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/autodiff/multithread.rs

@@ -0,0 +1,88 @@
+use super::*;
+use burn_tensor::{TensorData, Tolerance};
+
+#[test]
+fn should_behave_the_same_with_multithread() {
+    let data_1 = TensorData::from([[1.0, 7.0], [13.0, -3.0]]);
+    let data_2 = TensorData::from([[4.0, 7.0], [2.0, 3.0]]);
+
+    let with_move = || {
+        let device = Default::default();
+        let tensor_1 = TestAutodiffTensor::<2>::from_data(data_1.clone(), &device).require_grad();
+        let tensor_2 = TestAutodiffTensor::from_data(data_2.clone(), &device).require_grad();
+
+        let tensor_3 = tensor_1.clone().matmul(tensor_2.clone());
+        let tensor_4 = tensor_3.clone().matmul(tensor_2.clone());
+        let tensor_5 = tensor_4.matmul(tensor_3);
+
+        // Task 1
+        let tensor_1_cloned = tensor_1.clone();
+        let tensor_2_cloned = tensor_2.clone();
+        let tensor_5_cloned = tensor_5.clone();
+
+        let first_call = move || {
+            let tensor_6_1 = tensor_5_cloned.matmul(tensor_2_cloned);
+            tensor_6_1.matmul(tensor_1_cloned)
+        };
+
+        // Task 2
+        let tensor_1_cloned = tensor_1.clone();
+        let tensor_2_cloned = tensor_2.clone();
+        let tensor_5_cloned = tensor_5;
+
+        let second_call = move || {
+            let tensor_6_2 = tensor_5_cloned.matmul(tensor_1_cloned);
+            tensor_6_2.matmul(tensor_2_cloned)
+        };
+
+        let tensor_7_1_handle = std::thread::spawn(first_call);
+        let tensor_7_2_handle = std::thread::spawn(second_call);
+
+        let tensor_7_1 = tensor_7_1_handle.join().unwrap();
+        let tensor_7_2 = tensor_7_2_handle.join().unwrap();
+        let tensor_8 = tensor_7_1.matmul(tensor_7_2);
+
+        let grads = tensor_8.backward();
+
+        let grad_1 = tensor_1.grad(&grads).unwrap();
+        let grad_2 = tensor_2.grad(&grads).unwrap();
+
+        (grad_1, grad_2)
+    };
+    let without_move = || {
+        let device = Default::default();
+        let tensor_1 = TestAutodiffTensor::<2>::from_data(data_1.clone(), &device).require_grad();
+        let tensor_2 = TestAutodiffTensor::from_data(data_2.clone(), &device).require_grad();
+
+        let tensor_3 = tensor_1.clone().matmul(tensor_2.clone());
+        let tensor_4 = tensor_3.clone().matmul(tensor_2.clone());
+        let tensor_5 = tensor_4.matmul(tensor_3);
+
+        // Task 1
+        let tensor_6_1 = tensor_5.clone().matmul(tensor_2.clone());
+        let tensor_7_1 = tensor_6_1.matmul(tensor_1.clone());
+
+        // Task 2
+        let tensor_6_2 = tensor_5.matmul(tensor_1.clone());
+        let tensor_7_2 = tensor_6_2.matmul(tensor_2.clone());
+
+        let tensor_8 = tensor_7_1.matmul(tensor_7_2);
+
+        let grads = tensor_8.backward();
+
+        let grad_1 = tensor_1.grad(&grads).unwrap();
+        let grad_2 = tensor_2.grad(&grads).unwrap();
+
+        (grad_1, grad_2)
+    };
+
+    let (grad_1, grad_2) = without_move();
+    let (grad_1_moved, grad_2_moved) = with_move();
+
+    grad_1
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&grad_1_moved.into_data(), Tolerance::default());
+    grad_2
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&grad_2_moved.into_data(), Tolerance::default());
+}