer,
523    Service,
524    Custom,
525}
526
527#[derive(Debug, Clone, Serialize, Deserialize)]
528pub struct AutoConnectConfig {
529    /// Auto-connect frameworks
530    pub frameworks: bool,
531    /// Auto-connect arguments
532    pub arguments: bool,
533    /// Auto-connect models
534    pub models: bool,
535    /// Auto-connect artifacts
536    pub artifacts: bool,
537    /// Auto-connect datasets
538    pub datasets: bool,
539}
540
541#[derive(Debug, Clone, Serialize, Deserialize)]
542pub struct ClearMLArtifactConfig {
543    /// Upload artifacts
544    pub upload_artifacts: bool,
545    /// Artifact types to track
546    pub tracked_types: Vec<String>,
547    /// Compression
548    pub compression: Option<String>,
549}
550
551/// Experiment metadata
552#[derive(Debug, Clone, Serialize, Deserialize)]
553pub struct ExperimentMetadata {
554    /// Experiment ID
555    pub experiment_id: String,
556    /// Experiment name
557    pub name: String,
558    /// Description
559    pub description: Option<String>,
560    /// Start time
561    pub start_time: SystemTime,
562    /// End time
563    pub end_time: Option<SystemTime>,
564    /// Status
565    pub status: ExperimentStatus,
566    /// Tags
567    pub tags: Vec<String>,
568    /// Hyperparameters
569    pub hyperparameters: HashMap<String, ParameterValue>,
570    /// Metrics
571    pub metrics: HashMap<String, Vec<MetricValue>>,
572    /// Artifacts
573    pub artifacts: Vec<ArtifactInfo>,
574}
575
576#[derive(Debug, Clone, Serialize, Deserialize)]
577pub enum ExperimentStatus {
578    Running,
579    Completed,
580    Failed,
581    Cancelled,
582    Paused,
583}
584
585#[derive(Debug, Clone, Serialize, Deserialize)]
586pub enum ParameterValue {
587    Float(f64),
588    Int(i64),
589    String(String),
590    Bool(bool),
591    List(Vec<ParameterValue>),
592    Dict(HashMap<String, ParameterValue>),
593}
594
595#[derive(Debug, Clone, Serialize, Deserialize)]
596pub struct MetricValue {
597    /// Metric value
598    pub value: f64,
599    /// Step/epoch
600    pub step: usize,
601    /// Timestamp
602    pub timestamp: SystemTime,
603    /// Additional metadata
604    pub metadata: HashMap<String, String>,
605}
606
607#[derive(Debug, Clone, Serialize, Deserialize)]
608pub struct ArtifactInfo {
609    /// Artifact name
610    pub name: String,
611    /// Artifact type
612    pub artifact_type: String,
613    /// File path
614    pub path: PathBuf,
615    /// Size in bytes
616    pub size: u64,
617    /// Checksum
618    pub checksum: String,
619    /// Upload time
620    pub upload_time: SystemTime,
621    /// Metadata
622    pub metadata: HashMap<String, String>,
623}
624
625/// Trait for experiment tracking integrations
626pub trait ExperimentTracker: Send + Sync {
627    /// Initialize the tracker
628    fn initialize(&mut self) -> Result<()>;
629
630    /// Start a new experiment/run
631    fn start_experiment(&mut self, metadata: &ExperimentMetadata) -> Result<String>;
632
633    /// Log a parameter
634    fn log_parameter(&mut self, name: &str, value: ParameterValue) -> Result<()>;
635
636    /// Log a metric
637    fn log_metric(&mut self, name: &str, value: f64, step: Option<usize>) -> Result<()>;
638
639    /// Log multiple metrics
640    fn log_metrics(&mut self, metrics: HashMap<String, f64>, step: Option<usize>) -> Result<()>;
641
642    /// Log an artifact
643    fn log_artifact(&mut self, artifact: &ArtifactInfo) -> Result<()>;
644
645    /// Log a model
646    fn log_model(&mut self, model_path: &PathBuf, metadata: HashMap<String, String>) -> Result<()>;
647
648    /// Log system information
649    fn log_system_info(&mut self, info: HashMap<String, String>) -> Result<()>;
650
651    /// Update experiment status
652    fn update_status(&mut self, status: ExperimentStatus) -> Result<()>;
653
654    /// End the experiment
655    fn end_experiment(&mut self) -> Result<()>;
656
657    /// Get the integration name
658    fn name(&self) -> &str;
659
660    /// Sync with remote
661    fn sync(&mut self) -> Result<()>;
662}
663
664/// WandB integration implementation
665pub struct WandBTracker {
666    #[allow(dead_code)]
667    config: WandBConfig,
668    run_id: Option<String>,
669    initialized: bool,
670}
671
672impl WandBTracker {
673    pub fn new(config: WandBConfig) -> Self {
674        Self {
675            config,
676            run_id: None,
677            initialized: false,
678        }
679    }
680}
681
682impl ExperimentTracker for WandBTracker {
683    fn initialize(&mut self) -> Result<()> {
684        // Initialize WandB connection
685        // In real implementation, this would call wandb.init()
686        self.initialized = true;
687        Ok(())
688    }
689
690    fn start_experiment(&mut self, metadata: &ExperimentMetadata) -> Result<String> {
691        if !self.initialized {
692            self.initialize()?;
693        }
694
695        // Start a new WandB run
696        let run_id = format!("wandb_run_{}", metadata.experiment_id);
697        self.run_id = Some(run_id.clone());
698
699        // Log initial metadata
700        for (key, value) in &metadata.hyperparameters {
701            self.log_parameter(key, value.clone())?;
702        }
703
704        Ok(run_id)
705    }
706
707    fn log_parameter(&mut self, name: &str, value: ParameterValue) -> Result<()> {
708        // Log parameter to WandB
709        println!("WandB: Logging parameter {} = {:?}", name, value);
710        Ok(())
711    }
712
713    fn log_metric(&mut self, name: &str, value: f64, step: Option<usize>) -> Result<()> {
714        // Log metric to WandB
715        println!(
716            "WandB: Logging metric {} = {} at step {:?}",
717            name, value, step
718        );
719        Ok(())
720    }
721
722    fn log_metrics(&mut self, metrics: HashMap<String, f64>, step: Option<usize>) -> Result<()> {
723        for (name, value) in metrics {
724            self.log_metric(&name, value, step)?;
725        }
726        Ok(())
727    }
728
729    fn log_artifact(&mut self, artifact: &ArtifactInfo) -> Result<()> {
730        // Log artifact to WandB
731        println!("WandB: Logging artifact {}", artifact.name);
732        Ok(())
733    }
734
735    fn log_model(&mut self, model_path: &PathBuf, metadata: HashMap<String, String>) -> Result<()> {
736        // Log model to WandB
737        println!(
738            "WandB: Logging model at {:?} with metadata {:?}",
739            model_path, metadata
740        );
741        Ok(())
742    }
743
744    fn log_system_info(&mut self, info: HashMap<String, String>) -> Result<()> {
745        // Log system info to WandB
746        println!("WandB: Logging system info {:?}", info);
747        Ok(())
748    }
749
750    fn update_status(&mut self, status: ExperimentStatus) -> Result<()> {
751        // Update run status
752        println!("WandB: Updating status to {:?}", status);
753        Ok(())
754    }
755
756    fn end_experiment(&mut self) -> Result<()> {
757        // Finish WandB run
758        println!("WandB: Ending experiment");
759        self.run_id = None;
760        Ok(())
761    }
762
763    fn name(&self) -> &str {
764        "WandB"
765    }
766
767    fn sync(&mut self) -> Result<()> {
768        // Sync with WandB servers
769        println!("WandB: Syncing with servers");
770        Ok(())
771    }
772}
773
774/// MLflow integration implementation
775pub struct MLflowTracker {
776    #[allow(dead_code)]
777    config: MLflowConfig,
778    run_id: Option<String>,
779    initialized: bool,
780}
781
782impl MLflowTracker {
783    pub fn new(config: MLflowConfig) -> Self {
784        Self {
785            config,
786            run_id: None,
787            initialized: false,
788        }
789    }
790}
791
792impl ExperimentTracker for MLflowTracker {
793    fn initialize(&mut self) -> Result<()> {
794        // Initialize MLflow connection
795        self.initialized = true;
796        Ok(())
797    }
798
799    fn start_experiment(&mut self, metadata: &ExperimentMetadata) -> Result<String> {
800        if !self.initialized {
801            self.initialize()?;
802        }
803
804        let run_id = format!("mlflow_run_{}", metadata.experiment_id);
805        self.run_id = Some(run_id.clone());
806
807        Ok(run_id)
808    }
809
810    fn log_parameter(&mut self, name: &str, value: ParameterValue) -> Result<()> {
811        println!("MLflow: Logging parameter {} = {:?}", name, value);
812        Ok(())
813    }
814
815    fn log_metric(&mut self, name: &str, value: f64, step: Option<usize>) -> Result<()> {
816        println!(
817            "MLflow: Logging metric {} = {} at step {:?}",
818            name, value, step
819        );
820        Ok(())
821    }
822
823    fn log_metrics(&mut self, metrics: HashMap<String, f64>, step: Option<usize>) -> Result<()> {
824        for (name, value) in metrics {
825            self.log_metric(&name, value, step)?;
826        }
827        Ok(())
828    }
829
830    fn log_artifact(&mut self, artifact: &ArtifactInfo) -> Result<()> {
831        println!("MLflow: Logging artifact {}", artifact.name);
832        Ok(())
833    }
834
835    fn log_model(&mut self, model_path: &PathBuf, metadata: HashMap<String, String>) -> Result<()> {
836        println!(
837            "MLflow: Logging model at {:?} with metadata {:?}",
838            model_path, metadata
839        );
840        Ok(())
841    }
842
843    fn log_system_info(&mut self, info: HashMap<String, String>) -> Result<()> {
844        println!("MLflow: Logging system info {:?}", info);
845        Ok(())
846    }
847
848    fn update_status(&mut self, status: ExperimentStatus) -> Result<()> {
849        println!("MLflow: Updating status to {:?}", status);
850        Ok(())
851    }
852
853    fn end_experiment(&mut self) -> Result<()> {
854        println!("MLflow: Ending experiment");
855        self.run_id = None;
856        Ok(())
857    }
858
859    fn name(&self) -> &str {
860        "MLflow"
861    }
862
863    fn sync(&mut self) -> Result<()> {
864        println!("MLflow: Syncing with tracking server");
865        Ok(())
866    }
867}
868
869/// TensorBoard integration implementation
870pub struct TensorBoardTracker {
871    #[allow(dead_code)]
872    config: TensorBoardConfig,
873    log_dir: PathBuf,
874    initialized: bool,
875}
876
877impl TensorBoardTracker {
878    pub fn new(config: TensorBoardConfig) -> Self {
879        let log_dir = config.log_dir.clone();
880        Self {
881            config,
882            log_dir,
883            initialized: false,
884        }
885    }
886}
887
888impl ExperimentTracker for TensorBoardTracker {
889    fn initialize(&mut self) -> Result<()> {
890        // Initialize TensorBoard writer
891        std::fs::create_dir_all(&self.log_dir)?;
892        self.initialized = true;
893        Ok(())
894    }
895
896    fn start_experiment(&mut self, metadata: &ExperimentMetadata) -> Result<String> {
897        if !self.initialized {
898            self.initialize()?;
899        }
900
901        let run_id = format!("tensorboard_run_{}", metadata.experiment_id);
902        Ok(run_id)
903    }
904
905    fn log_parameter(&mut self, name: &str, value: ParameterValue) -> Result<()> {
906        println!("TensorBoard: Logging parameter {} = {:?}", name, value);
907        Ok(())
908    }
909
910    fn log_metric(&mut self, name: &str, value: f64, step: Option<usize>) -> Result<()> {
911        println!(
912            "TensorBoard: Logging metric {} = {} at step {:?}",
913            name, value, step
914        );
915        Ok(())
916    }
917
918    fn log_metrics(&mut self, metrics: HashMap<String, f64>, step: Option<usize>) -> Result<()> {
919        for (name, value) in metrics {
920            self.log_metric(&name, value, step)?;
921        }
922        Ok(())
923    }
924
925    fn log_artifact(&mut self, artifact: &ArtifactInfo) -> Result<()> {
926        println!("TensorBoard: Logging artifact {}", artifact.name);
927        Ok(())
928    }
929
930    fn log_model(&mut self, model_path: &PathBuf, metadata: HashMap<String, String>) -> Result<()> {
931        println!(
932            "TensorBoard: Logging model at {:?} with metadata {:?}",
933            model_path, metadata
934        );
935        Ok(())
936    }
937
938    fn log_system_info(&mut self, info: HashMap<String, String>) -> Result<()> {
939        println!("TensorBoard: Logging system info {:?}", info);
940        Ok(())
941    }
942
943    fn update_status(&mut self, status: ExperimentStatus) -> Result<()> {
944        println!("TensorBoard: Updating status to {:?}", status);
945        Ok(())
946    }
947
948    fn end_experiment(&mut self) -> Result<()> {
949        println!("TensorBoard: Ending experiment");
950        Ok(())
951    }
952
953    fn name(&self) -> &str {
954        "TensorBoard"
955    }
956
957    fn sync(&mut self) -> Result<()> {
958        println!("TensorBoard: Flushing logs to disk");
959        Ok(())
960    }
961}
962
963/// Neptune.ai experiment tracker
964pub struct NeptuneTracker {
965    config: NeptuneConfig,
966    run_id: Option<String>,
967    initialized: bool,
968}
969
970impl NeptuneTracker {
971    pub fn new(config: NeptuneConfig) -> Self {
972        Self {
973            config,
974            run_id: None,
975            initialized: false,
976        }
977    }
978}
979
980impl ExperimentTracker for NeptuneTracker {
981    fn initialize(&mut self) -> Result<()> {
982        println!(
983            "Neptune: Initializing connection to project: {}",
984            self.config.project
985        );
986        self.initialized = true;
987        Ok(())
988    }
989
990    fn start_experiment(&mut self, metadata: &ExperimentMetadata) -> Result<String> {
991        if !self.initialized {
992            self.initialize()?;
993        }
994
995        let run_id = format!("neptune_run_{}", metadata.experiment_id);
996        self.run_id = Some(run_id.clone());
997
998        println!(
999            "Neptune: Starting experiment {} with run ID: {}",
1000            metadata.experiment_id, run_id
1001        );
1002
1003        // Log initial metadata
1004        for (key, value) in &metadata.hyperparameters {
1005            self.log_parameter(key, value.clone())?;
1006        }
1007
1008        // Log tags
1009        for tag in &self.config.tags {
1010            println!("Neptune: Adding tag: {}", tag);
1011        }
1012
1013        Ok(run_id)
1014    }
1015
1016    fn log_parameter(&mut self, name: &str, value: ParameterValue) -> Result<()> {
1017        println!("Neptune: Logging parameter {} = {:?}", name, value);
1018        Ok(())
1019    }
1020
1021    fn log_metric(&mut self, name: &str, value: f64, step: Option<usize>) -> Result<()> {
1022        println!(
1023            "Neptune: Logging metric {} = {} at step {:?}",
1024            name, value, step
1025        );
1026        Ok(())
1027    }
1028
1029    fn log_metrics(&mut self, metrics: HashMap<String, f64>, step: Option<usize>) -> Result<()> {
1030        for (name, value) in metrics {
1031            self.log_metric(&name, value, step)?;
1032        }
1033        Ok(())
1034    }
1035
1036    fn log_artifact(&mut self, artifact: &ArtifactInfo) -> Result<()> {
1037        println!(
1038            "Neptune: Logging artifact: {} ({})",
1039            artifact.name, artifact.artifact_type
1040        );
1041        Ok(())
1042    }
1043
1044    fn log_model(&mut self, model_path: &PathBuf, metadata: HashMap<String, String>) -> Result<()> {
1045        println!("Neptune: Logging model from path: {:?}", model_path);
1046        for (key, value) in metadata {
1047            println!("Neptune: Model metadata - {}: {}", key, value);
1048        }
1049        Ok(())
1050    }
1051
1052    fn log_system_info(&mut self, info: HashMap<String, String>) -> Result<()> {
1053        println!("Neptune: Logging system information");
1054        for (key, value) in info {
1055            println!("Neptune: System info - {}: {}", key, value);
1056        }
1057        Ok(())
1058    }
1059
1060    fn update_status(&mut self, status: ExperimentStatus) -> Result<()> {
1061        println!("Neptune: Updating experiment status to {:?}", status);
1062        Ok(())
1063    }
1064
1065    fn end_experiment(&mut self) -> Result<()> {
1066        if let Some(run_id) = &self.run_id {
1067            println!("Neptune: Ending experiment with run ID: {}", run_id);
1068        } else {
1069            println!("Neptune: Ending experiment (no active run)");
1070        }
1071        self.run_id = None;
1072        Ok(())
1073    }
1074
1075    fn name(&self) -> &str {
1076        "Neptune"
1077    }
1078
1079    fn sync(&mut self) -> Result<()> {
1080        println!("Neptune: Syncing with Neptune.ai servers");
1081        Ok(())
1082    }
1083}
1084
1085/// ClearML experiment tracker
1086pub struct ClearMLTracker {
1087    config: ClearMLConfig,
1088    task_id: Option<String>,
1089    initialized: bool,
1090}
1091
1092impl ClearMLTracker {
1093    pub fn new(config: ClearMLConfig) -> Self {
1094        Self {
1095            config,
1096            task_id: None,
1097            initialized: false,
1098        }
1099    }
1100}
1101
1102impl ExperimentTracker for ClearMLTracker {
1103    fn initialize(&mut self) -> Result<()> {
1104        println!(
1105            "ClearML: Initializing connection to project: {}",
1106            self.config.project_name
1107        );
1108        self.initialized = true;
1109        Ok(())
1110    }
1111
1112    fn start_experiment(&mut self, metadata: &ExperimentMetadata) -> Result<String> {
1113        if !self.initialized {
1114            self.initialize()?;
1115        }
1116
1117        let task_id = format!("clearml_task_{}", metadata.experiment_id);
1118        self.task_id = Some(task_id.clone());
1119
1120        println!(
1121            "ClearML: Starting task {} of type {:?} with task ID: {}",
1122            self.config.task_name, self.config.task_type, task_id
1123        );
1124
1125        // Log initial metadata
1126        for (key, value) in &metadata.hyperparameters {
1127            self.log_parameter(key, value.clone())?;
1128        }
1129
1130        Ok(task_id)
1131    }
1132
1133    fn log_parameter(&mut self, name: &str, value: ParameterValue) -> Result<()> {
1134        println!("ClearML: Logging parameter {} = {:?}", name, value);
1135        Ok(())
1136    }
1137
1138    fn log_metric(&mut self, name: &str, value: f64, step: Option<usize>) -> Result<()> {
1139        println!(
1140            "ClearML: Logging metric {} = {} at step {:?}",
1141            name, value, step
1142        );
1143        Ok(())
1144    }
1145
1146    fn log_metrics(&mut self, metrics: HashMap<String, f64>, step: Option<usize>) -> Result<()> {
1147        for (name, value) in metrics {
1148            self.log_metric(&name, value, step)?;
1149        }
1150        Ok(())
1151    }
1152
1153    fn log_artifact(&mut self, artifact: &ArtifactInfo) -> Result<()> {
1154        println!(
1155            "ClearML: Logging artifact: {} ({})",
1156            artifact.name, artifact.artifact_type
1157        );
1158        if self
1159            .config
1160            .artifacts
1161            .tracked_types
1162            .contains(&artifact.artifact_type.to_string())
1163        {
1164            println!("ClearML: Auto-tracking {} artifact", artifact.artifact_type);
1165        }
1166        Ok(())
1167    }
1168
1169    fn log_model(&mut self, model_path: &PathBuf, metadata: HashMap<String, String>) -> Result<()> {
1170        println!("ClearML: Logging model from path: {:?}", model_path);
1171        for (key, value) in metadata {
1172            println!("ClearML: Model metadata - {}: {}", key, value);
1173        }
1174        Ok(())
1175    }
1176
1177    fn log_system_info(&mut self, info: HashMap<String, String>) -> Result<()> {
1178        println!("ClearML: Logging system information");
1179        for (key, value) in info {
1180            println!("ClearML: System info - {}: {}", key, value);
1181        }
1182        Ok(())
1183    }
1184
1185    fn update_status(&mut self, status: ExperimentStatus) -> Result<()> {
1186        println!("ClearML: Updating task status to {:?}", status);
1187        Ok(())
1188    }
1189
1190    fn end_experiment(&mut self) -> Result<()> {
1191        if let Some(task_id) = &self.task_id {
1192            println!("ClearML: Completing task with ID: {}", task_id);
1193        } else {
1194            println!("ClearML: Completing task (no active task)");
1195        }
1196        self.task_id = None;
1197        Ok(())
1198    }
1199
1200    fn name(&self) -> &str {
1201        "ClearML"
1202    }
1203
1204    fn sync(&mut self) -> Result<()> {
1205        println!("ClearML: Syncing with ClearML servers");
1206        Ok(())
1207    }
1208}
1209
1210impl FrameworkIntegrationManager {
1211    pub fn new(config: IntegrationConfig) -> Self {
1212        Self {
1213            integrations: Arc::new(Mutex::new(HashMap::new())),
1214            config,
1215            experiment_metadata: Arc::new(Mutex::new(ExperimentMetadata::default())),
1216        }
1217    }
1218
1219    pub fn add_integration(&self, integration_type: IntegrationType) -> Result<()> {
1220        let mut integrations = self.integrations.lock().expect("lock should not be poisoned");
1221
1222        let tracker: Box<dyn ExperimentTracker> = match integration_type {
1223            IntegrationType::WandB { config } => Box::new(WandBTracker::new(config)),
1224            IntegrationType::MLflow { config } => Box::new(MLflowTracker::new(config)),
1225            IntegrationType::TensorBoard { config } => Box::new(TensorBoardTracker::new(config)),
1226            IntegrationType::Neptune { config } => Box::new(NeptuneTracker::new(config)),
1227            IntegrationType::ClearML { config } => Box::new(ClearMLTracker::new(config)),
1228            IntegrationType::Custom { name, config: _ } => {
1229                return Err(anyhow!("Custom integration '{}' not implemented", name));
1230            },
1231        };
1232
1233        let integration_name = tracker.name().to_string();
1234        integrations.insert(integration_name, tracker);
1235
1236        Ok(())
1237    }
1238
1239    pub fn start_experiment(&self, name: &str, description: Option<String>) -> Result<String> {
1240        let experiment_id = uuid::Uuid::new_v4().to_string();
1241
1242        let metadata = ExperimentMetadata {
1243            experiment_id: experiment_id.clone(),
1244            name: name.to_string(),
1245            description,
1246            start_time: SystemTime::now(),
1247            end_time: None,
1248            status: ExperimentStatus::Running,
1249            tags: vec![],
1250            hyperparameters: HashMap::new(),
1251            metrics: HashMap::new(),
1252            artifacts: vec![],
1253        };
1254
1255        // Update stored metadata
1256        {
1257            let mut stored_metadata =
1258                self.experiment_metadata.lock().expect("lock should not be poisoned");
1259            *stored_metadata = metadata.clone();
1260        }
1261
1262        // Start experiment in all integrations
1263        let mut integrations = self.integrations.lock().expect("lock should not be poisoned");
1264        for (_, tracker) in integrations.iter_mut() {
1265            tracker.start_experiment(&metadata)?;
1266        }
1267
1268        Ok(experiment_id)
1269    }
1270
1271    pub fn log_hyperparameters(&self, parameters: HashMap<String, ParameterValue>) -> Result<()> {
1272        // Update metadata
1273        {
1274            let mut metadata =
1275                self.experiment_metadata.lock().expect("lock should not be poisoned");
1276            metadata.hyperparameters.extend(parameters.clone());
1277        }
1278
1279        // Log to all integrations
1280        let mut integrations = self.integrations.lock().expect("lock should not be poisoned");
1281        for (_, tracker) in integrations.iter_mut() {
1282            for (name, value) in &parameters {
1283                tracker.log_parameter(name, value.clone())?;
1284            }
1285        }
1286
1287        Ok(())
1288    }
1289
1290    pub fn log_metrics(&self, metrics: HashMap<String, f64>, step: Option<usize>) -> Result<()> {
1291        // Update metadata
1292        {
1293            let mut metadata =
1294                self.experiment_metadata.lock().expect("lock should not be poisoned");
1295            for (name, value) in &metrics {
1296                let metric_value = MetricValue {
1297                    value: *value,
1298                    step: step.unwrap_or(0),
1299                    timestamp: SystemTime::now(),
1300                    metadata: HashMap::new(),
1301                };
1302                metadata.metrics.entry(name.clone()).or_default().push(metric_value);
1303            }
1304        }
1305
1306        // Log to all integrations
1307        let mut integrations = self.integrations.lock().expect("lock should not be poisoned");
1308        for (_, tracker) in integrations.iter_mut() {
1309            tracker.log_metrics(metrics.clone(), step)?;
1310        }
1311
1312        Ok(())
1313    }
1314
1315    pub fn log_artifact(&self, name: &str, path: &PathBuf, artifact_type: &str) -> Result<()> {
1316        let artifact = ArtifactInfo {
1317            name: name.to_string(),
1318            artifact_type: artifact_type.to_string(),
1319            path: path.clone(),
1320            size: std::fs::metadata(path)?.len(),
1321            checksum: "".to_string(), // Would compute actual checksum
1322            upload_time: SystemTime::now(),
1323            metadata: HashMap::new(),
1324        };
1325
1326        // Update metadata
1327        {
1328            let mut metadata =
1329                self.experiment_metadata.lock().expect("lock should not be poisoned");
1330            metadata.artifacts.push(artifact.clone());
1331        }
1332
1333        // Log to all integrations
1334        let mut integrations = self.integrations.lock().expect("lock should not be poisoned");
1335        for (_, tracker) in integrations.iter_mut() {
1336            tracker.log_artifact(&artifact)?;
1337        }
1338
1339        Ok(())
1340    }
1341
1342    pub fn end_experiment(&self) -> Result<()> {
1343        // Update metadata
1344        {
1345            let mut metadata =
1346                self.experiment_metadata.lock().expect("lock should not be poisoned");
1347            metadata.end_time = Some(SystemTime::now());
1348            metadata.status = ExperimentStatus::Completed;
1349        }
1350
1351        // End experiment in all integrations
1352        let mut integrations = self.integrations.lock().expect("lock should not be poisoned");
1353        for (_, tracker) in integrations.iter_mut() {
1354            tracker.end_experiment()?;
1355        }
1356
1357        Ok(())
1358    }
1359
1360    pub fn sync_all(&self) -> Result<()> {
1361        let mut integrations = self.integrations.lock().expect("lock should not be poisoned");
1362        for (_, tracker) in integrations.iter_mut() {
1363            tracker.sync()?;
1364        }
1365        Ok(())
1366    }
1367}
1368
1369impl Default for ExperimentMetadata {
1370    fn default() -> Self {
1371        Self {
1372            experiment_id: "".to_string(),
1373            name: "".to_string(),
1374            description: None,
1375            start_time: SystemTime::now(),
1376            end_time: None,
1377            status: ExperimentStatus::Running,
1378            tags: vec![],
1379            hyperparameters: HashMap::new(),
1380            metrics: HashMap::new(),
1381            artifacts: vec![],
1382        }
1383    }
1384}
1385
1386#[cfg(test)]
1387mod tests {
1388    use super::*;
1389
1390    #[test]
1391    fn test_framework_integration_manager() {
1392        let config = IntegrationConfig {
1393            enabled_integrations: vec![],
1394            default_integration: None,
1395            sync_config: SyncConfig {
1396                sync_metrics: true,
1397                sync_artifacts: true,
1398                sync_frequency: SyncFrequency::RealTime,
1399                conflict_resolution: ConflictResolution::LastWins,
1400            },
1401            export_config: ExportConfig {
1402                formats: vec![ExportFormat::JSON],
1403                frequency: ExportFrequency::EndOfTraining,
1404                output_dir: PathBuf::from("/tmp/exports"),
1405            },
1406        };
1407
1408        let manager = FrameworkIntegrationManager::new(config);
1409        assert!(manager.integrations.lock().expect("lock should not be poisoned").is_empty());
1410    }
1411
1412    #[test]
1413    fn test_wandb_tracker() {
1414        let config = WandBConfig {
1415            project: "test-project".to_string(),
1416            entity: None,
1417            run_name: None,
1418            group: None,
1419            job_type: None,
1420            tags: vec![],
1421            api_key: None,
1422            offline: true,
1423            resume: ResumeConfig::Never,
1424            artifacts: ArtifactConfig {
1425                track_models: true,
1426                track_datasets: true,
1427                track_code: true,
1428                custom_artifacts: vec![],
1429            },
1430            advanced: WandBAdvancedConfig {
1431                log_system_metrics: true,
1432                log_code: true,
1433                save_code: true,
1434                watch_model: WatchModelConfig {
1435                    enabled: false,
1436                    log_freq: 100,
1437                    log_gradients: false,
1438                    log_parameters: false,
1439                    log_graph: false,
1440                },
1441                custom_metrics: vec![],
1442            },
1443        };
1444
1445        let tracker = WandBTracker::new(config);
1446        assert_eq!(tracker.name(), "WandB");
1447        assert!(!tracker.initialized);
1448    }
1449
1450    #[test]
1451    fn test_mlflow_tracker() {
1452        let config = MLflowConfig {
1453            tracking_uri: "http://localhost:5000".to_string(),
1454            experiment_name: "test-experiment".to_string(),
1455            run_name: None,
1456            registry_uri: None,
1457            artifact_location: None,
1458            auth: MLflowAuth {
1459                auth_type: MLflowAuthType::None,
1460                credentials: HashMap::new(),
1461            },
1462            model_registration: ModelRegistrationConfig {
1463                auto_register: false,
1464                model_name: "test-model".to_string(),
1465                stage: ModelStage::None,
1466                description: None,
1467                tags: HashMap::new(),
1468            },
1469            advanced: MLflowAdvancedConfig {
1470                log_system_metrics: true,
1471                autolog_parameters: true,
1472                autolog_metrics: true,
1473                autolog_artifacts: true,
1474                nested_runs: false,
1475            },
1476        };
1477
1478        let tracker = MLflowTracker::new(config);
1479        assert_eq!(tracker.name(), "MLflow");
1480        assert!(!tracker.initialized);
1481    }
1482
1483    #[test]
1484    fn test_tensorboard_tracker() {
1485        let config = TensorBoardConfig {
1486            log_dir: PathBuf::from("/tmp/tensorboard"),
1487            experiment_name: "test-experiment".to_string(),
1488            update_freq: UpdateFrequency::Steps(100),
1489            histograms: HistogramConfig {
1490                enabled: true,
1491                log_weights: true,
1492                log_gradients: true,
1493                log_activations: false,
1494                bucket_count: 50,
1495            },
1496            images: ImageLoggingConfig {
1497                enabled: false,
1498                max_images: 10,
1499                image_size: (224, 224),
1500                color_format: ColorFormat::RGB,
1501            },
1502            audio: AudioLoggingConfig {
1503                enabled: false,
1504                sample_rate: 22050,
1505                max_duration: 10.0,
1506            },
1507            graph: GraphLoggingConfig {
1508                enabled: true,
1509                profile_execution: false,
1510                log_device_placement: false,
1511            },
1512            advanced: TensorBoardAdvancedConfig {
1513                profiling: ProfilingConfig {
1514                    enabled: false,
1515                    profile_steps: vec![],
1516                    profile_memory: false,
1517                    profile_operators: false,
1518                },
1519                custom_scalars: vec![],
1520                mesh_visualization: false,
1521            },
1522        };
1523
1524        let tracker = TensorBoardTracker::new(config);
1525        assert_eq!(tracker.name(), "TensorBoard");
1526        assert!(!tracker.initialized);
1527    }
1528}
trustformers_training/framework_integration.rs

trustformers_training/
framework_integration.rs
