tf.keras.ops.softmax

Softmax activation function.

tf.keras.ops.softmax(
    x, axis=-1
)

The elements of the output vector lie within the range (0, 1), and their total sum is exactly 1 (excluding the floating point rounding error).

Each vector is processed independently. The axis argument specifies the axis along which the function is applied within the input.

It is defined as:

f(x) = exp(x) / sum(exp(x))

x Input tensor.
axis Integer, axis along which the softmax is applied.

A tensor with the same shape as x.

Example:

x = np.array([-1., 0., 1.])
x_softmax = keras.ops.softmax(x)
print(x_softmax)
array([0.09003057, 0.24472847, 0.66524096], shape=(3,), dtype=float64)