min

paddle. min ( x, axis=None, keepdim=False, name=None ) [source]

Computes the minimum of tensor elements over the given axis

Parameters
  • x (Tensor) – A tensor, the data type is float32, float64, int32, int64.

  • axis (list|int, optional) – The axis along which the minimum is computed. If None, compute the minimum over all elements of x and return a Tensor with a single element, otherwise must be in the range \([-x.ndim, x.ndim)\). If \(axis[i] < 0\), the axis to reduce is \(x.ndim + axis[i]\).

  • keepdim (bool, optional) – Whether to reserve the reduced dimension in the output Tensor. The result tensor will have one fewer dimension than the x unless keepdim is true, default value is False.

  • name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name

Returns

Tensor, results of minimum on the specified axis of input tensor, it’s data type is the same as input’s Tensor.

Examples

import paddle

# x is a tensor with shape [2, 4]
# the axis is a int element
x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9],
                      [0.1, 0.2, 0.6, 0.7]])
result1 = paddle.min(x)
print(result1)
#[0.1]
result2 = paddle.min(x, axis=0)
print(result2)
#[0.1 0.2 0.5 0.7]
result3 = paddle.min(x, axis=-1)
print(result3)
#[0.2 0.1]
result4 = paddle.min(x, axis=1, keepdim=True)
print(result4)
#[[0.2]
# [0.1]]

# y is a Tensor with shape [2, 2, 2]
# the axis is list
y = paddle.to_tensor([[[1.0, 2.0], [3.0, 4.0]],
                      [[5.0, 6.0], [7.0, 8.0]]])
result5 = paddle.min(y, axis=[1, 2])
print(result5)
#[1. 5.]
result6 = paddle.min(y, axis=[0, 1])
print(result6)
#[1. 2.]