Replication pad (#861)

* Add the embed mapper convolutions.

* Add the replication pad layer.

* Use the replication-pad op.

* Tweak a todo.

candle-nn/src/ops.rs

@@ -213,3 +213,18 @@ pub fn pixel_unshuffle(xs: &Tensor, downscale_factor: usize) -> Result<Tensor> {
     .permute((0, 1, 3, 5, 2, 4))?
     .reshape((b_size, out_c, h / downscale_factor, w / downscale_factor))
 }
+
+// https://pytorch.org/docs/stable/generated/torch.nn.ReplicationPad2d.html
+pub fn replication_pad2d(xs: &Tensor, pad: usize) -> Result<Tensor> {
+    match pad {
+        0 => Ok(xs.clone()),
+        1 => {
+            let (_b_size, _c, h, w) = xs.dims4()?;
+            let (first, last) = (xs.narrow(3, 0, 1)?, xs.narrow(3, w - 1, 1)?);
+            let xs = Tensor::cat(&[&first, xs, &last], 3)?;
+            let (first, last) = (xs.narrow(2, 0, 1)?, xs.narrow(2, h - 1, 1)?);
+            Tensor::cat(&[&first, &xs, &last], 2)
+        }
+        n => candle::bail!("replication-pad with a size of {n} is not supported"),
+    }
+}