tf.segment_prod(data, segment_ids, name=None) Computes the product along segments of a tensor. Read

tf.maximum(x, y, name=None) Returns the max of x and y (i.e. x > y ? x : y) element-wise. NOTE:

tf.argmax(input, dimension, name=None) Returns the index with the largest value across dimensions of a tensor.

tf.abs(x, name=None) Computes the absolute value of a tensor. Given a tensor of real numbers x

tf.reduce_all(input_tensor, reduction_indices=None, keep_dims=False, name=None) Computes the "logical and" of elements across

tf.reduce_min(input_tensor, reduction_indices=None, keep_dims=False, name=None) Computes the minimum of elements across dimensions

tf.igamma(a, x, name=None) Compute the lower regularized incomplete Gamma function Q(a, x). The

tf.log(x, name=None) Computes natural logarithm of x element-wise. I.e., \(y = \log_e x\).

tf.reduce_logsumexp(input_tensor, reduction_indices=None, keep_dims=False, name=None) Computes log(sum(exp(elements across dimensions

tf.zeta(x, q, name=None) Compute the Hurwitz zeta function \(\zeta(x, q)\). The Hurwitz zeta function