fix: div return type for integer arguments

onnx2torch/node_converters/binary_math_operations.py

@@ -15,11 +15,19 @@
 from onnx2torch.utils.common import old_style_broadcast
 from onnx2torch.utils.common import onnx_mapping_from_node
 
+
+def _onnx_div(first: torch.Tensor, second: torch.Tensor) -> torch.Tensor:
+    if first.is_floating_point() or second.is_floating_point():  # float division
+        return torch.div(first, second)
+
+    return torch.div(first, second, rounding_mode='trunc')  # integer division
+
+
 _TORCH_FUNCTION_FROM_ONNX_TYPE = {
     'Add': torch.add,
     'Sub': torch.sub,
     'Mul': torch.mul,
-    'Div': torch.div,
+    'Div': _onnx_div,
 }
 
 

tests/node_converters/binary_operations_test.py

@@ -30,3 +30,31 @@ def test_math_binary_operation(op_type: str) -> None:  # pylint: disable=missing
 
         model = make_model_from_nodes(nodes=node, initializers=initializers, inputs_example=test_inputs)
         check_onnx_model(model, test_inputs)
+
+
+@pytest.mark.parametrize(
+    'x, y',
+    [
+        (1, 2),
+        (1, 5),
+        (5, 30),
+        (-1, 2),
+        (-1, 5),
+        (5, -30),
+        (5, 2),
+        (-5, 2),
+    ],
+)
+def test_div_operation(x: int, y: int) -> None:  # pylint: disable=missing-function-docstring
+    x_ = np.array(x, dtype=np.int64)  # pylint: disable=invalid-name
+    y_ = np.array(y, dtype=np.int64)  # pylint: disable=invalid-name
+    test_inputs = {'x': x_, 'y': y_}
+
+    node = onnx.helper.make_node(
+        op_type='Div',
+        inputs=['x', 'y'],
+        outputs=['z'],
+    )
+
+    model = make_model_from_nodes(nodes=node, initializers={}, inputs_example=test_inputs)
+    check_onnx_model(model, test_inputs)