feat: update workspace paths and enhance gitignore

- Updated stablediffusion crate path from "../stable-diffusion-burn" to "./crates/stable-diffusion-burn" for proper workspace resolution
- Enhanced .gitignore to include generated model files (.mpk, .pt, .bin, .safetensors, .ckpt) and user_data directory
- Added Cargo.lock to gitignore with appropriate comment
- Reorganized IDE files section in gitignore for better clarity
- Added newline at end of file for proper formatting

crates/stable-diffusion-burn/burn-crates/burn-backend-tests/tests/cubecl/conv2d.rs

@@ -0,0 +1,78 @@
+use super::*;
+use burn_tensor::Tolerance;
+use burn_tensor::{Distribution, Tensor, module};
+
+#[test]
+fn conv2d_should_match_reference_backend() {
+    let test_device = Default::default();
+    let input =
+        Tensor::<TestBackend, 4>::random([6, 16, 32, 32], Distribution::Default, &test_device);
+    let weight =
+        Tensor::<TestBackend, 4>::random([12, 8, 3, 3], Distribution::Default, &test_device);
+    let bias = Tensor::<TestBackend, 1>::random([12], Distribution::Default, &test_device);
+    let ref_device = Default::default();
+
+    let input_ref = Tensor::<ReferenceBackend, 4>::from_data(input.to_data(), &ref_device);
+    let weight_ref = Tensor::<ReferenceBackend, 4>::from_data(weight.to_data(), &ref_device);
+    let bias_ref = Tensor::<ReferenceBackend, 1>::from_data(bias.to_data(), &ref_device);
+
+    let options = burn_tensor::ops::ConvOptions::new([2, 3], [2, 3], [2, 3], 2);
+
+    let output = module::conv2d(input, weight, Some(bias), options.clone());
+    let output_ref = module::conv2d(input_ref, weight_ref, Some(bias_ref), options);
+
+    output
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&output_ref.into_data(), Tolerance::default());
+}
+
+#[test]
+fn conv2d_should_match_reference_backend_implicit() {
+    let test_device = Default::default();
+    let input =
+        Tensor::<TestBackend, 4>::random([4, 16, 6, 6], Distribution::Default, &test_device);
+    let weight =
+        Tensor::<TestBackend, 4>::random([16, 16, 3, 3], Distribution::Default, &test_device);
+    let bias = Tensor::<TestBackend, 1>::random([16], Distribution::Default, &test_device);
+    let ref_device = Default::default();
+
+    let input_ref = Tensor::<ReferenceBackend, 4>::from_data(input.to_data(), &ref_device);
+    let weight_ref = Tensor::<ReferenceBackend, 4>::from_data(weight.to_data(), &ref_device);
+    let bias_ref = Tensor::<ReferenceBackend, 1>::from_data(bias.to_data(), &ref_device);
+
+    let options = burn_tensor::ops::ConvOptions::new([1, 1], [2, 2], [1, 1], 1);
+
+    let output = module::conv2d(input, weight, Some(bias), options.clone());
+    let output_ref = module::conv2d(input_ref, weight_ref, Some(bias_ref), options);
+
+    let tolerance = Tolerance::default();
+    output
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&output_ref.into_data(), tolerance);
+}
+
+/// Regression test for bias loader in new implicit GEMM
+#[test]
+fn conv2d_should_match_reference_backend_bias_regression() {
+    let test_device = Default::default();
+    let input = Tensor::<TestBackend, 4>::random([1, 1, 1, 1], Distribution::Default, &test_device);
+    let weight =
+        Tensor::<TestBackend, 4>::random([32, 1, 3, 3], Distribution::Default, &test_device);
+    let bias = Tensor::<TestBackend, 1>::random([32], Distribution::Default, &test_device);
+    let ref_device = Default::default();
+
+    let input_ref = Tensor::<ReferenceBackend, 4>::from_data(input.to_data(), &ref_device);
+    let weight_ref = Tensor::<ReferenceBackend, 4>::from_data(weight.to_data(), &ref_device);
+    let bias_ref = Tensor::<ReferenceBackend, 1>::from_data(bias.to_data(), &ref_device);
+
+    let options = burn_tensor::ops::ConvOptions::new([1, 1], [1, 1], [1, 1], 1);
+
+    let output = module::conv2d(input, weight, Some(bias), options.clone()).permute([0, 2, 3, 1]);
+    let output_ref =
+        module::conv2d(input_ref, weight_ref, Some(bias_ref), options).permute([0, 2, 3, 1]);
+
+    let tolerance = Tolerance::default();
+    output
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&output_ref.into_data(), tolerance);
+}