Fixes

Cargo.toml

@@ -153,11 +153,11 @@ ahash = { version = "0.8.11", default-features = false }
 portable-atomic-util = { version = "0.2.4", features = ["alloc"] }
 
 ### For the main burn branch. ###
-#cubecl = { git = "https://github.com/tracel-ai/cubecl", default-features = false, rev = "4c42d0b54ac9069ff520c7719e7ef77833248e34" }
-#cubecl-common = { git = "https://github.com/tracel-ai/cubecl", default-features = false, rev = "4c42d0b54ac9069ff520c7719e7ef77833248e34" }
+cubecl = { git = "https://github.com/tracel-ai/cubecl", default-features = false, rev = "2cc42af02671d90255ab823e29a4a3ad2e564333" }
+cubecl-common = { git = "https://github.com/tracel-ai/cubecl", default-features = false, rev = "2cc42af02671d90255ab823e29a4a3ad2e564333" }
 ### For local development. ###
-cubecl = { path = "../cubecl/crates/cubecl", default-features = false }
-cubecl-common = { path = "../cubecl/crates/cubecl-common", default-features = false }
+# cubecl = { path = "../cubecl/crates/cubecl", default-features = false }
+# cubecl-common = { path = "../cubecl/crates/cubecl-common", default-features = false }
 ### For the release. ###
 # cubecl = { version = "0.4.0", default-features = false }
 # cubecl-common = { version = "0.4.0", default-features = false }

crates/burn-jit/src/kernel/conv/conv2d/tune/conv_transpose2d.rs

@@ -1,5 +1,5 @@
 use burn_tensor::{ops::ConvTransposeOptions, ElementConversion, Shape};
-use cubecl::tune::{local_tuner, tune_with, LocalTuner, TunableSet};
+use cubecl::tune::{local_tuner, LocalTuner, TunableSet};
 
 use crate::{
     kernel::{
@@ -64,7 +64,7 @@ pub fn create_transpose2d_input<R: JitRuntime, E: FloatElement>(
     let bias = key
         .has_bias
         .then(|| random_uniform(bias_shape, device, random_bounds.0, random_bounds.1));
-    tune_with!(input, weights, bias, options.clone())
+    (input, weights, bias, options.clone())
 }
 
 fn create_key<R: JitRuntime, E: FloatElement>(

crates/burn-jit/src/kernel/matmul/tune/base.rs

@@ -1,7 +1,7 @@
 use burn_tensor::{Element, ElementConversion};
 use cubecl::{
     linalg::matmul::{kernels::tiling2d::Tiling2dConfig, Strategy},
-    tune::{local_tuner, tune_with, LocalTuner, TunableSet},
+    tune::{local_tuner, LocalTuner, TunableSet},
 };
 
 use crate::{
@@ -27,7 +27,7 @@ fn matmul_input_gen<R: JitRuntime, E: FloatElement>(
 
     let out = empty_device::<R, E>(out.client.clone(), out.device.clone(), out.shape.clone());
 
-    tune_with!(lhs, rhs, out)
+    (lhs, rhs, out)
 }
 
 /// Executes autotune on matmul operations