mindspore.ops.normal
- mindspore.ops.normal(shape, mean, stddev, seed=None)[source]
Generates random numbers according to the Normal (or Gaussian) random number distribution.
- Parameters
shape (tuple) – The shape of random tensor to be generated. The format is \((N,*)\) where \(*\) means, any number of additional dimensions.
mean (Tensor) – The mean μ distribution parameter, which specifies the location of the peak, with data type in [int8, int16, int32, int64, float16, float32].
stddev (Tensor) – The deviation σ distribution parameter. It should be greater than 0, with data type in [int8, int16, int32, int64, float16, float32].
seed (int) – Seed is used as entropy source for the Random number engines to generate pseudo-random numbers. must be non-negative. Default: None, which will be treated as 0.
- Returns
Tensor. The shape should be equal to the broadcasted shape between the input shape and shapes of mean and stddev. The dtype is float32.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> shape = (3, 1, 2) >>> mean = Tensor(np.array([[3, 4], [5, 6]]), mindspore.float32) >>> stddev = Tensor(1.0, mindspore.float32) >>> output = ops.normal(shape, mean, stddev, seed=5) >>> result = output.shape >>> print(result) (3, 2, 2) >>> shape = (3, 1, 3) >>> mean = Tensor(np.array([[3, 4, 3], [3, 5, 6]]), mindspore.float32) >>> stddev = Tensor(1.0, mindspore.float32) >>> output = ops.normal(shape, mean, stddev, seed=5) >>> result = output.shape >>> print(result) (3, 2, 3) >>> shape = (3, 1, 3) >>> mean = Tensor(np.array([[1, 2, 3], [3, 4, 3], [3, 5, 6]]), mindspore.float32) >>> stddev = Tensor(1.0, mindspore.float32) >>> output = ops.normal(shape, mean, stddev, seed=5) >>> result = output.shape >>> print(result) (3, 3, 3)