tf.matrix_solve_ls(matrix, rhs, l2_regularizer=0.0, fast=True, name=None) Solves one or more linear least-squares problems.

tf.einsum(axes, *inputs) A generalized contraction between tensors of arbitrary dimension. Like

tf.lbeta(x, name='lbeta') Computes ln(|Beta(x)|), reducing along the last dimension. Given

tf.ifft2d(input, name=None) Compute the inverse 2-dimensional discrete Fourier Transform over the inner-most 2

tf.round(x, name=None) Rounds the values of a tensor to the nearest integer, element-wise. For

tf.matrix_band_part(input, num_lower, num_upper, name=None) Copy a tensor setting everything outside a central band in each innermost

tf.add(x, y, name=None) Returns x + y element-wise. NOTE: Add supports broadcasting

tf.matmul(a, b, transpose_a=False, transpose_b=False, a_is_sparse=False, b_is_sparse=False, name=None) Multiplies matrix a

tf.sqrt(x, name=None) Computes square root of x element-wise. I.e., (y = \sqrt{x} = x^{1/2}).

tf.floor(x, name=None) Returns element-wise largest integer not greater than x. Args: