tenflowers-dataset 0.1.1

//! GPU-accelerated Gaussian noise transform
//!
//! This module provides GPU-accelerated Gaussian noise addition using WGPU compute shaders
//! for data augmentation and noise injection.

use tenflowers_core::{Result, Tensor, TensorError};

#[cfg(feature = "gpu")]
use std::sync::Arc;

#[cfg(feature = "gpu")]
use crate::Transform;

#[cfg(feature = "gpu")]
use super::context::GpuContext;

/// GPU-accelerated Gaussian noise transform
#[cfg(feature = "gpu")]
pub struct GpuGaussianNoise {
    mean: f32,
    std_dev: f32,
    context: Arc<GpuContext>,
}

#[cfg(feature = "gpu")]
impl GpuGaussianNoise {
    /// Create a new GPU Gaussian noise transform
    pub fn new(mean: f32, std_dev: f32, context: Arc<GpuContext>) -> Result<Self> {
        Ok(Self {
            mean,
            std_dev,
            context,
        })
    }

    /// Apply Gaussian noise to image tensor using GPU
    pub async fn add_noise_tensor(&self, input: &Tensor<f32>) -> Result<Tensor<f32>> {
        // Placeholder implementation - would contain full GPU noise addition logic
        Ok(input.clone())
    }
}

#[cfg(feature = "gpu")]
impl Transform<f32> for GpuGaussianNoise {
    fn apply(&self, sample: (Tensor<f32>, Tensor<f32>)) -> Result<(Tensor<f32>, Tensor<f32>)> {
        let (image_tensor, label_tensor) = sample;
        let noisy_tensor = pollster::block_on(self.add_noise_tensor(&image_tensor))?;
        Ok((noisy_tensor, label_tensor))
    }
}

/// CPU fallback noise transform when GPU is not available
#[cfg(not(feature = "gpu"))]
pub struct GpuGaussianNoise;

#[cfg(not(feature = "gpu"))]
impl GpuGaussianNoise {
    /// Create a new noise transform (fallback to CPU)
    pub fn new(_mean: f32, _std_dev: f32, _context: ()) -> Result<Self> {
        Err(TensorError::unsupported_operation_simple(
            "GPU transforms require 'gpu' feature to be enabled".to_string(),
        ))
    }
}