Depth Anything v2 (#2279)

* define structs

* construct ResidualConvUnit

* forward() for ResidualConvUnit

* implement FeatureFusionBlock

* implement Scratch

* implement DPTHead

* add identity module

* implement forward for DTPHead

* add get_intermediate_layers to DinoVisionTransformer

* implement DepthAnythingV2

* some minor tweaks

* fix compile errors

* fix var builder prefixes

* setup initial example

* use fixed patch size of 37 (518 / 14)

* debugged until output

* print min and max values

* add some dynamism to the output location

* scale input image

* extract prep function

* extract output path function

* normalize image with magic mean and std

* add spectral coloring

* squeeze in the right place

* make enterpolation optional

* use bail instead of panic

* omit unnecessary Shape call

* remove empty curly braces

* use bail instead of assert

* use vb and pp

* remove closures

* extract config object

* Apply rustfmt.

* Fix some clippy lints.

* More lints.

* Use the array methods.

---------

Co-authored-by: laurent <laurent.mazare@gmail.com>

candle-transformers/src/models/dinov2.rs

@@ -258,6 +258,84 @@ impl DinoVisionTransformer {
         let xs = Tensor::cat(&[&self.cls_token, &xs], 1)?;
         &xs + &self.interpolate_pos_encoding(&xs, w, h)?
     }
+
+    fn get_intermediate_layers_not_chunked(
+        &self,
+        xs: &Tensor,
+        blocks_to_take: &[usize],
+    ) -> Result<Vec<Tensor>> {
+        let mut xs = self.prepare_tokens_with_mask(xs)?;
+        let mut output = Vec::new();
+        for (i, blk) in self.blocks.iter().enumerate() {
+            xs = blk.forward(&xs)?;
+            if blocks_to_take.contains(&i) {
+                output.push(xs.clone());
+            }
+        }
+        if output.len() != blocks_to_take.len() {
+            candle::bail!(
+                "only {} / {} blocks found",
+                output.len(),
+                blocks_to_take.len()
+            );
+        }
+        Ok(output)
+    }
+
+    pub fn get_intermediate_layers(
+        &self,
+        xs: &Tensor,
+        blocks_to_take: &[usize],
+        reshape: bool,
+        return_class_token: bool,
+        norm: bool,
+    ) -> Result<Tensor> {
+        let outputs = self.get_intermediate_layers_not_chunked(xs, blocks_to_take)?;
+        let outputs = if norm {
+            outputs
+                .iter()
+                .map(|out| self.norm.forward(out))
+                .collect::<Result<Vec<_>>>()?
+        } else {
+            outputs
+        };
+        let class_tokens = outputs
+            .iter()
+            .map(|out| out.i((.., 0)))
+            .collect::<Result<Vec<_>>>()?;
+        let outputs = outputs
+            .iter()
+            .map(|out| out.i((.., 1..)))
+            .collect::<Result<Vec<_>>>()?;
+
+        let outputs = if reshape {
+            let (b, _c, w, h) = xs.dims4()?;
+            let patch_size = self.patch_embed.patch_size.0;
+            let num_channels = outputs[0].elem_count() / (b * (w / patch_size) * (h / patch_size));
+            outputs
+                .iter()
+                .map(|out| {
+                    out.reshape((b, w / patch_size, h / patch_size, num_channels))?
+                        .transpose(2, 3)?
+                        .transpose(1, 2)
+                })
+                .collect::<Result<Vec<_>>>()?
+        } else {
+            outputs
+        };
+
+        let outputs = if return_class_token {
+            outputs
+                .iter()
+                .zip(class_tokens.iter())
+                .map(|(out, class_token)| Tensor::cat(&[out, class_token], D::Minus1))
+                .collect::<Result<Vec<_>>>()?
+        } else {
+            outputs
+        };
+
+        Tensor::stack(&outputs[..], 0)
+    }
 }
 
 impl Module for DinoVisionTransformer {