gather values from 2dim tensor in tensorflow


Hi tensorflow beginner here… I’m trying to get the value of a certain elements in an 2 dim tensor, in my case class scores from a probability matrix.

The probability matrix is (1000,81) with batchsize 1000 and number of classes 81. ClassIDs is (1000,) and contains the index for the highest class score for each sample. How do I get the corresponding class score from the probability matrix using tf.gather?

class_ids = tf.cast(tf.argmax(probs, axis=1), tf.int32)  
class_scores = tf.gather_nd(probs,class_ids)

class_scores should be a tensor of shape (1000,) containing the highest class_score for each sample.

Right now I’m using a workaround that looks like this:

class_score_count = []
for i in range(probs.shape[0]):
    prob = probs[i,:]
    class_score = prob[class_ids[i]]
class_scores = tf.stack(class_score_count, axis=0)

Thanks for the help!


You can do it with tf.gather_nd like this:

class_ids = tf.cast(tf.argmax(probs, axis=1), tf.int32)
# If shape is not dynamic you can use probs.shape[0].value instead of tf.shape(probs)[0]
row_ids = tf.range(tf.shape(probs)[0], dtype=tf.int32)
idx = tf.stack([row_ids, class_ids], axis=1)
class_scores = tf.gather_nd(probs, idx)

You could also just use tf.reduce_max, even though it would actually compute the maximum again it may not be much slower if your data is not too big:

class_scores = tf.reduce_max(probs, axis=1)

Answered By – jdehesa

This Answer collected from stackoverflow, is licensed under cc by-sa 2.5 , cc by-sa 3.0 and cc by-sa 4.0

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