More segment-anything again. (#764)

* More segment-anything again.

* Transformer block forward.

* Two-ways transformer.

* Position embeddings.

* Sketch the prompt encoder.

* More prompt-encoder.

* More prompt-encoder.

* Add the main sam module.

* Embed the transformer.

* And hook the transformer forward step.

* Build the model.

* Handle the global attn indexes.

* Get the model to load.

candle-examples/examples/segment-anything/model_mask_decoder.rs

@@ -1,6 +1,8 @@
 use candle::{DType, IndexOp, Result, Tensor, D};
 use candle_nn::{layer_norm, LayerNorm, Linear, Module, VarBuilder};
 
+use crate::model_transformer::TwoWayTransformer;
+
 #[derive(Debug)]
 struct MlpMaskDecoder {
     layers: Vec<Linear>,
@@ -53,7 +55,7 @@ impl Module for MlpMaskDecoder {
 }
 
 #[derive(Debug)]
-struct MaskDecoder {
+pub struct MaskDecoder {
     iou_token: candle_nn::Embedding,
     mask_tokens: candle_nn::Embedding,
     iou_prediction_head: MlpMaskDecoder,
@@ -62,17 +64,18 @@ struct MaskDecoder {
     output_upscaling_conv2: candle_nn::ConvTranspose2d,
     num_mask_tokens: usize,
     output_hypernetworks_mlps: Vec<MlpMaskDecoder>,
+    transformer: TwoWayTransformer,
 }
 
 impl MaskDecoder {
-    fn new(
+    pub fn new(
         transformer_dim: usize,
         num_multimask_outputs: usize,
         iou_head_depth: usize,
         iou_head_hidden_dim: usize,
         vb: VarBuilder,
     ) -> Result<Self> {
-        let num_mask_tokens = num_multimask_outputs - 1;
+        let num_mask_tokens = num_multimask_outputs + 1;
         let iou_prediction_head = MlpMaskDecoder::new(
             transformer_dim,
             iou_head_hidden_dim,
@@ -117,6 +120,13 @@ impl MaskDecoder {
             )?;
             output_hypernetworks_mlps.push(mlp)
         }
+        let transformer = TwoWayTransformer::new(
+            /* depth */ 2,
+            /* embedding_dim */ transformer_dim,
+            /* num_heads */ 8,
+            /* mlp_dim */ 2048,
+            vb.pp("transformer"),
+        )?;
         Ok(Self {
             iou_token,
             mask_tokens,
@@ -126,6 +136,7 @@ impl MaskDecoder {
             output_upscaling_conv2,
             num_mask_tokens,
             output_hypernetworks_mlps,
+            transformer,
         })
     }
 
@@ -182,7 +193,7 @@ impl MaskDecoder {
         let (b, c, h, w) = src.dims4()?;
 
         // Run the transformer
-        let (hs, src) = run_transformer(&src, &pos_src, &tokens)?;
+        let (hs, src) = self.transformer.forward(&src, &pos_src, &tokens)?;
         let iou_token_out = hs.i((.., 0))?;
         let mask_tokens_out = hs.i((.., 1, 1 + self.num_mask_tokens))?;
 
@@ -216,7 +227,3 @@ impl MaskDecoder {
 fn repeat_interleave(_img: &Tensor, _repeats: usize, _dim: usize) -> Result<Tensor> {
     todo!()
 }
-
-fn run_transformer(_src: &Tensor, _pos: &Tensor, _tokens: &Tensor) -> Result<(Tensor, Tensor)> {
-    todo!()
-}