# minimum¶

`paddle.` `minimum` ( x, y, name=None ) [source]

Compare two tensors and returns a new tensor containing the element-wise minima. The equation is:

\[out = min(x, y)\]

Note: `paddle.minimum` supports broadcasting. If you want know more about broadcasting, please refer to Broadcasting .

Parameters
• x (Tensor) – the input tensor, it’s data type should be float32, float64, int32, int64.

• y (Tensor) – the input tensor, it’s data type should be float32, float64, int32, int64.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

N-D Tensor. A location into which the result is stored. If x, y have different shapes and are “broadcastable”, the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.

Examples

```import numpy as np

x = paddle.to_tensor([[1, 2], [7, 8]])
y = paddle.to_tensor([[3, 4], [5, 6]])
print(res)
#       [[1, 2],
#        [5, 6]]

x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]])
print(res)
#       [[[1, 0, 3],
#         [1, 0, 3]]]

x = paddle.to_tensor([2, 3, 5], dtype='float32')
y = paddle.to_tensor([1, np.nan, np.nan], dtype='float32')