From 6a60fe01c481c34d9257c08720ab84799f25480a Mon Sep 17 00:00:00 2001
From: laurent <laurent.mazare@gmail.com>
Date: Sat, 26 Oct 2024 21:51:17 +0200
Subject: [PATCH] Remove some unnecessary clones.

---
 .../examples/stable-diffusion-3/main.rs       | 21 +++++--------------
 .../examples/stable-diffusion-3/sampling.rs   |  2 +-
 2 files changed, 6 insertions(+), 17 deletions(-)

diff --git a/candle-examples/examples/stable-diffusion-3/main.rs b/candle-examples/examples/stable-diffusion-3/main.rs
index 58e811c38a..19361e4325 100644
--- a/candle-examples/examples/stable-diffusion-3/main.rs
+++ b/candle-examples/examples/stable-diffusion-3/main.rs
@@ -203,7 +203,7 @@ fn main() -> Result<()> {
 
             // Apply TAESD3 scale factor. Seems to be significantly improving the quality of the image.
             // https://github.com/comfyanonymous/ComfyUI/blob/3c60ecd7a83da43d694e26a77ca6b93106891251/nodes.py#L721-L723
-            autoencoder.decode(&((x.clone() / 1.5305)? + 0.0609)?)?
+            autoencoder.decode(&((x / 1.5305)? + 0.0609)?)?
         }
     } else {
         let sai_repo = {
@@ -212,20 +212,12 @@ fn main() -> Result<()> {
         };
         let model_file = sai_repo.get("sd3_medium_incl_clips_t5xxlfp16.safetensors")?;
         let vb_fp16 = unsafe {
-            candle_nn::VarBuilder::from_mmaped_safetensors(
-                &[model_file.clone()],
-                DType::F16,
-                &device,
-            )?
+            candle_nn::VarBuilder::from_mmaped_safetensors(&[&model_file], DType::F16, &device)?
         };
 
         let (context, y) = {
             let vb_fp32 = unsafe {
-                candle_nn::VarBuilder::from_mmaped_safetensors(
-                    &[model_file.clone()],
-                    DType::F32,
-                    &device,
-                )?
+                candle_nn::VarBuilder::from_mmaped_safetensors(&[model_file], DType::F32, &device)?
             };
             let mut triple = StableDiffusion3TripleClipWithTokenizer::new(
                 vb_fp16.pp("text_encoders"),
@@ -271,15 +263,12 @@ fn main() -> Result<()> {
         };
 
         {
-            let vb_vae = vb_fp16
-                .clone()
-                .rename_f(sd3_vae_vb_rename)
-                .pp("first_stage_model");
+            let vb_vae = vb_fp16.rename_f(sd3_vae_vb_rename).pp("first_stage_model");
             let autoencoder = build_sd3_vae_autoencoder(vb_vae)?;
 
             // Apply TAESD3 scale factor. Seems to be significantly improving the quality of the image.
             // https://github.com/comfyanonymous/ComfyUI/blob/3c60ecd7a83da43d694e26a77ca6b93106891251/nodes.py#L721-L723
-            autoencoder.decode(&((x.clone() / 1.5305)? + 0.0609)?)?
+            autoencoder.decode(&((x / 1.5305)? + 0.0609)?)?
         }
     };
     let img = ((img.clamp(-1f32, 1f32)? + 1.0)? * 127.5)?.to_dtype(candle::DType::U8)?;
diff --git a/candle-examples/examples/stable-diffusion-3/sampling.rs b/candle-examples/examples/stable-diffusion-3/sampling.rs
index 0efd160eba..cd881b6a2f 100644
--- a/candle-examples/examples/stable-diffusion-3/sampling.rs
+++ b/candle-examples/examples/stable-diffusion-3/sampling.rs
@@ -30,7 +30,7 @@ pub fn euler_sample(
 
         let timestep = (*s_curr) * 1000.0;
         let noise_pred = mmdit.forward(
-            &Tensor::cat(&[x.clone(), x.clone()], 0)?,
+            &Tensor::cat(&[&x, &x], 0)?,
             &Tensor::full(timestep as f32, (2,), x.device())?.contiguous()?,
             y,
             context,