Softmax - version 1#

This page documents version 1 of operator Softmax. See Softmax for the latest version (since version 13).

  • Domain: ai.onnx

  • Since version: 1

The operator computes the normalized exponential values for the given input. Inputs are conceptually coerced to a 2D matrix and Softmax is applied on the second dimension. The output tensor has the same shape as the input tensor.

Inputs

  • input (T): The input tensor that’s coerced into a 2D matrix of size (NxD) as described above.

Outputs

  • output (T): The output values with the same shape as input tensor (the original size without coercion).

Attributes

  • axis (int): Describes the dimension Softmax will be performed on. Negative value means counting dimensions from the back.

Type Constraints

  • T: Constrain input and output types to float tensors. Allowed types: tensor(double), tensor(float), tensor(float16).