def _symmetric_matrix_square_root(mat, eps=1e-10):
"""Compute square root of a symmetric matrix.
Note that this is different from an elementwise square root. We want to
compute M' where M' = sqrt(mat) such that M' * M' = mat.
Also note that this method **only** works for symmetric matrices.
Args:
mat: Matrix to take the square root of.
eps: Small epsilon such that any element less than eps will not be square
rooted to guard against numerical instability.
Returns:
Matrix square root of mat.
"""
# Unlike numpy, tensorflow's return order is (s, u, v)
s, u, v = tf.svd(mat)
# sqrt is unstable around 0, just use 0 in such case
si = tf.where(tf.less(s, eps), s, tf.sqrt(s))
# Note that the v returned by Tensorflow is v = V
# (when referencing the equation A = U S V^T)
# This is unlike Numpy which returns v = V^T
return tf.matmul(
tf.matmul(u, tf.diag(si)), v, transpose_b=True)
评论列表
文章目录