tf.nn.softmax

softmax(
    logits,
    dim=-1,
    name=None
)

Defined in tensorflow/python/ops/nn_ops.py.

See the guides: Layers (contrib) > Higher level ops for building neural network layers, Neural Network > Classification

Computes softmax activations.

This function performs the equivalent of

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

Args:

• logits: A non-empty Tensor. Must be one of the following types: half, float32, float64.
• dim: 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 dim is beyond the last dimension of logits.