name: Multinomial (GitHub)
shape inference: True
This version of the operator has been available since version 7.
Generate a tensor of samples from a multinomial distribution according to the probabilities of each of the possible outcomes.
dtype: (Optional) The data type for the elements of the output tensor, if not specified, we will use int32. Default value is
sample_size: Number of times to sample. Default value is
seed: (Optional) Seed to the random generator, if not specified we will auto generate one.
input (heterogeneous) - T1: Input tensor with shape [batch_size, class_size], where class_size is the number of all possible outcomes. Each value along the axis zero represents the unnormalized log-probability of each corresponding outcome in a batch.
output (heterogeneous) - T2: Output tensor with shape [batch_size, sample_size], where sample_size is the number of times to sample. Each value along the axis zero represents the outcome of the corresponding sample in a batch.
T1 in ( tensor(double), tensor(float), tensor(float16) ): Constrain input types to float tensors.
T2 in ( tensor(int32), tensor(int64) ): Constrain output types to integral tensors.