mindspore.ops.Gamma
- class mindspore.ops.Gamma(seed=0, seed2=0)[source]
Produces random positive floating-point values x, distributed according to probability density function:
\[\text{P}(x|α,β) = \frac{\exp(-x/β)}{{β^α}\cdot{\Gamma(α)}}\cdot{x^{α-1}}\]- Parameters
- Inputs:
shape (tuple) - The shape of random tensor to be generated. Only constant value is allowed.
alpha (Tensor) - The α distribution parameter. It must be greater than 0. It is also known as the shape parameter with float32 data type.
beta (Tensor) - The β distribution parameter. It must be greater than 0. It is also known as the inverse scale parameter with float32 data type.
- Outputs:
Tensor. The shape must be the broadcasted shape of Input “shape” and shapes of alpha and beta. The dtype is float32.
- Raises
TypeError – If neither seed nor seed2 is an int.
TypeError – If neither alpha nor beta is a Tensor.
ValueError – If shape is not a constant value.
- Supported Platforms:
Ascend
Examples
>>> shape = (3, 1, 2) >>> alpha = Tensor(np.array([[3, 4], [5, 6]]), mstype.float32) >>> beta = Tensor(np.array([1.0]), mstype.float32) >>> gamma = ops.Gamma(seed=3) >>> output = gamma(shape, alpha, beta) >>> result = output.shape >>> print(result) (3, 2, 2)