CODEWITHSUNDEEP
pythontensorflowlinear-algebratensorflow2.0
jajamaharaja
jajamaharaja

Reputation: 135

elegant way to do inverse matrix in tensorflow

I would like to invert a bunch of tensors in a list using cholesky decomposition in tensorflow 2, but the resulting code is quite ugly. is there any elegant / more pythonic way to do something like this :

iMps = []
for Mp in Mps :
    cholMp  = tf.linalg.cholesky(Mp)
    icholMp = tf.linalg.inv(cholMp)
    iMp = tf.tensordot(tf.transpose(icholMp),icholMp)
    iMps.append(iMp)

is it possible to replace for loop with other stuff ?, Mps is list of tensors with different size (can i represent it as something else?). is there any way to make it more elegant ?

Upvotes: 1

Views: 584

Answers (1)

user11530462
user11530462

Reputation:

You can achieve this using python Map function.

I have modified your code to create Map function like below. 

def inverse_tensors(Mp):
    cholMp  = tf.linalg.cholesky(Mp)
    icholMp = tf.linalg.inv(cholMp)
    iMp = tf.tensordot(tf.transpose(icholMp),icholMp,axes=0)
    return iMp 

iMps = list(map(inverse_tensors,list_tensors))

Hope this answers your question, Happy Learning!

Upvotes: 1

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