6 files changed, 9 insertions, 9 deletions

diff --git a/candle-examples/examples/bert/main.rs b/candle-examples/examples/bert/main.rs
index d8f6921e..1c3c429b 100644
--- a/candle-examples/examples/bert/main.rs
+++ b/candle-examples/examples/bert/main.rs
@@ -196,7 +196,7 @@ impl BertEmbeddings {
         if let Some(position_embeddings) = &self.position_embeddings {
             // TODO: Proper absolute positions?
             let position_ids = (0..seq_len as u32).collect::<Vec<_>>();
-            let position_ids = Tensor::new(&position_ids[..], &input_ids.device())?;
+            let position_ids = Tensor::new(&position_ids[..], input_ids.device())?;
             embeddings = embeddings.broadcast_add(&position_embeddings.forward(&position_ids)?)?
         }
         let embeddings = self.layer_norm.forward(&embeddings)?;
diff --git a/candle-examples/examples/falcon/model.rs b/candle-examples/examples/falcon/model.rs
index 82c5d4b2..60821add 100644
--- a/candle-examples/examples/falcon/model.rs
+++ b/candle-examples/examples/falcon/model.rs
@@ -183,7 +183,7 @@ impl FalconRotaryEmbedding {
         past_kv_len: usize,
     ) -> Result<(Tensor, Tensor)> {
         let (_batch, seq_len, _head_dim) = query.shape().r3()?;
-        let (cos, sin) = self.cos_sin(MAX_SEQ_LEN, &query.device(), query.dtype())?;
+        let (cos, sin) = self.cos_sin(MAX_SEQ_LEN, query.device(), query.dtype())?;
         let cos = cos.narrow(0, past_kv_len, seq_len)?;
         let sin = sin.narrow(0, past_kv_len, seq_len)?;
         let qs = (query.broadcast_mul(&cos)? + &rotate_half(query)?.broadcast_mul(&sin)?)?;
@@ -194,7 +194,7 @@ impl FalconRotaryEmbedding {
 
 fn masked_fill(on_false: &Tensor, mask: &Tensor, on_true: f32) -> Result<Tensor> {
     let shape = mask.shape();
-    let on_true = Tensor::new(on_true, &on_false.device())?.broadcast_as(shape.dims())?;
+    let on_true = Tensor::new(on_true, on_false.device())?.broadcast_as(shape.dims())?;
     let m = mask.where_cond(&on_true, on_false)?;
     Ok(m)
 }
@@ -471,7 +471,7 @@ impl Falcon {
             Some((k, _)) => k.dim(1)?,
             None => 0,
         };
-        let causal_mask = prepare_attn_mask(b_sz, seq_len)?.to_device(&input_ids.device())?;
+        let causal_mask = prepare_attn_mask(b_sz, seq_len)?.to_device(input_ids.device())?;
         for block in self.blocks.iter_mut() {
             hidden_state = block.forward(&hidden_state, &causal_mask, past_kv_len)?;
         }
diff --git a/candle-examples/examples/llama/model.rs b/candle-examples/examples/llama/model.rs
index daab199d..04397d1e 100644
--- a/candle-examples/examples/llama/model.rs
+++ b/candle-examples/examples/llama/model.rs
@@ -227,7 +227,7 @@ impl CausalSelfAttention {
 
 fn masked_fill(on_false: &Tensor, mask: &Tensor, on_true: f32) -> Result<Tensor> {
     let shape = mask.shape();
-    let on_true = Tensor::new(on_true, &on_false.device())?.broadcast_as(shape.dims())?;
+    let on_true = Tensor::new(on_true, on_false.device())?.broadcast_as(shape.dims())?;
     let m = mask.where_cond(&on_true, on_false)?;
     Ok(m)
 }
diff --git a/candle-examples/examples/musicgen/encodec_model.rs b/candle-examples/examples/musicgen/encodec_model.rs
index f9b883fe..2ef6f20f 100644
--- a/candle-examples/examples/musicgen/encodec_model.rs
+++ b/candle-examples/examples/musicgen/encodec_model.rs
@@ -180,7 +180,7 @@ impl EncodecResidualVectorQuantizer {
     }
 
     fn decode(&self, codes: &Tensor) -> Result<Tensor> {
-        let mut quantized_out = Tensor::zeros((), DType::F32, &codes.device())?;
+        let mut quantized_out = Tensor::zeros((), DType::F32, codes.device())?;
         if codes.dim(0)? != self.layers.len() {
             anyhow::bail!(
                 "codes shape {:?} does not match the number of quantization layers {}",
diff --git a/candle-examples/examples/musicgen/musicgen_model.rs b/candle-examples/examples/musicgen/musicgen_model.rs
index 512e35e8..3c5e66f8 100644
--- a/candle-examples/examples/musicgen/musicgen_model.rs
+++ b/candle-examples/examples/musicgen/musicgen_model.rs
@@ -311,13 +311,13 @@ impl MusicgenDecoder {
         let (b_sz_times_codebooks, seq_len) = input_ids.shape().r2()?;
         let b_sz = b_sz_times_codebooks / self.num_codebooks;
         let input = input_ids.reshape((b_sz, self.num_codebooks, seq_len))?;
-        let mut inputs_embeds = Tensor::zeros((b_sz, seq_len, self.d_model), DType::F32, &dev)?;
+        let mut inputs_embeds = Tensor::zeros((b_sz, seq_len, self.d_model), DType::F32, dev)?;
         for (idx, codebook) in self.embed_tokens.iter().enumerate() {
             let inp = input.narrow(1, idx, 1)?.squeeze(1)?;
             inputs_embeds = (inputs_embeds + codebook.forward(&inp)?)?
         }
         let inputs_embeds = inputs_embeds;
-        let positions = self.embed_positions.forward(&input)?.to_device(&dev)?;
+        let positions = self.embed_positions.forward(&input)?.to_device(dev)?;
         let mut xs = inputs_embeds.broadcast_add(&positions)?;
         let attention_mask = self.prepare_decoder_attention_mask(b_sz, seq_len)?;
         for (_layer_idx, decoder_layer) in self.layers.iter_mut().enumerate() {
diff --git a/candle-examples/examples/whisper/main.rs b/candle-examples/examples/whisper/main.rs
index 9403b8b1..d0329f4d 100644
--- a/candle-examples/examples/whisper/main.rs
+++ b/candle-examples/examples/whisper/main.rs
@@ -109,7 +109,7 @@ impl Decoder {
         let mut no_speech_prob = f64::NAN;
         let mut tokens = vec![SOT_TOKEN];
         for i in 0..sample_len {
-            let tokens_t = Tensor::new(tokens.as_slice(), &mel.device())?;
+            let tokens_t = Tensor::new(tokens.as_slice(), mel.device())?;
 
             // The model expects a batch dim but this inference loop does not handle
             // it so we add it at this point.