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.. _op_ai_onnx_Multinomial-7:

Multinomial - version 7
=======================

This page documents version **7** of operator **Multinomial**. See :doc:`Multinomial` for the latest version (since version 22).

- **Domain**: ``ai.onnx``
- **Since version**: 7

Generate a tensor of samples from a multinomial distribution according to the probabilities
of each of the possible outcomes.

**Inputs**

- **input** (*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.

**Outputs**

- **output** (*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.

**Attributes**

- **dtype** (*int*): (Optional) The data type for the elements of the output tensor, if not specified, we will use int32.
- **sample_size** (*int*): Number of times to sample.
- **seed** (*float*): (Optional) Seed to the random generator, if not specified we will auto generate one.

**Type Constraints**

- **T1**: Constrain input types to float tensors.
  Allowed types: tensor(double), tensor(float), tensor(float16).
- **T2**: Constrain output types to integral tensors.
  Allowed types: tensor(int32), tensor(int64).