Suppose I execute the following code
W = tf.random.uniform(shape = (100,1), minval = 0, maxval = 1) Z = tf.random.uniform(shape = (100,1), minval = 0, maxval = 1) X = tf.concat([W,Z],1)
The shape of X[:,1] would be [100,]. That is, X[:,1].shape would yield [100,]. If I want to select the second column of X and want the resulting array to have shape [100,1], what should I do? I looked at tf.slice but I’m not sure if it’ helpful.
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Answer
Maybe just use tf.newaxis for your use case:
import tensorflow as tf W = tf.random.uniform(shape = (100,1), minval = 0, maxval = 1) Z = tf.random.uniform(shape = (100,1), minval = 0, maxval = 1) X = tf.concat([W,Z],1) print(X[:, 1, tf.newaxis].shape) # (100, 1)