quantrs2-device 0.1.3

Quantum device connectors for the QuantRS2 framework
Documentation 
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//! # DummyMLModel - Trait Implementations
//!
//! This module contains trait implementations for `DummyMLModel`.
//!
//! ## Implemented Traits
//!
//! - `MLModel`
//!
//! 🤖 Generated with [SplitRS](https://github.com/cool-japan/splitrs)

use async_trait::async_trait;
use chrono::Utc;
use std::collections::HashMap;
use std::time::Duration;

use super::type_definitions::*;
use crate::quantum_network::distributed_protocols::TrainingDataPoint;

#[async_trait]
impl MLModel for DummyMLModel {
    async fn predict(&self, _features: &FeatureVector) -> Result<PredictionResult> {
        Ok(PredictionResult {
            predicted_values: HashMap::new(),
            confidence_intervals: HashMap::new(),
            uncertainty_estimate: 0.1,
            prediction_timestamp: Utc::now(),
        })
    }
    async fn train(&mut self, _training_data: &[TrainingDataPoint]) -> Result<TrainingResult> {
        Ok(TrainingResult {
            training_accuracy: 0.8,
            validation_accuracy: 0.75,
            loss_value: 0.2,
            training_duration: Duration::from_secs(100),
            model_size_bytes: 1024,
        })
    }
    async fn update_weights(&mut self, _feedback: &FeedbackData) -> Result<()> {
        Ok(())
    }
    fn get_model_metrics(&self) -> ModelMetrics {
        ModelMetrics {
            accuracy: 0.8,
            precision: 0.8,
            recall: 0.8,
            f1_score: 0.8,
            mae: 0.1,
            rmse: 0.1,
        }
    }
}