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mindspore.ops.mvlgamma

mindspore.ops.mvlgamma(input, p)

Returns the results of the multivariate log-gamma function with dimension p element-wise.

The mathematical calculation process of Mvlgamma is shown as follows:

$$\log ({\mathrm{\Gamma }}_p(input))=C+\sum _{i=1}^p\log (\mathrm{\Gamma }(input-\frac{i-1}{2}))$$

where $C=\log (\pi )\times \frac{p(p-1)}{4}$ and $\mathrm{\Gamma }(\cdot )$ is the Gamma function.

Parameters

• input (Tensor) – The input tensor of the multivariate log-gamma function, which must be one of the following types: float32, float64. The shape is $(N,\ast )$, where $\ast$ means any number of additional dimensions. And the value of any element in input must be greater than $(p-1)/2$.

• p (int) – The number of dimensions. And the value of p must be greater than or equal to 1.

Returns

Tensor, has the same shape and type as input.

Raises

• TypeError – If dtype of input is neither float32 nor float64.

• TypeError – If p is not an int.

• ValueError – If p is less than 1.

• ValueError – If not all elements of input are greater than $(p-1)/2$.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([[3, 4, 5], [4, 2, 6]]), mindspore.float32)
>>> y = ops.mvlgamma(x, p=3)
>>> print(y)
[[2.694925 5.402975 9.140645]
 [5.402975 1.596312 13.64045]]