mindspore.Tensor.random_categorical

Tensor.random_categorical(num_sample, seed=0, dtype=mstype.int64)[source]

Generates random samples from a given categorical distribution tensor.

Parameters

  • num_sample (int) – Number of sample to be drawn. Only constant values is allowed.

  • seed (int) – Random seed.Only constant values is allowed. Default: 0

  • dtype (mindspore.dtype) – The type of output. Its value must be one of mindspore.int16, mindspore.int32 and mindspore.int64. Default: mindspore.int64.

Returns

Tensor, the output Tensor with shape \((batch\_size, num\_samples)\).

Raises

  • TypeError – If dtype is not one of the following: mindspore.int16, mindspore.int32, mindspore.int64.

  • TypeError – If logits is not a Tensor.

  • TypeError – If neither num_sample nor seed is an int.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import numpy as np
>>> import mindspore.common.dtype as mstype
>>> from mindspore import Tensor
>>> x = Tensor(np.random.random((10, 5)).astype(np.float32), mstype.float32)
>>> output = x.random_categorical(8)
>>> result = output.shape
>>> print(result)
(10, 8)