mindspore.ops.Multinomial
- class mindspore.ops.Multinomial(seed=0, seed2=0, dtype=mstype.int32)[source]
Returns a tensor sampled from the multinomial probability distribution located in the corresponding row of tensor input.
Note
The rows of input do not need to sum to one (in which case we use the values as weights), but must be non-negative, finite and have a non-zero sum.
- Parameters
- Inputs:
x (Tensor) - the input tensor containing the cumsum of probabilities, must be 1 or 2 dimensions. Must be one of the following types: float16, float32, float64. CPU and GPU supports x 1 or 2 dimensions and Ascend only supports 2 dimensions.
num_samples (int) - number of samples to draw, must be a nonnegative number.
- Outputs:
Tensor with the same rows as x, each row has num_samples sampled indices.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> x = Tensor([[0., 9., 4., 0.]], mstype.float32) >>> multinomial = ops.Multinomial(seed=10) >>> output = multinomial(x, 2) >>> print(output) # run in CPU [[1 1]]