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rustytorch/crates/models/rtx-multimodal/src/multimodal_preprocessing.rs
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2026-03-04 00:08:42 +00:00

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Rust

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