Add some conv1d test + bugfix using padding. (#349)

1 files changed, 40 insertions, 0 deletions

diff --git a/candle-core/tests/conv_tests.rs b/candle-core/tests/conv_tests.rs
index 59240079..4ef47780 100644
--- a/candle-core/tests/conv_tests.rs
+++ b/candle-core/tests/conv_tests.rs
@@ -6,6 +6,46 @@ use candle_core::{Device, Tensor};
 import torch
 torch.manual_seed(4242)
 
+t = torch.randn((1, 4, 5))
+w = torch.randn((2, 4, 3))
+print(t.flatten())
+print(w.flatten())
+res = torch.nn.functional.conv1d(t, w)
+print(res.flatten())
+*/
+#[test]
+fn conv1d() -> Result<()> {
+    let dev = &Device::Cpu;
+    let t = Tensor::new(
+        &[
+            0.4056f32, -0.8689, -0.0773, -1.5630, 1.2279, -0.9287, -1.7030, 0.1370, 0.1866, 0.4145,
+            1.8025, -0.1536, 2.2013, -0.6836, 0.2477, 1.3127, -0.6957, 0.3278, -1.0124, 0.5599,
+        ],
+        dev,
+    )?
+    .reshape((1, 4, 5))?;
+    let w = Tensor::new(
+        &[
+            -0.8404f32, -0.3490, 0.0130, 1.3123, 0.1763, -1.9249, 1.4270, 0.9421, 0.8670, -0.7181,
+            -1.1111, 0.8869, -1.2429, 1.8357, 1.6052, -1.3844, 0.3951, -1.2036, 0.6686, 1.6261,
+            -0.6451, -0.0840, -1.4247, 0.5512,
+        ],
+        dev,
+    )?
+    .reshape((2, 4, 3))?;
+    let res = t.conv1d(&w, 0, 1)?;
+    assert_eq!(res.dims(), [1, 2, 3]);
+    assert_eq!(
+        test_utils::to_vec1_round(&res.flatten_all()?, 4)?,
+        [2.6357, -1.3336, 4.1393, -1.1784, 3.5675, 0.5069]
+    );
+    Ok(())
+}
+
+/* This test is based on the following script.
+import torch
+torch.manual_seed(4242)
+
 t = torch.randn((1, 4, 5, 5))
 w = torch.randn((2, 4, 3, 3))
 print(t.flatten())