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/add.rs

@@ -0,0 +1,74 @@
+use super::*;
+use burn_tensor::TensorData;
+
+#[test]
+fn should_diff_add() {
+    let device = Default::default();
+    let tensor_1 = TestAutodiffTensor::<1>::from_floats([2.0, 5.0], &device).require_grad();
+    let tensor_2 = TestAutodiffTensor::from_floats([4.0, 1.0], &device).require_grad();
+
+    let tensor_3 = tensor_1.clone() + tensor_2.clone();
+    let grads = tensor_3.backward();
+
+    let grad_1 = tensor_1.grad(&grads).unwrap();
+    let grad_2 = tensor_2.grad(&grads).unwrap();
+
+    grad_1
+        .to_data()
+        .assert_eq(&TensorData::from([1.0, 1.0]), false);
+    grad_2
+        .to_data()
+        .assert_eq(&TensorData::from([1.0, 1.0]), false);
+    tensor_3
+        .to_data()
+        .assert_eq(&TensorData::from([6.0, 6.0]), false);
+}
+
+#[test]
+fn should_diff_add_scalar() {
+    let data = TensorData::from([2.0, 10.0]);
+
+    let tensor = TestAutodiffTensor::<1>::from_data(data, &Default::default()).require_grad();
+    let tensor_out = tensor.clone().add_scalar(5.0);
+    let grads = tensor_out.backward();
+
+    let grad = tensor.grad(&grads).unwrap();
+
+    grad.to_data()
+        .assert_eq(&TensorData::from([1.0, 1.0]), false);
+    tensor_out
+        .into_data()
+        .assert_eq(&TensorData::from([7.0, 15.0]), false);
+}
+
+#[test]
+fn test_add_complex_1() {
+    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 data_3 = TensorData::from([[2.0, 2.0], [2.0, 2.0]]);
+
+    let device = Default::default();
+    let tensor_1 = TestAutodiffTensor::<2>::from_data(data_1, &device).require_grad();
+    let tensor_2 = TestAutodiffTensor::from_data(data_2, &device).require_grad();
+    let tensor_3 = TestAutodiffTensor::from_data(data_3, &device).require_grad();
+
+    let tensor_4 = tensor_1.clone().add(tensor_2.clone());
+    let tensor_5 = tensor_4
+        .add(tensor_3)
+        .add_scalar(5.0)
+        .add(tensor_1.clone())
+        .add(tensor_2.clone());
+    let tensor_6 = tensor_1.clone().add(tensor_5);
+
+    let grads = tensor_6.backward();
+
+    let grad_1 = tensor_1.grad(&grads).unwrap();
+    let grad_2 = tensor_2.grad(&grads).unwrap();
+
+    grad_1
+        .to_data()
+        .assert_eq(&TensorData::from([[3.0, 3.0], [3.0, 3.0]]), false);
+    grad_2
+        .to_data()
+        .assert_eq(&TensorData::from([[2.0, 2.0], [2.0, 2.0]]), false);
+}