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/avgpool1d.rs

@@ -0,0 +1,102 @@
+use super::*;
+use burn_tensor::module::avg_pool1d;
+use burn_tensor::{Shape, Tolerance};
+
+#[test]
+fn test_avg_pool1d_simple() {
+    let test = AvgPool1dTestCase {
+        batch_size: 1,
+        channels: 1,
+        kernel_size: 3,
+        padding: 0,
+        stride: 1,
+        length: 6,
+        count_include_pad: true,
+    };
+
+    test.assert_output(TestTensor::from_floats(
+        [[[0.33333, 0.66667, 1.0000, 1.0000, 0.66667, 0.33333]]],
+        &Default::default(),
+    ));
+}
+
+#[test]
+fn test_avg_pool1d_complex() {
+    let test = AvgPool1dTestCase {
+        batch_size: 1,
+        channels: 2,
+        kernel_size: 3,
+        padding: 1,
+        stride: 2,
+        length: 6,
+        count_include_pad: true,
+    };
+
+    test.assert_output(TestTensor::from_floats(
+        [[
+            [0.33333, 0.66667, 0.33333, 0.66667, 0.33333, 0.33333],
+            [0.33333, 0.66667, 0.33333, 0.66667, 0.33333, 0.33333],
+        ]],
+        &Default::default(),
+    ));
+}
+
+#[test]
+fn test_avg_pool1d_complex_dont_count_pad() {
+    let test = AvgPool1dTestCase {
+        batch_size: 1,
+        channels: 2,
+        kernel_size: 3,
+        padding: 1,
+        stride: 2,
+        length: 6,
+        count_include_pad: false,
+    };
+
+    test.assert_output(TestTensor::from_floats(
+        [[
+            [0.5000, 0.83333, 0.33333, 0.66667, 0.33333, 0.33333],
+            [0.5000, 0.83333, 0.33333, 0.66667, 0.33333, 0.33333],
+        ]],
+        &Default::default(),
+    ));
+}
+
+struct AvgPool1dTestCase {
+    batch_size: usize,
+    channels: usize,
+    kernel_size: usize,
+    padding: usize,
+    stride: usize,
+    length: usize,
+    count_include_pad: bool,
+}
+
+impl AvgPool1dTestCase {
+    fn assert_output(self, x_grad: TestTensor<3>) {
+        let shape_x = Shape::new([self.batch_size, self.channels, self.length]);
+        let device = Default::default();
+        let x = TestAutodiffTensor::from_data(
+            TestTensorInt::arange(0..shape_x.num_elements() as i64, &device)
+                .reshape::<3, _>(shape_x)
+                .into_data(),
+            &device,
+        )
+        .require_grad();
+        let output = avg_pool1d(
+            x.clone(),
+            self.kernel_size,
+            self.stride,
+            self.padding,
+            self.count_include_pad,
+            false,
+        );
+        let grads = output.backward();
+        let x_grad_actual = x.grad(&grads).unwrap();
+
+        let tolerance = Tolerance::default().set_half_precision_relative(1e-3);
+        x_grad
+            .to_data()
+            .assert_approx_eq::<FloatElem>(&x_grad_actual.into_data(), tolerance);
+    }
+}