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tf.compat.v2.math.softmax

View source on GitHub

Computes softmax activations.

Aliases:

  • tf.compat.v2.nn.softmax
tf.compat.v2.math.softmax(
    logits,
    axis=None,
    name=None
)

This function performs the equivalent of

softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis)

Args:

  • logits: A non-empty Tensor. Must be one of the following types: half, float32, float64.
  • axis: The dimension softmax would be performed on. The default is -1 which indicates the last dimension.
  • name: A name for the operation (optional).

Returns:

A Tensor. Has the same type and shape as logits.

Raises:

  • InvalidArgumentError: if logits is empty or axis is beyond the last dimension of logits.