问题描述
我有一个形状为 [4,4,2,2]
的矩阵 g
,在这里我需要找到 g [0,0]的等级
, g [1,1]
, g [2,2]
和 g [3,3]
code> 2x2 矩阵.我使用了 tf.rank
运算符,但将 g
视为单个数组并计算等级并为整个矩阵返回单个值.我需要的是相应的 g [i,j]
的等级的 2x2
矩阵.以下是MWE:
I have a matrix g
of shape [4, 4, 2, 2]
where I need to find the rank of g[0, 0]
, g[1, 1]
, g[2, 2]
and g[3, 3]
which are all 2x2
matrices. I used the tf.rank
operator but it treats g
as a single array and computes the rank and returns a single value for the whole matrix. What I need is a 2x2
matrix of ranks of the corresponding g[i, j]
's.Following is a MWE:
import tensorflow as tf
import numpy as np
a = np.array([
[[[ 0., 0.], [ 0., 0.]], [[-1., -1.], [-1., -1.]], [[-2., -2.], [-2., -2.]], [[-3., -3.], [-3., -3.]]],
[[[ 1., 1.], [ 1., 1.]], [[ 0., 0.], [ 0., 0.]], [[-1., -1.], [-1., -1.]], [[-2., -2.], [-2., -2.]]],
[[[ 2., 2.], [ 2., 2.]], [[ 1., 1.], [ 1., 1.]], [[ 0., 0.], [ 0., 0.]], [[-1., -1.], [-1., -1.]]],
[[[ 3., 3.], [ 3., 3.]], [[ 2., 2.], [ 2., 2.]], [[ 1., 1.], [ 1., 1.]], [[ 0., 0.], [ 0., 0.]]]
])
rank = tf.rank(a) # Returns a number
除了使用 for
循环之外,还有什么方法可以获取此排名矩阵?谢谢.
Apart from using a for
loop is there any way to get this rank matrix? Thanks.
推荐答案
我认为TensorFlow中没有任何函数可以计算矩阵等级.一种可能性是使用 tf.linalg.svd
并计算非零奇异值的数量:
I don't think there is any function to compute matrix rank in TensorFlow. One possibility is to use tf.linalg.svd
and count the number of nonzero singular values:
import tensorflow as tf
EPS = 1e-6
a = tf.ones((4, 4, 2, 2), tf.float32)
s = tf.linalg.svd(a, full_matrices=False, compute_uv=False)
r = tf.math.count_nonzero(tf.abs(s) > EPS, axis=-1)
print(r.numpy())
# [[1 1 1 1]
# [1 1 1 1]
# [1 1 1 1]
# [1 1 1 1]]
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