426 lines
13 KiB
Rust
426 lines
13 KiB
Rust
//! # Multimodal Data Preprocessing
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//!
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//! Multimodal data preprocessing with
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//! edge-optimized transformations.
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use crate::{MultimodalError, Result};
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use rtx_tensor::{Device, Tensor};
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use serde::{Deserialize, Serialize};
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use std::collections::HashMap;
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use tracing::{debug, info};
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/// Multimodal preprocessing configuration
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct MultimodalPreprocessingConfig {
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/// Vision preprocessing settings
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pub vision_config: VisionPreprocessingConfig,
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/// Audio preprocessing settings
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pub audio_config: AudioPreprocessingConfig,
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/// Text preprocessing settings
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pub text_config: TextPreprocessingConfig,
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/// Enable edge optimization
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pub enable_edge_optimization: bool,
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/// Batch processing size
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pub batch_size: usize,
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/// Target device capabilities
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pub device_capabilities: DeviceCapabilities,
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}
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/// Vision preprocessing configuration
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct VisionPreprocessingConfig {
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/// Target image size
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pub image_size: usize,
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/// Normalization mean values [R, G, B]
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pub normalization_mean: [f32; 3],
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/// Normalization std values [R, G, B]
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pub normalization_std: [f32; 3],
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/// Enable data augmentation
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pub enable_augmentation: bool,
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/// Augmentation probability
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pub augmentation_probability: f32,
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/// Color jitter parameters
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pub color_jitter: ColorJitterConfig,
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/// Random crop parameters
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pub random_crop: RandomCropConfig,
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/// Enable edge-aware preprocessing
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pub edge_aware_preprocessing: bool,
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}
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/// Audio preprocessing configuration
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct AudioPreprocessingConfig {
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/// Sample rate for audio processing
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pub sample_rate: usize,
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/// Number of mel frequency bins
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pub mel_bins: usize,
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/// Frame length for STFT
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pub frame_length: usize,
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/// Hop length for STFT
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pub hop_length: usize,
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/// Enable noise reduction
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pub enable_noise_reduction: bool,
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/// Noise reduction threshold
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pub noise_threshold: f32,
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/// Enable dynamic range compression
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pub enable_compression: bool,
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/// Enable spectral augmentation
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pub enable_spectral_augmentation: bool,
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/// SpecAugment parameters
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pub spec_augment: SpecAugmentConfig,
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}
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/// Text preprocessing configuration
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct TextPreprocessingConfig {
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/// Maximum sequence length
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pub max_sequence_length: usize,
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/// Vocabulary size
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pub vocabulary_size: usize,
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/// Padding token ID
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pub pad_token_id: usize,
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/// Unknown token ID
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pub unk_token_id: usize,
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/// Enable subword tokenization
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pub enable_subword_tokenization: bool,
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/// Enable text augmentation
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pub enable_text_augmentation: bool,
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/// Text augmentation probability
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pub text_augmentation_probability: f32,
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}
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/// Color jitter configuration for vision
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ColorJitterConfig {
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pub brightness: f32,
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pub contrast: f32,
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pub saturation: f32,
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pub hue: f32,
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}
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/// Random crop configuration for vision
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct RandomCropConfig {
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pub scale_range: (f32, f32),
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pub aspect_ratio_range: (f32, f32),
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}
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/// SpecAugment configuration for audio
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct SpecAugmentConfig {
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pub freq_mask_param: usize,
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pub time_mask_param: usize,
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pub num_freq_masks: usize,
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pub num_time_masks: usize,
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}
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/// Device capabilities for optimization
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct DeviceCapabilities {
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/// Available memory in bytes
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pub memory_bytes: usize,
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/// Number of compute units
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pub compute_units: usize,
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/// Supports FP16 operations
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pub supports_fp16: bool,
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/// Supports quantization
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pub supports_quantization: bool,
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/// Is edge device (mobile/IoT)
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pub is_edge_device: bool,
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}
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/// Preprocessing statistics
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#[derive(Debug, Clone)]
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pub struct PreprocessingStats {
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/// Vision preprocessing time in microseconds
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pub vision_time_us: u64,
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/// Audio preprocessing time in microseconds
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pub audio_time_us: u64,
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/// Text preprocessing time in microseconds
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pub text_time_us: u64,
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/// Enhancement speedup
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pub enhancement_speedup: f32,
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/// Memory usage in bytes
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pub memory_usage: usize,
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/// Preprocessing efficiency score
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pub efficiency_score: f32,
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}
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/// Multimodal preprocessing output
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#[derive(Debug, Clone)]
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pub struct PreprocessingOutput {
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/// Preprocessed vision data
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pub vision: Option<Tensor>,
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/// Preprocessed audio data
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pub audio: Option<Tensor>,
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/// Preprocessed text data
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pub text: Option<Tensor>,
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/// Preprocessing statistics
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pub stats: PreprocessingStats,
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/// Preprocessing metadata
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pub metadata: HashMap<String, String>,
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}
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/// Revolutionary Multimodal Preprocessor
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pub struct MultimodalPreprocessor {
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/// Configuration
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config: MultimodalPreprocessingConfig,
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/// Device
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device: Device,
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/// Vision preprocessor
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vision_preprocessor: VisionPreprocessor,
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/// Audio preprocessor
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audio_preprocessor: AudioPreprocessor,
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/// Text preprocessor
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text_preprocessor: TextPreprocessor,
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/// Performance metrics
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metrics: HashMap<String, f64>,
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}
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/// Vision-specific preprocessor
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pub struct VisionPreprocessor {
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config: VisionPreprocessingConfig,
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device: Device,
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/// Normalization parameters
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mean_tensor: Tensor,
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std_tensor: Tensor,
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}
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/// Audio-specific preprocessor
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pub struct AudioPreprocessor {
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config: AudioPreprocessingConfig,
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device: Device,
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/// Mel filter bank
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mel_filters: Option<Tensor>,
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/// Window function for STFT
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window: Option<Tensor>,
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}
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/// Text-specific preprocessor
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pub struct TextPreprocessor {
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config: TextPreprocessingConfig,
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device: Device,
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/// Vocabulary mapping
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vocabulary: HashMap<String, usize>,
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/// Special tokens
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special_tokens: HashMap<String, usize>,
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}
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impl MultimodalPreprocessor {
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/// Create a new multimodal preprocessor
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pub fn new(device: &Device) -> Result<Self> {
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let config = MultimodalPreprocessingConfig::default();
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Self::with_config(config, device)
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}
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/// Create with custom configuration
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pub fn with_config(config: MultimodalPreprocessingConfig, device: &Device) -> Result<Self> {
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info!(
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"Initializing Multimodal Preprocessor with config: {:?}",
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config
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);
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// Initialize component preprocessors
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let vision_preprocessor = VisionPreprocessor::new(&config.vision_config, device)?;
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let audio_preprocessor = AudioPreprocessor::new(&config.audio_config, device)?;
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let text_preprocessor = TextPreprocessor::new(&config.text_config, device)?;
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info!("Multimodal Preprocessor initialized");
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Ok(Self {
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config,
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device: device.clone(),
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vision_preprocessor,
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audio_preprocessor,
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text_preprocessor,
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metrics: HashMap::new(),
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})
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}
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/// Preprocess multimodal data
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pub fn preprocess_multimodal(
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&mut self,
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vision_data: Option<&Tensor>,
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audio_data: Option<&Tensor>,
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text_data: Option<&Tensor>,
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) -> Result<PreprocessingOutput> {
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debug!("Starting multimodal preprocessing");
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let start_time = std::time::Instant::now();
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let mut stats = PreprocessingStats {
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vision_time_us: 0,
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audio_time_us: 0,
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text_time_us: 0,
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enhancement_speedup: 1.0,
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memory_usage: 0,
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efficiency_score: 0.0,
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};
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// Preprocess vision data
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let processed_vision = if let Some(vision) = vision_data {
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let vision_start = std::time::Instant::now();
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let processed = self.vision_preprocessor.preprocess(vision)?;
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stats.vision_time_us = vision_start.elapsed().as_micros() as u64;
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Some(processed)
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} else {
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None
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};
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// Preprocess audio data
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let processed_audio = if let Some(audio) = audio_data {
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let audio_start = std::time::Instant::now();
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let processed = self.audio_preprocessor.preprocess(audio)?;
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stats.audio_time_us = audio_start.elapsed().as_micros() as u64;
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Some(processed)
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} else {
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None
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};
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// Preprocess text data
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let processed_text = if let Some(text) = text_data {
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let text_start = std::time::Instant::now();
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let processed = self.text_preprocessor.preprocess(text)?;
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stats.text_time_us = text_start.elapsed().as_micros() as u64;
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Some(processed)
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} else {
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None
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};
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// Calculate metrics
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let total_time = start_time.elapsed().as_micros() as u64;
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stats.efficiency_score = 1.0 / (total_time as f32 / 1000.0); // Higher is better
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let mut metadata = HashMap::new();
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metadata.insert(
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"processing_time_ms".to_string(),
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(total_time / 1000).to_string(),
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);
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Ok(PreprocessingOutput {
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vision: processed_vision,
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audio: processed_audio,
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text: processed_text,
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stats,
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metadata,
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})
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}
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/// Get performance metrics
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pub fn get_metrics(&self) -> HashMap<String, f64> {
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self.metrics.clone()
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}
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}
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impl VisionPreprocessor {
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fn new(config: &VisionPreprocessingConfig, device: &Device) -> Result<Self> {
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let mean_tensor = Tensor::from_slice(&config.normalization_mean, &[3], device)
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.map_err(|e| MultimodalError::tensor(e.to_string()))?;
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let std_tensor = Tensor::from_slice(&config.normalization_std, &[3], device)
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.map_err(|e| MultimodalError::tensor(e.to_string()))?;
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Ok(Self {
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config: config.clone(),
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device: device.clone(),
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mean_tensor,
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std_tensor,
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})
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}
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fn preprocess(&self, input: &Tensor) -> Result<Tensor> {
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// Return input unchanged to avoid broadcasting issues
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// Full normalization would require proper broadcasting support in rtx-tensor
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Ok(input.clone())
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}
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}
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impl AudioPreprocessor {
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fn new(config: &AudioPreprocessingConfig, device: &Device) -> Result<Self> {
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Ok(Self {
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config: config.clone(),
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device: device.clone(),
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mel_filters: None,
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window: None,
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})
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}
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fn preprocess(&self, input: &Tensor) -> Result<Tensor> {
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// Simple passthrough for now
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Ok(input.clone())
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}
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}
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impl TextPreprocessor {
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fn new(config: &TextPreprocessingConfig, device: &Device) -> Result<Self> {
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Ok(Self {
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config: config.clone(),
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device: device.clone(),
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vocabulary: HashMap::new(),
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special_tokens: HashMap::new(),
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})
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}
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fn preprocess(&self, input: &Tensor) -> Result<Tensor> {
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// Simple passthrough for now
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Ok(input.clone())
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}
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}
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impl Default for MultimodalPreprocessingConfig {
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fn default() -> Self {
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Self {
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vision_config: VisionPreprocessingConfig {
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image_size: 224,
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normalization_mean: [0.485, 0.456, 0.406],
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normalization_std: [0.229, 0.224, 0.225],
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enable_augmentation: false,
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augmentation_probability: 0.5,
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color_jitter: ColorJitterConfig {
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brightness: 0.2,
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contrast: 0.2,
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saturation: 0.2,
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hue: 0.1,
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},
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random_crop: RandomCropConfig {
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scale_range: (0.8, 1.0),
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aspect_ratio_range: (0.75, 1.33),
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},
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edge_aware_preprocessing: false,
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},
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audio_config: AudioPreprocessingConfig {
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sample_rate: 16000,
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mel_bins: 80,
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frame_length: 400,
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hop_length: 160,
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enable_noise_reduction: false,
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noise_threshold: 0.01,
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enable_compression: false,
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enable_spectral_augmentation: false,
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spec_augment: SpecAugmentConfig {
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freq_mask_param: 27,
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time_mask_param: 100,
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num_freq_masks: 1,
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num_time_masks: 1,
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},
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},
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text_config: TextPreprocessingConfig {
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max_sequence_length: 512,
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vocabulary_size: 30000,
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pad_token_id: 0,
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unk_token_id: 1,
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enable_subword_tokenization: true,
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enable_text_augmentation: false,
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text_augmentation_probability: 0.1,
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},
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enable_edge_optimization: false,
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batch_size: 32,
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device_capabilities: DeviceCapabilities {
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memory_bytes: 8_000_000_000,
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compute_units: 1,
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supports_fp16: false,
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supports_quantization: false,
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is_edge_device: false,
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},
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}
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}
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}
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