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mindspore.ops.logsumexp

View Source On Gitee
mindspore.ops.logsumexp(input, dim, keepdim=False)[source]

Calculate the log of summed exponentials of the tensor along a specified dimension.

logsumexp(input)=log((einputinputmax))+inputmax
Parameters
  • input (Tensor) – The input tensor.

  • dim (Union[int, tuple(int), list(int)]) – Specify the dimension for computation. If () , compute all elements in the input .

  • keepdim (bool, optional) – Whether the output tensor has dim retained. Default False .

Returns

Tensor

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> input = mindspore.tensor([[9., 3, 4, 5],
...                           [5, 2, 7, 4],
...                           [8, 1, 3, 6]])
>>> # case 1: By default, compute the log of summed exponential of all elements.
>>> output = mindspore.ops.logsumexp(input, ())
>>> print(output)
9.475807
>>>
>>> # case 2: Compute the log of summed exponential along dim 0.
>>> output = mindspore.ops.logsumexp(input, 0)
>>> print(output)
[9.326562  3.4076054 7.065884  6.4076056]
>>>
>>> # case 3: If keepdim=True, the output shape will be same of that of the input.
>>> output = mindspore.ops.logsumexp(input, 1, True)
>>> print(output)
[[9.02716 ]
 [7.175515]
 [8.133643]]