mindspore.ops.randn_like

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mindspore.ops.randn_like(input, seed=None, *, dtype=None)[source]

Returns a new Tensor with given shape and dtype, filled with a sample (or samples) from the standard normal distribution.

Warning

The Ascend backend does not support the reproducibility of random numbers, so the seed parameter has no effect.

Parameters

  • input (Tensor) – Input Tensor to specify the output shape and its default dtype.

  • seed (int, optional) – Random seed, must be greater or equal to 0. Default: None , and 0 will be used.

Keyword Arguments

dtype (mindspore.dtype, optional) – Designated tensor dtype, it must be float type. If None, mindspore.float32 will be used. Default: None .

Returns

Tensor, with the designated shape and dtype, filled with a sample (or samples) from the "standard normal" distribution.

Raises

  • TypeError – seed is not a non-negative integer.

  • ValueError – If dtype is not a mstype.float_type.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore as ms
>>> from mindspore import Tensor, ops
>>> a = Tensor([[1, 2, 3], [4, 5, 6]])
>>> print(ops.randn_like(a, dtype=ms.float32))
[[ 0.30639967 -0.42438635 -0.20454668]
 [-0.4287376   1.3054721   0.64747655]]