mindspore.ops.Add

class mindspore.ops.Add[source]

Adds two input tensors element-wise.

Refer to mindspore.ops.add() for more details.

Note

  • One of the two inputs must be a Tensor, when the two inputs have different shapes, they must be able to broadcast to a common shape.

  • The two inputs can not be bool type at the same time, [True, Tensor(True, bool_), Tensor(np.array([True]), bool_)] are all considered bool type.

  • The two inputs comply with the implicit type conversion rules to make the data types consistent.

Inputs:

  • x (Union[Tensor, number.Number, bool]) - The first input is a number.Number or a bool or a tensor whose data type is number or bool_.

  • y (Union[Tensor, number.Number, bool]) - The second input, when the first input is a Tensor, the second input should be a number.Number or bool value, or a Tensor whose data type is number or bool. When the first input is Scalar, the second input must be a Tensor whose data type is number or bool.

Outputs:

Tensor, the shape is the same as the one of the input x , y after broadcasting, and the data type is the one with higher precision or higher digits among the two inputs.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> # case 1: x and y are both Tensor.
>>> add = ops.Add()
>>> x = Tensor(np.array([1, 2, 3]).astype(np.float32))
>>> y = Tensor(np.array([4, 5, 6]).astype(np.float32))
>>> output = add(x, y)
>>> print(output)
[5. 7. 9.]
>>> # case 2: x is a scalar and y is a Tensor
>>> add = ops.Add()
>>> x = Tensor(1, mindspore.int32)
>>> y = Tensor(np.array([4, 5, 6]).astype(np.float32))
>>> output = add(x, y)
>>> print(output)
[5. 6. 7.]
>>> # the data type of x is int32, the data type of y is float32,
>>> # and the output is the data format of higher precision float32.
>>> print(output.dtype)
Float32
>>> # case 3: one of x and y is a bool scalar
>>> add = ops.Add()
>>> x = True
>>> y = Tensor(np.array([4, 5, 6]).astype(np.float32))
>>> output = add(x, y)
>>> print(output)
[5. 6. 7.]
>>> # case 4: one of x and y is a bool Tensor
>>> add = ops.Add()
>>> x = Tensor(np.array([True, False, True]), mindspore.bool_)
>>> y = Tensor(np.array([4, 5, 6]).astype(np.float32))
>>> output = add(x, y)
>>> print(output)
[5. 5. 7.]