[Python API] Add tuple support for opset.constant

Fixes #34210

Author: LuciferDono

src/bindings/python/src/openvino/opset1/ops.py

@@ -333,7 +333,7 @@ def concat(nodes: list[NodeInput], axis: int, name: Optional[str] = None) -> Nod
 
 @nameable_op
 def constant(
-    value: Union[NumericData, np.number, bool, np.bool_, list],
+    value: Union[NumericData, np.number, bool, np.bool_, list, tuple],
     dtype: Union[NumericType, Type] = None,
     name: Optional[str] = None,
 ) -> Constant:

src/bindings/python/src/openvino/opset13/ops.py

@@ -290,7 +290,7 @@ def scaled_dot_product_attention(
 )  # type: ignore
 @nameable_op
 def constant(
-    value: Union[NumericData, np.number, bool, np.bool_, list],
+    value: Union[NumericData, np.number, bool, np.bool_, list, tuple],
     dtype: Union[NumericType, Type] = None,
     name: Optional[str] = None,
     *,

src/bindings/python/src/openvino/utils/types.py

@@ -16,7 +16,7 @@
 log = logging.getLogger(__name__)
 
 TensorShape = list[int]
-NumericData = Union[int, float, np.ndarray]
+NumericData = Union[int, float, np.ndarray, tuple]
 NumericType = Union[type, np.dtype]
 ScalarData = Union[int, float]
 NodeInput = Union[Node, NumericData]
@@ -140,7 +140,7 @@ def get_shape(data: NumericData) -> TensorShape:
     """Return a shape of NumericData."""
     if isinstance(data, np.ndarray):
         return data.shape  # type: ignore
-    if isinstance(data, list):
+    if isinstance(data, (list, tuple)):
         return [len(data)]  # type: ignore
     return []
 

src/bindings/python/tests/test_graph/test_constant.py

@@ -796,3 +796,41 @@ def test_const_from_tensor_with_shared_memory_by_default():
     arr += 1
     assert np.array_equal(ov_const.data, arr)
     assert np.shares_memory(arr, ov_const.data)
+
+
+def test_constant_from_tuple():
+    value = (1, 2, 3)
+    ov_const = ops.constant(value, dtype=np.int32)
+
+    assert isinstance(ov_const, Constant)
+    assert list(ov_const.shape) == [3]
+    assert ov_const.get_element_type() == Type.i32
+    assert np.array_equal(ov_const.data, np.array(value, dtype=np.int32))
+
+
+def test_constant_from_tuple_float():
+    value = (1.0, 2.5, 3.5)
+    ov_const = ops.constant(value, dtype=np.float32)
+
+    assert isinstance(ov_const, Constant)
+    assert list(ov_const.shape) == [3]
+    assert ov_const.get_element_type() == Type.f32
+    assert np.allclose(ov_const.data, np.array(value, dtype=np.float32))
+
+
+def test_constant_from_nested_tuple():
+    value = ((1, 2), (3, 4))
+    ov_const = ops.constant(value, dtype=np.int32)
+
+    assert isinstance(ov_const, Constant)
+    assert list(ov_const.shape) == [2, 2]
+    assert np.array_equal(ov_const.data, np.array(value, dtype=np.int32))
+
+
+def test_constant_from_tuple_no_dtype():
+    value = (1, 2, 3)
+    ov_const = ops.constant(value)
+
+    assert isinstance(ov_const, Constant)
+    assert list(ov_const.shape) == [3]
+    assert np.array_equal(ov_const.data, np.array(value))