2 files changed, 5 insertions, 5 deletions
diff --git a/candle-examples/examples/whisper/main.rs b/candle-examples/examples/whisper/main.rs
index d7b303cf..079424e3 100644
--- a/candle-examples/examples/whisper/main.rs
+++ b/candle-examples/examples/whisper/main.rs
@@ -127,7 +127,7 @@ impl Decoder {
                     .to_scalar::<f32>()? as f64;
             }
 
-            let (seq_len, _) = logits.shape().r2()?;
+            let (seq_len, _) = logits.dims2()?;
             let logits = logits
                 .get(seq_len - 1)?
                 .broadcast_add(&self.suppress_tokens)?;
@@ -195,7 +195,7 @@ impl Decoder {
     }
 
     fn run(&mut self, mel: &Tensor) -> Result<Vec<Segment>> {
-        let (_, _, content_frames) = mel.shape().r3()?;
+        let (_, _, content_frames) = mel.dims3()?;
         let mut seek = 0;
         let mut segments = vec![];
         while seek < content_frames {
diff --git a/candle-examples/examples/whisper/model.rs b/candle-examples/examples/whisper/model.rs
index d4553e79..330b2a00 100644
--- a/candle-examples/examples/whisper/model.rs
+++ b/candle-examples/examples/whisper/model.rs
@@ -132,7 +132,7 @@ impl MultiHeadAttention {
     }
 
     fn reshape_head(&self, x: &Tensor) -> Result<Tensor> {
-        let (n_batch, n_ctx, n_state) = x.shape().r3()?;
+        let (n_batch, n_ctx, n_state) = x.dims3()?;
         let target_dims = &[n_batch, n_ctx, self.n_head, n_state / self.n_head];
         Ok(x.reshape(target_dims)?.transpose(1, 2)?)
     }
@@ -144,7 +144,7 @@ impl MultiHeadAttention {
         v: &Tensor,
         mask: Option<&Tensor>,
     ) -> Result<Tensor> {
-        let (_, n_ctx, n_state) = q.shape().r3()?;
+        let (_, n_ctx, n_state) = q.dims3()?;
         let scale = ((n_state / self.n_head) as f64).powf(-0.25);
         let q = (self.reshape_head(q)? * scale)?;
         let k = (self.reshape_head(k)?.transpose(2, 3)? * scale)?;
@@ -270,7 +270,7 @@ impl AudioEncoder {
         let x = self.conv1.forward(x)?.gelu()?;
         let x = self.conv2.forward(&x)?.gelu()?;
         let x = x.transpose(1, 2)?;
-        let (_bsize, seq_len, _hidden) = x.shape().r3()?;
+        let (_bsize, seq_len, _hidden) = x.dims3()?;
         let positional_embedding = self.positional_embedding.narrow(0, 0, seq_len)?;
         let mut x = x.broadcast_add(&positional_embedding)?;
         for block in self.blocks.iter() {