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/mask.rs

@@ -0,0 +1,65 @@
+use super::*;
+use burn_tensor::Tolerance;
+use burn_tensor::{Bool, Tensor, TensorData};
+
+#[test]
+fn should_diff_mask_fill() {
+    let data_1 = TensorData::from([[1.0, 7.0], [2.0, 3.0]]);
+    let data_2 = TensorData::from([[4.0, 7.0], [2.0, 3.0]]);
+    let mask = TensorData::from([[true, false], [false, true]]);
+
+    let device = Default::default();
+    let tensor_1 = TestAutodiffTensor::from_data(data_1, &device).require_grad();
+    let tensor_2 = TestAutodiffTensor::from_data(data_2, &device).require_grad();
+    let mask = Tensor::<TestAutodiffBackend, 2, Bool>::from_bool(mask, &device);
+
+    let tensor_3 = tensor_1.clone().matmul(tensor_2.clone());
+    let tensor_4 = tensor_3.mask_fill(mask, 2.0);
+    let grads = tensor_4.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([[7.0, 3.0], [4.0, 2.0]]), false);
+    grad_2
+        .to_data()
+        .assert_eq(&TensorData::from([[2.0, 1.0], [3.0, 7.0]]), false);
+}
+
+#[test]
+fn should_diff_mask_where() {
+    let device = Default::default();
+    let tensor_1 = TestAutodiffTensor::from_data([[1.0, 7.0], [2.0, 3.0]], &device).require_grad();
+    let tensor_2 = TestAutodiffTensor::from_data([[4.0, 7.0], [2.0, 3.0]], &device).require_grad();
+    let tensor_3 =
+        TestAutodiffTensor::from_data([[8.8, 9.8], [10.8, 11.8]], &device).require_grad();
+    let mask =
+        Tensor::<TestAutodiffBackend, 2, Bool>::from_data([[true, false], [false, true]], &device);
+
+    let tensor_4 = tensor_1.clone().matmul(tensor_2.clone());
+    let tensor_5 = tensor_4.clone().matmul(tensor_3.clone());
+    let tensor_6 = tensor_5.mask_where(mask, tensor_3.clone());
+    let grads = tensor_6.backward();
+
+    let grad_1 = tensor_1.grad(&grads).unwrap();
+    let grad_2 = tensor_2.grad(&grads).unwrap();
+    let grad_3 = tensor_3.grad(&grads).unwrap();
+
+    let tolerance = Tolerance::default().set_half_precision_relative(1e-3);
+    let expected = TensorData::from([[121.8, 55.0], [110.8, 50.0]]);
+    grad_1
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&expected, tolerance);
+
+    let expected = TensorData::from([[27.4, 33.4], [95.0, 115.0]]);
+    grad_2
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&expected, tolerance);
+
+    let expected = TensorData::from([[15., 18.], [23., 29.]]);
+    grad_3
+        .into_data()
+        .assert_approx_eq::<FloatElem>(&expected, tolerance);
+}