Onnx Support for Sign operation #2641 (#2642)

* Support for Sign operation #2641

* Apply rustfmt.

---------

Co-authored-by: Laurent <laurent.mazare@gmail.com>

2 files changed, 47 insertions, 0 deletions

diff --git a/candle-onnx/src/eval.rs b/candle-onnx/src/eval.rs
index 358af7ac..2c60ed2f 100644
--- a/candle-onnx/src/eval.rs
+++ b/candle-onnx/src/eval.rs
@@ -1944,6 +1944,12 @@ fn simple_eval_(
 
                 values.insert(node.output[0].clone(), out);
             }
+            // https://onnx.ai/onnx/operators/onnx__Sign.html
+            "Sign" => {
+                let input = get(&node.input[0])?;
+                let output = input.sign()?;
+                values.insert(node.output[0].clone(), output);
+            }
             op_type => bail!("unsupported op_type {op_type} for op {node:?}"),
         }
     }
diff --git a/candle-onnx/tests/ops.rs b/candle-onnx/tests/ops.rs
index a84ba481..3586bfbd 100644
--- a/candle-onnx/tests/ops.rs
+++ b/candle-onnx/tests/ops.rs
@@ -5869,3 +5869,44 @@ fn test_xor() -> Result<()> {
     }
     Ok(())
 }
+
+#[test]
+fn test_sign_operation() -> Result<()> {
+    let manual_graph = create_model_proto_with_graph(Some(GraphProto {
+        node: vec![NodeProto {
+            op_type: "Sign".to_string(),
+            domain: "".to_string(),
+            attribute: vec![],
+            input: vec![INPUT_X.to_string()],
+            output: vec![OUTPUT_Z.to_string()],
+            name: "".to_string(),
+            doc_string: "".to_string(),
+        }],
+        name: "".to_string(),
+        initializer: vec![],
+        input: vec![],
+        output: vec![ValueInfoProto {
+            name: OUTPUT_Z.to_string(),
+            doc_string: "".to_string(),
+            r#type: None,
+        }],
+        value_info: vec![],
+        doc_string: "".to_string(),
+        sparse_initializer: vec![],
+        quantization_annotation: vec![],
+    }));
+
+    let mut inputs: HashMap<String, Tensor> = HashMap::new();
+    inputs.insert(
+        INPUT_X.to_string(),
+        Tensor::new(vec![-2f32, -1., 0., 1., 2.], &Device::Cpu)?,
+    );
+    let eval = candle_onnx::simple_eval(&manual_graph, inputs)?;
+
+    let z = eval.get(OUTPUT_Z).expect("Output 'z' not found");
+    assert_eq!(
+        z.to_dtype(candle::DType::I64)?.to_vec1::<i64>()?.to_vec(),
+        vec![-1, -1, 0, 1, 1]
+    );
+    Ok(())
+}