candle-onnx: Implement Hard Swish operator (huggingface#2980)

* feat: added Elu operator

* feat: added hard swish

* added more tests for hard swish

* clened up

---------

authored-by: misadowsk <michalsad.protondynamic@gmail.com>

Author: Michall00

candle-onnx/src/eval.rs

@@ -2097,6 +2097,11 @@ fn simple_eval_(
                 let output = input.sign()?;
                 values.insert(node.output[0].clone(), output);
             }
+            "HardSwish" => {
+                let input = get(&node.input[0])?;
+                let hard_sigmoid = candle_nn::ops::hard_sigmoid(&input)?;
+                let output = input * hard_sigmoid;
+                values.insert(node.output[0].clone(), output?);
             "Resize" => {
                 let input = get(&node.input[0])?;
 
@@ -2365,6 +2370,7 @@ fn simple_eval_(
                 values.insert(node.output[0].clone(), output);
             }
             op_type => bail!("unsupported op_type {op_type} for op {node:?}"),
+            
         }
     }
     graph

candle-onnx/tests/ops.rs

@@ -6247,6 +6247,92 @@ fn test_sign_operation() -> Result<()> {
     Ok(())
 }
 
+#[test]
+fn test_hard_swish() -> candle::Result<()> {
+    {
+    let manual_graph = create_model_proto_with_graph(Some(GraphProto {
+        node: vec![NodeProto {
+            op_type: "HardSwish".to_string(),
+            input: vec![INPUT_X.to_string()],
+            output: vec![OUTPUT_Z.to_string()],
+            ..Default::default()
+        }],
+        input: vec![ValueInfoProto {
+            name: INPUT_X.to_string(),
+            ..Default::default()
+        }],
+        output: vec![ValueInfoProto {
+            name: OUTPUT_Z.to_string(),
+            ..Default::default()
+        }],
+        ..Default::default()
+    }));
+    let input_data = vec![-4.0f32, -3.0, 0.0, 2.0, 3.0, 5.0];
+    let input_tensor = Tensor::from_vec(input_data.clone(), (input_data.len(),), &Device::Cpu)?;
+    let mut inputs = HashMap::new();
+    inputs.insert(INPUT_X.to_string(), input_tensor);
+
+    let outputs = simple_eval(&manual_graph, inputs)?;
+    let output = outputs.get(OUTPUT_Z).expect("missing output Z");
+    let output_vec = output.to_vec1::<f32>()?;
+
+    let expected = vec![
+        0.0,
+        0.0,
+        0.0,
+        1.6666666,
+        3.0,
+        5.0,
+    ];
+
+    for (i, (got, exp)) in output_vec.iter().zip(expected.iter()).enumerate() {
+        let diff = (got - exp).abs();
+        assert!(
+            diff < 1e-4,
+            "Mismatch at index {i}: got {got}, expected {exp}, diff={diff}"
+        );
+    }
+    }
+    {
+    let manual_graph = create_model_proto_with_graph(Some(GraphProto {
+        node: vec![NodeProto {
+            op_type: "HardSwish".to_string(),
+            input: vec![INPUT_X.to_string()],
+            output: vec![OUTPUT_Z.to_string()],
+            ..Default::default()
+        }],
+        input: vec![ValueInfoProto {
+            name: INPUT_X.to_string(),
+            ..Default::default()
+        }],
+        output: vec![ValueInfoProto {
+            name: OUTPUT_Z.to_string(),
+            ..Default::default()
+        }],
+        ..Default::default()
+    }));
+    let input_data = vec![-4.0f32, -2.0, 0.0, 2.0, 4.0];
+    let input_tensor = Tensor::from_vec(input_data.clone(), (input_data.len(),), &Device::Cpu)?;
+    let mut inputs = HashMap::new();
+    inputs.insert(INPUT_X.to_string(), input_tensor);
+
+    let outputs = simple_eval(&manual_graph, inputs)?;
+    let output = outputs.get(OUTPUT_Z).expect("missing output Z");
+    let output_vec = output.to_vec1::<f32>()?;
+
+    let expected = vec![0.0, -0.33333334, 0.0, 1.6666667, 4.0 ];
+
+    for (i, (got, exp)) in output_vec.iter().zip(expected.iter()).enumerate() {
+        let diff = (got - exp).abs();
+        assert!(
+            diff < 1e-4,
+            "Mismatch at index {i}: got {got}, expected {exp}, diff={diff}"
+        );
+    }
+    }
+    Ok(())
+}
+
 #[test]
 fn test_scatternd_operation() -> Result<()> {
     // Example 1 based on ONNX documentation
@@ -6752,6 +6838,5 @@ fn test_trilu_operation() -> Result<()> {
             ]
         );
     }
-
     Ok(())
 }