ak.softmax#

Defined in awkward.operations.ak_softmax on line 27.

ak.softmax(x, axis=None, *, keepdims=False, mask_identity=False, highlevel=True, behavior=None, attrs=None)#
Parameters:

  • x – The data on which to compute the softmax (anything ak.to_layout recognizes).

  • axis (None or int or str) – The dimension over which the softmax is computed. If None, the softmax is computed over the innermost dimension. If an int, 0 is the outermost dimension, 1 is the first level of nested lists, etc., and negative values count from the innermost: -1 is the innermost, -2 is the next level up, etc. If a str, it is interpreted as the name of the axis which maps to an int if named axes are present. Named axes are attached to an array using ak.with_named_axis and removed with ak.without_named_axis; also see the Named axes user guide.

  • keepdims (bool) – If False, this function decreases the number of dimensions by 1; if True, the output values are wrapped in a new length-1 dimension so that the result of this operation may be broadcasted with the original array.

  • mask_identity (bool) – If True, the application of this function on empty lists results in None (an option type); otherwise, the calculation is followed through with the reducers’ identities, usually resulting in floating-point nan.

  • highlevel (bool) – If True, return an ak.Array; otherwise, return a low-level ak.contents.Content subclass.

  • behavior (None or dict) – Custom ak.behavior for the output array, if high-level.

  • attrs (None or dict) – Custom attributes for the output array, if high-level.

Computes the softmax in each group of elements from x (many types supported, including all Awkward Arrays and Records). The grouping is performed the same way as for reducers, though this operation is not a reducer and has no identity.

This function has no NumPy equivalent.

Passing all arguments to the reducers, the softmax is calculated as

np.exp(x) / ak.sum(np.exp(x))

See ak.sum for a complete description of handling nested lists and missing values (None) in reducers, and ak.mean for an example with another non-reducer.