def custom_converter(node: NodeContext):
nonlocal invoked
invoked = True
a = node.get_input(0)
b = node.get_input(1)
add = ops.add(a, b)
return [add.output(0)]
def custom_converter(node: NodeContext):
nonlocal invoked
invoked = True
def check_attribute(context, name, expected_value, dtype):
attribute = context.get_attribute(name, dtype=dtype)
if isinstance(attribute, list):
assert type(attribute[0]) == dtype
else:
assert type(attribute) == dtype
assert attribute == expected_value
check_attribute(node, "attribute_i32", 10, float)
check_attribute(node, "attribute_i64", 10, float)
check_attribute(node, "attribute_str", "string", np.str)
check_attribute(node, "attribute_f32", 10, int)
check_attribute(node, "attribute_f64", 10, int)
check_attribute(node, "attribute_bool", True, bool)
check_attribute(node, "attribute_type", Type.i32, Type)
check_attribute(node, "attribute_list_i32", [1., 2., 3.], float)
check_attribute(node, "attribute_list_i64", [1., 2., 3.], float)
check_attribute(node, "attribute_list_str", ["a", "b", "c"], np.str)
check_attribute(node, "attribute_list_f32", [1, 2, 3], int)
check_attribute(node, "attribute_list_f64", [1, 2, 3], int)
check_attribute(node, "attribute_list_bool", [True, False, True], bool)
check_attribute(node, "attribute_list_type", [Type.i32, Type.f32],
Type)
a = node.get_input(0)
b = node.get_input(1)
add = ops.add(a, b)
return [add.output(0)]
def custom_converter(node: NodeContext):
nonlocal invoked
invoked = True
def check_attribute(context, name, default_value):
assert not context.has_attribute(name)
attribute = context.get_attribute(name, default_value)
assert type(attribute) == type(default_value)
if isinstance(attribute, np.ndarray):
assert np.all(attribute == default_value)
else:
assert attribute == default_value
check_attribute(node, "attribute_i32", np.int32(5))
check_attribute(node, "attribute_i64", np.int64(5))
check_attribute(node, "attribute_str", "abc")
check_attribute(node, "attribute_f32", np.float32(5))
check_attribute(node, "attribute_f64", np.float64(5))
check_attribute(node, "attribute_bool", np.bool(False))
check_attribute(node, "attribute_type", onnx.TensorProto.FLOAT)
check_attribute(node, "attribute_list_i32", np.array([4, 5, 6], dtype=np.int32))
check_attribute(node, "attribute_list_i64", np.array([4, 5, 6], dtype=np.int64))
check_attribute(node, "attribute_list_str", np.array(["d", "e", "f"], dtype=np.str))
check_attribute(node, "attribute_list_f32", np.array([4, 5, 6], dtype=np.float))
check_attribute(node, "attribute_list_f64", np.array([4, 5, 6], dtype=np.float64))
check_attribute(node, "attribute_list_bool", np.array([True, False, True], dtype=np.bool))
check_attribute(node, "attribute_list_type", np.array([onnx.TensorProto.INT32,
onnx.TensorProto.FLOAT]))
a = node.get_input(0)
b = node.get_input(1)
add = ops.add(a, b)
return [add.output(0)]
def custom_converter(node: NodeContext):
nonlocal invoked
invoked = True
def check_attribute(context, name, expected_type, expected_value):
assert context.has_attribute(name)
attribute = context.get_attribute(name)
assert type(attribute) == expected_type
assert attribute == expected_value
check_attribute(node, "attribute_i32", int, 10)
check_attribute(node, "attribute_i64", int, 10)
check_attribute(node, "attribute_str", str, "string")
check_attribute(node, "attribute_f32", float, 10.)
check_attribute(node, "attribute_f64", float, 10.)
check_attribute(node, "attribute_bool", int, 1)
check_attribute(node, "attribute_type", int, 6)
check_attribute(node, "attribute_list_i32", list, [1, 2, 3])
check_attribute(node, "attribute_list_i64", list, [1, 2, 3])
check_attribute(node, "attribute_list_str", list, ["a", "b", "c"])
check_attribute(node, "attribute_list_f32", list, [1., 2., 3.])
check_attribute(node, "attribute_list_f64", list, [1., 2., 3.])
check_attribute(node, "attribute_list_bool", list, [1, 0, 1])
check_attribute(node, "attribute_list_type", list, [6, 1])
a = node.get_input(0)
b = node.get_input(1)
add = ops.add(a, b)
return [add.output(0)]
def custom_converter(node: NodeContext):
node.get_input(0)
node.get_attribute("alpha")