I have a basic question about how to do indexing in TensorFlow.
In numpy:
x = np.asarray([1,2,3,3,2,5,6,7,1,3])
e = np.asarray([0,1,0,1,1,1,0,1])
#nu
Fortunately, the exact case you're asking about is supported in TensorFlow by tf.gather():
result = x_t * tf.gather(e_t, x_t)
with tf.Session() as sess:
print sess.run(result) # ==> 'array([1, 0, 3, 3, 0, 5, 0, 7, 1, 3])'
The tf.gather()
op is less powerful than NumPy's advanced indexing: it only supports extracting full slices of a tensor on its 0th dimension. Support for more general indexing has been requested, and is being tracked in this GitHub issue.