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/select.rs

@@ -0,0 +1,89 @@
+use super::*;
+use burn_tensor::{IndexingUpdateOp, Int, Tensor, TensorData};
+
+#[test]
+fn test_select_grad() {
+    let device = Default::default();
+    let tensor_1 = TestAutodiffTensor::<2>::from_data(
+        TensorData::from([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]),
+        &device,
+    )
+    .require_grad();
+    let indices =
+        Tensor::<TestAutodiffBackend, 1, Int>::from_data(TensorData::from([1, 0]), &device);
+
+    let tensor_2 = tensor_1.clone().matmul(tensor_1.clone().transpose());
+    let tensor_3 = tensor_1.clone().select(0, indices);
+    let tensor_4 = tensor_2.matmul(tensor_3);
+
+    let grads = tensor_4.backward();
+
+    let grad_1 = tensor_1.grad(&grads).unwrap();
+
+    grad_1.into_data().assert_eq(
+        &TensorData::from([[109., 148., 187.], [37., 58., 79.]]),
+        false,
+    );
+}
+
+#[test]
+fn test_select_add_grad() {
+    let device = Default::default();
+    let tensor_1 = TestAutodiffTensor::<2>::from_data(
+        TensorData::from([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]),
+        &device,
+    )
+    .require_grad();
+    let values = TestAutodiffTensor::from_data(
+        TensorData::from([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]),
+        &device,
+    )
+    .require_grad();
+    let indices =
+        Tensor::<TestAutodiffBackend, 1, Int>::from_data(TensorData::from([1, 0]), &device);
+
+    let tensor_2 = tensor_1.clone().matmul(tensor_1.clone().transpose());
+    let tensor_3 =
+        tensor_1
+            .clone()
+            .select_assign(0, indices, values.clone(), IndexingUpdateOp::Add);
+    let tensor_4 = tensor_2.matmul(tensor_3);
+
+    let grads = tensor_4.backward();
+
+    let grad_1 = tensor_1.grad(&grads).unwrap();
+    let grad_2 = values.grad(&grads).unwrap();
+
+    grad_1.into_data().assert_eq(
+        &TensorData::from([[127., 199., 271.], [172., 244., 316.]]),
+        false,
+    );
+    grad_2
+        .into_data()
+        .assert_eq(&TensorData::from([[64., 64., 64.], [19., 19., 19.]]), false);
+}
+
+#[test]
+fn test_select_add_grad_different_shapes() {
+    let device = Default::default();
+
+    let indices: Tensor<TestAutodiffBackend, 1, Int> = Tensor::from_ints([1], &device);
+    let x: Tensor<TestAutodiffBackend, 2> = Tensor::ones([1, 1], &device).require_grad();
+    let y = Tensor::ones([2, 1], &device).require_grad();
+
+    let w = y
+        .clone()
+        .select_assign(0, indices, x.clone(), IndexingUpdateOp::Add);
+    let w = w.matmul(y.clone().transpose());
+
+    let grads = w.backward();
+    let x_grad = x.grad(&grads).unwrap();
+    let y_grad = y.grad(&grads).unwrap();
+
+    x_grad
+        .into_data()
+        .assert_eq(&TensorData::from([[2.0]]), false);
+    y_grad
+        .into_data()
+        .assert_eq(&TensorData::from([[5.0], [5.0]]), false);
+}