mxnet.npx.log_softmax

log_softmax(data, axis=-1, length=None, temperature=None, use_length=False, dtype=None)

Computes the log softmax of the input. This is equivalent to computing softmax followed by log.

Parameters

  • data (NDArray) – The input array.

  • axis (int, optional, default='-1') – The axis along which to compute softmax.

  • length (NDArray) – The length array.

  • temperature (double or None, optional, default=None) – Temperature parameter in softmax

  • dtype ({None, 'float16', 'float32', 'float64'},optional, default='None') – DType of the output in case this can’t be inferred. Defaults to the same as input’s dtype if not defined (dtype=None).

  • use_length (boolean or None, optional, default=0) – Whether to use the length input as a mask over the data input.

Returns

out – The output of this function.

Return type

NDArray or list of NDArrays

Examples

>>> data = np.array([1, 2, .1])
>>> npx.log_softmax(data)
array([-1.4170278, -0.4170278, -2.3170278])
>>> data = np.array([[1, 2, .1],[.1, 2, 1]])
>>> npx.log_softmax(data, axis=0)
array([[-0.34115386, -0.6931472 , -1.2411538 ],
    [-1.2411538 , -0.6931472 , -0.34115386]])