Add a couple functions required for yolo. (#527)

candle-nn/src/conv.rs

@@ -141,3 +141,19 @@ pub fn conv2d(
     let bs = vs.get_or_init(out_channels, "bias", init_bs)?;
     Ok(Conv2d::new(ws, Some(bs), cfg))
 }
+
+pub fn conv2d_no_bias(
+    in_channels: usize,
+    out_channels: usize,
+    kernel_size: usize,
+    cfg: Conv2dConfig,
+    vs: crate::VarBuilder,
+) -> Result<Conv2d> {
+    let init_ws = crate::init::DEFAULT_KAIMING_NORMAL;
+    let ws = vs.get_or_init(
+        (out_channels, in_channels, kernel_size, kernel_size),
+        "weight",
+        init_ws,
+    )?;
+    Ok(Conv2d::new(ws, None, cfg))
+}

candle-nn/src/func.rs

@@ -0,0 +1,27 @@
+//! Layers defined by closures.
+use candle::{Result, Tensor};
+
+/// A layer defined by a simple closure.
+pub struct Func<'a> {
+    #[allow(clippy::type_complexity)]
+    f: Box<dyn 'a + Fn(&Tensor) -> Result<Tensor> + Send>,
+}
+
+impl<'a> std::fmt::Debug for Func<'a> {
+    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
+        write!(f, "func")
+    }
+}
+
+pub fn func<'a, F>(f: F) -> Func<'a>
+where
+    F: 'a + Fn(&Tensor) -> Result<Tensor> + Send,
+{
+    Func { f: Box::new(f) }
+}
+
+impl<'a> super::Module for Func<'a> {
+    fn forward(&self, xs: &Tensor) -> Result<Tensor> {
+        (*self.f)(xs)
+    }
+}

candle-nn/src/lib.rs

@@ -4,6 +4,7 @@ pub mod activation;
 pub mod batch_norm;
 pub mod conv;
 pub mod embedding;
+pub mod func;
 pub mod group_norm;
 pub mod init;
 pub mod layer_norm;
@@ -16,8 +17,9 @@ pub mod var_map;
 
 pub use activation::Activation;
 pub use batch_norm::{batch_norm, BatchNorm, BatchNormConfig};
-pub use conv::{conv1d, conv2d, Conv1d, Conv1dConfig, Conv2d, Conv2dConfig};
+pub use conv::{conv1d, conv2d, conv2d_no_bias, Conv1d, Conv1dConfig, Conv2d, Conv2dConfig};
 pub use embedding::{embedding, Embedding};
+pub use func::{func, Func};
 pub use group_norm::{group_norm, GroupNorm};
 pub use init::Init;
 pub use layer_norm::{layer_norm, rms_norm, LayerNorm, LayerNormConfig, RmsNorm};