Add more to the forward pass and fix the cross-attention.

candle-examples/examples/whisper/main.rs

@@ -225,10 +225,10 @@ impl MultiHeadAttention {
         })
     }
 
-    fn forward(&self, x: &Tensor) -> Result<Tensor> {
+    fn forward(&self, x: &Tensor, xa: Option<&Tensor>) -> Result<Tensor> {
         let q = self.query.forward(x)?;
-        let k = self.key.forward(x)?;
-        let v = self.value.forward(x)?;
+        let k = self.key.forward(xa.unwrap_or(x))?;
+        let v = self.value.forward(xa.unwrap_or(x))?;
         let wv = self.qkv_attention(&q, &k, &v)?;
         let out = self.out.forward(&wv)?;
         Ok(out)
@@ -286,16 +286,16 @@ impl ResidualAttentionBlock {
         })
     }
 
-    fn forward(&self, x: &Tensor) -> Result<Tensor> {
-        let attn = self.attn.forward(&self.attn_ln.forward(x)?)?;
+    fn forward(&self, x: &Tensor, xa: Option<&Tensor>) -> Result<Tensor> {
+        let attn = self.attn.forward(&self.attn_ln.forward(x)?, None)?;
         let mut x = (x + attn)?;
         // Cross-Attn
-        if let Some(cross_attn) = &self.cross_attn {
-            x = cross_attn.forward(&x)?
-        }
         if let Some(cross_attn_ln) = &self.cross_attn_ln {
             x = cross_attn_ln.forward(&x)?
         }
+        if let Some(cross_attn) = &self.cross_attn {
+            x = cross_attn.forward(&x, xa)?
+        }
         // Mlp
         let mlp = self.mlp_linear2.forward(
             &self
@@ -358,7 +358,7 @@ impl AudioEncoder {
         let x = x.transpose(1, 2)?;
         let mut x = x.broadcast_add(&self.positional_embedding)?;
         for block in self.blocks.iter() {
-            x = block.forward(&x)?
+            x = block.forward(&x, None)?
         }
         let x = self.ln_post.forward(&x)?;
         Ok(x)
@@ -368,6 +368,7 @@ impl AudioEncoder {
 // https://github.com/openai/whisper/blob/f572f2161ba831bae131364c3bffdead7af6d210/whisper/model.py#L176
 struct TextDecoder {
     token_embedding: Embedding,
+    positional_embedding: Tensor,
     blocks: Vec<ResidualAttentionBlock>,
     ln: LayerNorm,
     mask: Tensor,
@@ -377,8 +378,11 @@ impl TextDecoder {
     fn load(p: &str, vb: &VarBuilder, cfg: &Config) -> Result<Self> {
         let n_state = cfg.n_text_state;
         let n_head = cfg.n_text_head;
+        let n_ctx = cfg.n_text_ctx;
         let token_embedding =
             Embedding::load(cfg.n_vocab, n_state, &format!("{p}.token_embedding"), vb)?;
+        let positional_embedding =
+            vb.get((n_ctx, n_state), &format!("{p}.positional_embedding"))?;
         let blocks = (0..cfg.n_text_layer)
             .map(|i| {
                 ResidualAttentionBlock::load(n_state, n_head, false, &format!("{p}.blocks.{i}"), vb)
@@ -388,13 +392,24 @@ impl TextDecoder {
         let mask = Tensor::new(&[0u32], &vb.device)?; // TODO
         Ok(Self {
             token_embedding,
+            positional_embedding,
             blocks,
             ln,
             mask,
         })
     }
-    fn forward(&self, _tokens: &Tensor, _enc: &Tensor) -> Result<Tensor> {
-        todo!()
+    fn forward(&self, x: &Tensor, xa: &Tensor) -> Result<Tensor> {
+        let x_dims = x.dims();
+        let last = x_dims[x_dims.len() - 1];
+        let token_embedding = self.token_embedding.forward(x)?;
+        let positional_embedding = self.positional_embedding.narrow(0, 0, last)?;
+        let mut x = (token_embedding + positional_embedding)?;
+        for block in self.blocks.iter() {
+            x = block.forward(&x, Some(xa))?
+        }
+        let x = self.ln.forward(&x)?;
+        let logits = x.matmul(&self.token_embedding.embeddings.t()?)?;
+        Ok(logits)
     }
 }