log_sum_exp

tfsnippet.ops.log_sum_exp(x, axis=None, keepdims=False, name=None)

Compute \(\log \sum_{k=1}^K \exp(x_k)\).

\[\begin{split}\begin{align*} \log \sum_{k=1}^K \exp(x_k) &= \log \left[\exp(x_{max}) \sum_{k=1}^K \exp(x_k - x_{max})\right] \\ &= x_{max} + \log \sum_{k=1}^K \exp(x_k - x_{max}) \\ x_{max} &= \max x_k \end{align*}\end{split}\]

Parameters:

• x (Tensor) – The input x.
• axis (int or tuple[int]) – The dimension to take summation. Default None, all dimensions.
• keepdims (bool) – Whether or not to keep the summed dimensions? (default False)
• name (str) – Default name of the name scope. If not specified, generate one according to the method name.

Returns:

The computed value.

Return type:

tf.Tensor