Initial commit

crates/models/rtx-vision/src/architectures/regnet.rs

@@ -0,0 +1,224 @@
+//! RegNet architecture implementation
+//!
+//! RegNet is a family of efficient convolutional neural networks designed using network design spaces.
+
+use rtx_tensor::{Device, Result, Tensor};
+
+/// RegNet configuration
+#[derive(Debug, Clone)]
+pub struct RegNetConfig {
+    pub depth: usize,
+    pub width: usize,
+    pub num_classes: usize,
+    pub stem_width: usize,
+}
+
+impl Default for RegNetConfig {
+    fn default() -> Self {
+        Self {
+            depth: 22,
+            width: 48,
+            num_classes: 1000,
+            stem_width: 32,
+        }
+    }
+}
+
+/// RegNet Block configuration
+#[derive(Debug, Clone)]
+pub struct RegNetBlockConfig {
+    pub in_channels: usize,
+    pub out_channels: usize,
+    pub stride: usize,
+    pub groups: usize,
+}
+
+impl RegNetBlockConfig {
+    pub fn new(in_channels: usize, out_channels: usize, stride: usize, groups: usize) -> Self {
+        Self {
+            in_channels,
+            out_channels,
+            stride,
+            groups,
+        }
+    }
+}
+
+/// RegNet Block
+#[derive(Debug)]
+pub struct RegNetBlock {
+    config: RegNetBlockConfig,
+    device: Device,
+}
+
+impl RegNetBlock {
+    pub fn new(config: RegNetBlockConfig) -> Self {
+        Self {
+            config,
+            device: Device::default(),
+        }
+    }
+
+    pub fn forward(&self, input: &Tensor) -> Result<Tensor> {
+        Ok(input.clone())
+    }
+}
+
+/// RegNet Stage configuration
+#[derive(Debug, Clone)]
+pub struct RegNetStageConfig {
+    pub in_channels: usize,
+    pub out_channels: usize,
+    pub num_blocks: usize,
+    pub stride: usize,
+}
+
+impl RegNetStageConfig {
+    pub fn new(in_channels: usize, out_channels: usize, num_blocks: usize, stride: usize) -> Self {
+        Self {
+            in_channels,
+            out_channels,
+            num_blocks,
+            stride,
+        }
+    }
+}
+
+/// RegNet Stage
+#[derive(Debug)]
+pub struct RegNetStage {
+    config: RegNetStageConfig,
+    device: Device,
+}
+
+impl RegNetStage {
+    pub fn new(config: RegNetStageConfig) -> Self {
+        Self {
+            config,
+            device: Device::default(),
+        }
+    }
+
+    pub fn forward(&self, input: &Tensor) -> Result<Tensor> {
+        Ok(input.clone())
+    }
+}
+
+/// RegNet Stem
+#[derive(Debug)]
+pub struct RegNetStem {
+    out_channels: usize,
+    device: Device,
+}
+
+impl RegNetStem {
+    pub fn new(out_channels: usize) -> Self {
+        Self {
+            out_channels,
+            device: Device::default(),
+        }
+    }
+
+    pub fn forward(&self, input: &Tensor) -> Result<Tensor> {
+        Ok(input.clone())
+    }
+}
+
+/// RegNet Head
+#[derive(Debug)]
+pub struct RegNetHead {
+    in_features: usize,
+    num_classes: usize,
+    device: Device,
+}
+
+impl RegNetHead {
+    pub fn new(in_features: usize, num_classes: usize) -> Self {
+        Self {
+            in_features,
+            num_classes,
+            device: Device::default(),
+        }
+    }
+
+    pub fn forward(&self, input: &Tensor) -> Result<Tensor> {
+        Ok(input.clone())
+    }
+}
+
+/// SE Module configuration
+#[derive(Debug, Clone)]
+pub struct SEModuleConfig {
+    pub channels: usize,
+    pub reduction: usize,
+}
+
+impl SEModuleConfig {
+    pub fn new(channels: usize, reduction: usize) -> Self {
+        Self {
+            channels,
+            reduction,
+        }
+    }
+}
+
+/// Squeeze-and-Excitation Module
+#[derive(Debug)]
+pub struct SEModule {
+    config: SEModuleConfig,
+    device: Device,
+}
+
+impl SEModule {
+    pub fn new(config: SEModuleConfig) -> Self {
+        Self {
+            config,
+            device: Device::default(),
+        }
+    }
+
+    pub fn forward(&self, input: &Tensor) -> Result<Tensor> {
+        Ok(input.clone())
+    }
+}
+
+/// RegNet architecture
+pub struct RegNet {
+    config: RegNetConfig,
+    device: Device,
+}
+
+impl RegNet {
+    /// Create new RegNet model
+    pub fn new(config: RegNetConfig) -> Result<Self> {
+        Ok(RegNet {
+            config,
+            device: Device::default(),
+        })
+    }
+
+    /// Create new RegNet model with device
+    pub fn with_device(config: RegNetConfig, device: Device) -> Result<Self> {
+        Ok(RegNet { config, device })
+    }
+
+    /// Forward pass through the network
+    pub fn forward(&self, input: &Tensor) -> Result<Tensor> {
+        // Placeholder implementation
+        Ok(input.clone())
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    #[ignore = "RegNet requires CUDA device"]
+    fn test_regnet() -> Result<()> {
+        let device = Device::cuda(0)?;
+        let config = RegNetConfig::default();
+        let _model = RegNet::new(config)?;
+        Ok(())
+    }
+}